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Phishing attacks occur when cybercriminals trick their victims into sharing personal information, such as passwords or credit card numbers, by pretending to be someone they’re not.
Smart devices are amazing, and they make our lives easier. Smart light bulbs for your home allow you to change the color and schedule lights to turn on and off based on your activities. Internet-connected cameras allow us to monitor our homes with phone apps. Unfortunately, even a device as simple as a light bulb connected to your WiFi can be a gateway for cybercriminals to launch an attack. It happens, and it can happen to you. Cybercriminals launch Internet of Things (IoT) attacks on both individuals and businesses by exploiting the weaknesses in smart devices.
You can prevent an Internet of Things attack by changing default passwords, using multi-factor authentication and updating your device software on a regular basis.
Read more below to learn how IoT attacks work and how to prevent them.
What Is an Internet of Things (IoT) Attack?
The Internet of Things (IoT) is a term used to describe the network of smart devices that include physical objects other than traditional computers, phones and tablets. For example, many homes now have smart TVs, smart light bulbs and other objects with some kind of internet connectivity. The connection allows users to control the devices from their phone or to give the devices special features such as being able to schedule smart light bulbs to turn on and off via an app. Smart TVs can stream content from the internet without plugging in an additional device.
IoT attacks use these devices as a gateway to access a network. Cybercriminals take advantage of the fact that users, including employees at organizations, don’t think to protect their devices the way they protect their computers. Unfortunately, our networks are only as strong as the weakest link. Cybercriminals can take advantage of even a single unprotected IoT device to gain access to a network and steal your data.
Risks of the Internet of Things
Internet of Things devices, just like your computers, need protection in order to avoid cyber attacks. Because they are connected to your home network, if an IoT device is hacked then the cybercriminal can access your network and install malicious software known as malware.
If a cybercriminal gets access to your network, it gives them an opportunity to steal your data. For individuals, this can include Personally Identifiable Information (PII). For organizations, cybercriminals may steal employee PII, along with other sensitive data. Stolen PII can be used for malicious purposes, including stealing money from your bank accounts or even identity theft. This type of attack can be very difficult to recover from.
Sometimes smart devices are hacked for even more disturbing purposes – such as monitoring people inside their homes.
Examples of IoT Attacks
IoT attacks can affect both individuals and organizations that use IoT devices. Here are some examples of frightening IoT attacks:
- Research has connected some identity theft-related cyber attacks to the Internet of Things.
- A cybercriminal hacked into an internet-connected baby monitor and spoke to the baby through the device. Similarly, baby cams have also been hacked – allowing cybercriminals to peer into the victim’s home.
- It was discovered that an IoT car could be hacked at a distance, resulting in the hacker being able to take control of the vehicle.
- Doorbell cameras, which allow homeowners to see who is outside of their door before opening it, have been hacked in order to swat the homeowner – which is a form of harassment that involves lying to the police in order to send a swat team to the victim’s home and put them in danger.
- Smart thermostats, which allow the user to change temperatures using an app, have been hacked by cybercriminals who then changed the user’s settings.
As you can see, any kind of IoT device can be exploited, resulting in serious consequences for the user.
How are DDoS attacks related to the Internet of Things?
DDoS stands for Distributed Denial of Service, which is an attack technique in which cybercriminals disrupt a network by flooding it with bots. The result is that real people have trouble using whatever network was flooded because the server is overloaded by millions of bots instead of real users.
This kind of attack can disrupt businesses, causing a major loss in productivity, and therefore, revenue. It also can have serious consequences for users who may be unable to access necessary services.
Because of the vulnerability of IoT devices, cybercriminals can easily use them as part of what’s called a “botnet,” which enables the DDoS attack. The hacked IoT devices can be commanded to help flood networks alongside other hacked devices. The more unprotected IoT devices out there, the bigger the botnets.
How To Prevent Internet of Things Attacks
Here are some ways to prevent IoT attacks.
1. Practice good cyber hygiene
Cyber hygiene means using everyday best practices to keep safe on the internet. Practices like using unique, strong passwords for every account and device or not sharing unnecessary information online can help prevent a variety of attacks, including IoT attacks.
2. Secure your network
You should secure your WiFi network by changing the default password to a strong, unique password, along with changing the network name and encrypting web traffic in your admin settings. Many people use the default credentials for their WiFi network, which can be easy for cybercriminals to guess.
3. Use a guest network for IoT devices
While some IoT devices need to be on the same network as your computer and phone for full functionality, many IoT devices can be hosted on a guest network instead. This creates an additional barrier for cybercriminals who want to use IoT devices to gain access to your computers or other devices that contain sensitive data. If your critical data and your IoT devices are on different networks, it makes it much more difficult for one to become a doorway into the other.
4. Control account access to IoT devices
Some IoT devices have privacy settings that you can use to help control device access. This is important because the more people who have online access to the device, the more likely one of them will have their account compromised by a cybercriminal who can use that account to access your device for malicious purposes.
Businesses can use Privileged Access Management (PAM) to help control who has access to devices. PAM describes a type of software solution that businesses use to manage privileged accounts with access to sensitive information.
5. Physically secure IoT devices
Make sure IoT devices are physically secure. If someone can reach your physical device, that could help them hack into the device and ultimately the rest of your network and critical data. For example, if your business uses smart cameras to monitor your store, you should keep them out of reach of customers.
6. Disconnect devices when they are not needed
In order to reduce opportunities for cybercriminals to attack, you should disconnect IoT devices when they are not in use. Unplug the smart TV, turn off the baby monitor and otherwise disconnect your devices so they aren’t sitting ducks for cybercriminals.
7. Disable unused features
Similar to the above tip, turning off any features you don’t use in your settings will help reduce the attack surface of your IoT device.
8. Keep device software updated
Tech companies issue security patches as part of software updates, including for IoT devices. These patches are developed to fix security vulnerabilities that have been discovered either by the company or because of a cyber attack. It’s important to always update your software right away in order to prevent these vulnerabilities from being exploited.
Protect Yourself From IoT Attacks
The more pervasive IoT devices become, the more opportunities cybercriminals will have to exploit them for cyber attacks. Protect yourself with the above steps. If there is one thing you should do today to protect yourself online, set strong, unique passwords for each of your accounts and devices.
Keeper Password Manager makes it easy by automatically generating strong passwords and saving them in an encrypted vault. Check out our free 30-day personal trial or 14-day business trial to see how we can simplify cyber hygiene for you or your business. | <urn:uuid:7505b70f-06bc-4592-b7f5-c3add7260bea> | CC-MAIN-2024-38 | https://www.keepersecurity.com/blog/2023/07/11/how-to-prevent-internet-of-things-iot-attacks/ | 2024-09-18T08:07:56Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651886.88/warc/CC-MAIN-20240918064858-20240918094858-00184.warc.gz | en | 0.942596 | 1,692 | 3.59375 | 4 |
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Examining Data Center Energy Consumption and Power Sources
Data centers consume a lot of power — 10 to 50 times more energy per floor space than a typical commercial office building. The largest hyperscale data centers in the world can use as much energy as 80,000 US households. Given the increasingly catastrophic effects of climate change, governments, residents, regulatory agencies, and nonprofit organizations are concerned about the impact of data centers on the environment. In light of that, operators are taking steps to reduce power consumption and improve data center sustainability.
These efforts come at a time when demand for data center resources is skyrocketing. On Sept. 9, 2016, we entered the “Zettabyte Era,” with global Internet traffic reaching a trillion gigabytes. Traffic is expected to exceed 150 billion gigabytes per month in 2023. The average household has 22 connected devices, and mobile devices generate 92.6 percent of traffic. Video streaming accounts for 82 percent of traffic.
Data center operators must consider these demands when developing power management strategies. It’s also important to understand how power is consumed and what climate-friendly power sources are available.
Data Center Power Usage
Industry experts use mathematical models to estimate data center consumption. One authoritative study estimated that data centers accounted for as much as 1.5 percent of global energy use in 2010, and extrapolations predicted that power consumption would skyrocket throughout the decade in line with exponential growth in internet traffic and increased adoption of network-connected devices. That didn’t happen. Data center power consumption has grown slightly since 2010, but not by much. Most estimates still have the number below 2%. Improvements in the energy efficiency of IT equipment and the adoption of alternative energy sources, coupled with server virtualization and cloud migration, caused power consumption to remain relatively constant.
Data Center Power Consumption Per Rack
The average power consumption per data center rack has increased to about 7kW, with almost two-thirds seeing peak demands of about 16kW. The cost to power one rack can be as much as $30,000 per year.
With the proliferation of AI technology, the associated adoption of power-hungry GPUs, and the evolution of the IoT, HPC, and 5G industries, there is little question that data center power consumption per rack and overall will continue to rise for the foreseeable future. It’s more important than ever to track performance metrics and identify sources of inefficiency. It all starts with understanding how much power the various elements of the IT infrastructure consume.
We’ll break down the components of a data center contributing most to overall energy consumption below:
When you think of data centers, servers and server racks typically come to mind. More powerful servers consume more electricity, but today’s servers are generally more efficient than previous generations. The primary source of inefficiency is underutilization, with most servers running at 50 percent capacity or less. Idle servers also waste a significant amount of electricity.
Cooling and Airflow
With the proliferation of high-performance computing (HPC), servers are more powerful, and racks are denser than ever before. On average, data centers use around 40% of their total energy on cooling. Cooling efficiency is important to limit energy expenses and meet overall sustainability goals.
Advancements in storage technology have limited its energy expense within the data center. The number of storage devices needed has decreased as device-level storage capacity has increased. Additionally, solid-state drives use less power than hard-disk drives.
Calculating network power consumption has been complicated by the increasing use of wireless networks. However, the energy consumed by routers, switches, and bridges can be measured easily and accounts for a meaningful chunk of data center power consumption. Efficiencies can be gained by using fewer, higher-capacity devices.
Aside from these four buckets, a lot of miscellaneous infrastructure within the data center uses power. It’s important to keep tabs on everything to maximize power usage efficiency. For example, power distribution systems and UPSs should be investigated as sources of power loss.
Data Center Power Sources
Most data centers use the traditional electric grid for power. The only issue is the electric grid is finite. Utility providers in major markets such as Northern Virginia and Silicon Valley have voiced concerns about available capacity and, in some cases, halted data center development until they can improve infrastructure.
As a result, many large and hyperscale data centers are experimenting with alternative power sources. These options promise to relieve the strain on the grid, reduce greenhouse gas emissions, and minimize data center outages. In fact, Amazon Meta, Microsoft, and Google are the largest buyers of corporate green energy power purchase agreements (PPAs) as they strive to meet net-zero carbon emission goals within the decade.
Wind and Solar
Wind and solar energy are becoming more widely available. Hyperscalers such as Meta and Google are even investing in solar farms to produce their own renewable energy, and the Inflation Reduction Act (IRA) offers incentives for such projects. The IRA also includes tax credits for batteries that can store renewable energy.
Hydrogen accounts for about three-fourths of the known universe, but most is contained in other compounds. Extracting it requires energy and precious metals. Still, hydrogen fuel cells and gas turbines hold promise for a greener energy future.
Geothermal energy uses heat from within the earth to create steam to generate electricity. The U.S. is the world leader in geothermal energy production, but one-fourth of Europe could tap this power source.
Nuclear energy is an emerging data center industry trend. It’s a reliable, carbon-free source of power. Data centers can harness this power by locating near an existing nuclear power plant or adopting emerging small modular reactor (SMR) technologies.
How the Enconnex InfiniRack Can Help
With millions of possible configurations and excellent load ratings of 4,000 lb static and 3,000 lb rolling/dynamic, the Enconnex InfiniRack data center cabinet was designed to adapt to the needs of nearly any data center and is ready to handle ever-growing power densities. Its structural design also maximizes airflow and available useable space. Let us customize an InfiniRack for your data center. The options are virtually limitless. Get in touch today.
Posted by Thane Moore on August 31, 2023
Thane Moore is the Senior Director of Sales Operations & Logistics for Enconnex and has 20 years of experience in the IT infrastructure manufacturing space working for companies such as Emerson and Vertiv. | <urn:uuid:8114361d-53a2-4a23-ae6c-7d258c95ddf8> | CC-MAIN-2024-38 | https://blog.enconnex.com/data-center-energy-consumption-and-power-sources | 2024-09-19T15:36:20Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652031.71/warc/CC-MAIN-20240919125821-20240919155821-00084.warc.gz | en | 0.931769 | 1,363 | 3.28125 | 3 |
Should Hacking Have a Code of Conduct?
For white hats who play by the rules, here are several ethical tenets to consider.
Earlier this year when international cyber-gang Lapsus$ attacked major tech brands including Samsung, Microsoft, Nvidia and password manager Okta, an ethical line seemed to have been crossed for many cybercriminals.
Even by their murky standards, the extent of the breach, the disruption caused, and the profile of the businesses involved was just too much. So, the cybercrime community came together to punish Lapsus$ by leaking information on the group, a move that ultimately led to their arrest and breakup.
So maybe there's honor amongst thieves after all? Now, don't get me wrong; this isn't a pat on the back for cybercriminals, but it does indicate that at least some professional code is being followed.
Which raises a question for the wider law-abiding hacking community: Should we have our own ethical code of conduct? And if so, what might that look like?
What Is Ethical Hacking?
First let's define ethical hacking. It is the process of assessing a computer system, network, infrastructure, or application with good intentions, to find vulnerabilities and security flaws that developers might have overlooked. Essentially, it's finding the weak spots before the bad guys do and alerting the organization, so it can avoid any big reputational or financial loss.
Ethical hacking requires, at a bare minimum, the knowledge and permission of the business or organization which is the subject of your attempted infiltration.
Here are five other guiding principles for activity to be considered ethical hacking.
Hack To Secure
An ethical and white-hat hacker coming to assess the security of any company will look for vulnerabilities, not only in the system but also in the reporting and information handling processes. The goal these hackers is to discover vulnerabilities, provide detailed insights, and make recommendations for building a secure environment. Ultimately, they're looking to make the organization more secure.
Hackers must ensure they have permission, outlining clearly the extent of access the company is giving, as well as the scope of the work they are doing. This is very important. Target knowledge, and a clear scope, help prevent any accidental compromises and establish solid lines of communication if the hacker uncovers anything alarming. Responsibility, timely communication, and openness are vital ethical principles to abide by, and clearly distinguish a hacker from a cybercriminal and from the rest of the security team.
All good hackers keep detailed notes of everything they do during an assessment and log all command and tool output. First and foremost, this is to protect themselves. For example, if an issue occurs during a penetration test, the employer will look to the hacker first. Having a timestamped log of the activities performed, be it exploiting a system or scanning for malware, gives piece of mind to organizations by reminding them that hackers work with them, not against them.
Good notes uphold the ethical and legal side of things; they are also the basis of the report hackers will produce, even when there are no major findings. The notes will allow them to highlight the issues they have identified, the steps needed to reproduce the issues, and detailed suggestions on how to fix them.
Keep Communications Active
Open and timely communications should be clearly defined in the contract. Staying in communication throughout an assessment is key. Good practice is to always notify when assessments are running; a daily email with the assessment run times is vital.
While the hacker might not need to report all the vulnerabilities they find immediately to their client contact, they still should flag any critical, show-stopping flaw during an external penetration test. This could be an exploitable unauthenticated RCE or SQLi, a malicious code execution, or sensitive data disclosure vulnerability. When encountering these, hackers stop testing, issue a written vulnerability notification via email, and follow up with a phone call. This gives teams on the business side the chance to pause and fix the issue immediately if they choose. It's irresponsible to let a flaw of this magnitude go unflagged until the report is issued weeks later.
Hackers should keep their main points of contact aware of their progress and any major issues they discover as they proceed. This ensures everyone is aware of any issues ahead of the final report.
Have a Hacker Mindset
The term hacking was used even before information security grew in importance. It just means to use things in unintended ways. For this, hackers first seek to understand all the intended use cases of a system and take into consideration all its components.
Hackers must keep developing this mindset and never stop learning. This allows them to think both from a defensive and an offensive perspective and is useful when looking at something you have never experienced before. By creating best practices, understanding the target, and creating attack paths, a hacker can deliver amazing results.
About the Author
You May Also Like | <urn:uuid:9f127bdd-b049-4773-9e09-f5cc37023d00> | CC-MAIN-2024-38 | https://www.darkreading.com/vulnerabilities-threats/should-hacking-have-a-code-of-conduct- | 2024-09-20T18:09:23Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725701419169.94/warc/CC-MAIN-20240920154713-20240920184713-00884.warc.gz | en | 0.951644 | 1,001 | 2.984375 | 3 |
Modern Linux desktop environments have gained popularity because they’re easy to use and have a more attractive design than the Linux GUI experience of years past.
Despite these milestones, Linux commands that are run from a terminal are still needed — and extremely useful for the end-user. In this article, I’ll share some commonly used commands for use on your Linux desktop, in addition to some great commands that can save you time.
One of my favorite commands is the cp command. Easy to use, it’s useful for copying one file from one location, to another. An example might be something like this:
cp importantfile newimportantfile
This command makes an exact copy of one file within the same directory. You’re also free to change the directories if you like, such as:
cp /home/$USER/importantfile /home/$USER/Desktop/newimportantfile
This command will then copy the target file from the user’s home directory over to the user’s desktop directory.
One last tip for this command is the ability to create a symlink. To create a symlink (symbolic link) to a file using the cp command, you would type the following:
cp -s importantfile newimportantfile
Using the above command will create an executable shortcut to the original file. This is a nice function in that you can create an executable link to another file you might not otherwise want to relocate for whatever reason.
Much like the dir command, using ls also provides you with a complete file list when run in a specific directory. Where ls begins to distinguish itself is in its ability to arrange files listed. For example, I can use ls to list my files with their corresponding dates and times:
Another useful approach is using ls to sort a list of files, but ignoring the ~backup files for each file listed. Most commonly found with text files, ~backups can be a distraction. So this command is useful in sorting them without the backups filling up the list.
Every once in a while, you’re going to have a rogue program that isn’t functioning as expected. When this happens, I’ve found the killall command is the best approach to putting it out of your misery. Unlike its cousin, the kill command, the killall command offers greater flexibility when you don’t know the PID. Granted, you could run the ps command to gain the PID for the misbehaving program…however this isn’t always practical – especially when it’s slowing down your workstation.
To use kill all, you only need know the name of your executable program. For example, if Google Chrome is locking up, you can kill the program with the following:
killall -v chrome
The above command not only kills Chrome dead in its tracks, it uses the verbose argument to let you know it’s dead and not still running in the background somewhere.
Relying on network manager is a common newbie mistake, especially when they’re dealing with network issues. I’ve seen instances where network manager shows someone as being connected to the network, when in fact they weren’t. To counter this, I prefer to take matters into my own hands by using the ifconfig command. By itself without any options used, ifconfig will give you a clear idea of your IP address, data transferred, among other related information.
To use ifconfig to connect to the network in your office, you can simply use the following two commands: [continued on next page]
This will give you an idea what the name of your device is called. Under Ubuntu, it’s likely to be something like eth0 or eth1. Other distributions however, will likely have a different variation. In any case, make a note of it. Then disconnect the device with the following:
ifconfig eth0 down
With the workstation now disconnected from the network, you’re ready to reconnect it.
ifconfig eth0 up
This brings up the wired interface, reconnecting it to the network. With wired connections, this usually works flawlessly.
Sometimes you will be presented with a situation, where you need to make a directory. In the event this can’t or shouldn’t be done from a GUI, doing so from the Linux command line can prove to be useful. To create a new directory using the terminal, simply type the following:
To take the mkdir command even further, you can also choose specific directory permissions by using the following command:
mkdir -m 200 NameOfNewDirectory
The above command created a new directory with permissions allowing for write only, for the owner of the directory. You can learn which permissions are right for your directory, from this article on chmod.
Passwords are often thought of as a mixed blessing. Remembering how or when to update them, for the sake of keeping security in check, is an even bigger problem. Most users will try to change their passwords from a GUI and usually this works. However, I’ve found that using the Linux command line to change passwords will not only provide greater success, but also give greater control overall.
To change your own user password, use the following command:
This will prompt you for the new password – press enter. Then you’ll be asked to confirm it by retyping it. After hitting enter again, you’ll be alerted to the password being updated successfully. The same approach also works for the root user, so long as you know the original root password.
To enable password aging, where a set password expires and needs to be reset with a new one, follow these commands closely (as root):
Locate the section containing PASS_MAX_DAYS 99999.
Change PASS_MAX_DAYS 99999 to something reasonable to say, 60 days.
The next setting you’ll want to change is how many days ahead of time the user will be alerted to when they need to change their user password. Look for this section, change it to something reasonable like five days. By default, it’s already set to seven.
You can dive deeper into these settings, but for most situations, this will work just fine for new users being added to a workstation. For existing users however, you will need to use the chage command line tool.
On the surface, relying on the Linux command line might seem dated and perhaps even silly. But for those of us who understand how versatile and powerful using the command line can be, the list of commands above are a mere sample of the tremendous power available at our finger tips.
Next time you need to create a directory, change a password or even troubleshoot a network connectivity issue, consider using your Linux terminal first. The end result might surprise you. | <urn:uuid:ffbb6ff0-7215-4fe4-9b9f-bf631978c5ca> | CC-MAIN-2024-38 | https://www.datamation.com/open-source/linux-commands-video-of-time-saving-commands/ | 2024-09-20T17:52:48Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725701419169.94/warc/CC-MAIN-20240920154713-20240920184713-00884.warc.gz | en | 0.905623 | 1,425 | 2.578125 | 3 |
How many blockchains are there
Blockchain technology has revolutionized the way we perceive and handle data, offering a decentralized and secure way to conduct transactions. As the popularity of blockchain continues to grow, one question frequently arises: How many blockchains are there? In this comprehensive guide, we’ll delve into the diverse world of blockchains, exploring their types, applications, and the factors contributing to their proliferation.
Understanding Blockchain Diversity
Public blockchains, such as Bitcoin and Ethereum, are open to anyone and are maintained by a distributed network of nodes. Bitcoin, the pioneer in blockchain technology, laid the foundation for decentralized currencies. Ethereum, on the other hand, expanded the use of blockchain to enable smart contracts and decentralized applications (DApps).
In contrast, private blockchains are restricted to a specific group or organization. These blockchains provide a higher degree of control over access and permissions, making them suitable for enterprise solutions. Companies can use private blockchains for internal record-keeping or supply chain management.
Consortium blockchains strike a balance between public and private blockchains. In this model, a predefined group of participants maintains the blockchain. Consortium blockchains are often adopted by industries where multiple organizations collaborate on a shared platform, such as banking consortia or supply chain networks.
Factors Influencing Blockchain Proliferation
The continuous evolution of blockchain technology has led to the creation of various protocols and consensus mechanisms. Each advancement brings forth a new blockchain, offering improved scalability, security, and functionality. Notable examples include Proof of Stake (PoS), Delegated Proof of Stake (DPoS), and Practical Byzantine Fault Tolerance (PBFT).
Different industries have recognized the potential of blockchain technology to streamline processes and enhance security. As a result, we see the emergence of industry-specific blockchains. For instance, the healthcare sector may utilize blockchain for patient data management, while the logistics industry may employ it for transparent supply chain tracking.
The rise of tokenization has led to the creation of numerous blockchain projects. Tokens, representing digital or physical assets, are created on existing blockchains or through the development of new ones. This has given birth to a multitude of blockchain projects aiming to tokenize real estate, art, and even intellectual property.
As the blockchain ecosystem matures, interoperability between different blockchains becomes crucial. Various projects focus on creating solutions that enable seamless communication between blockchains. This interoperability has the potential to further expand the blockchain landscape by facilitating data and asset transfers across different networks.
How Many Blockchains Are There?
Quantifying the exact number of blockchains is a challenging task due to the dynamic and decentralized nature of the technology. New blockchains are constantly being developed, while existing ones undergo updates and modifications. However, as of the latest available data, there are over 10,000 distinct blockchains, each serving different purposes and industries.
Top Blockchain Projects
Explore some of the most influential and promising blockchain projects, such as Bitcoin, Ethereum, Binance Smart Chain, and Polkadot. Discuss their unique features, use cases, and contributions to the blockchain ecosystem.
Blockchain Adoption Across Industries
Examine how various industries, including finance, healthcare, logistics, and entertainment, are integrating blockchain technology into their operations. Highlight specific use cases and the benefits derived from blockchain implementation.
The Role of Cryptocurrencies in Blockchain Expansion
Discuss the relationship between cryptocurrencies and blockchain technology. Explore how the creation of new cryptocurrencies often leads to the development of dedicated blockchains and ecosystems.
Challenges in the Blockchain Space
Acknowledge the challenges faced by the blockchain industry, such as scalability issues, regulatory concerns, and the environmental impact of certain consensus mechanisms. Offer insights into ongoing efforts to address these challenges.
In conclusion, the blockchain landscape is vast and ever-expanding, with a multitude of blockchains catering to diverse needs. The question of “how many blockchains are there” reflects the dynamic nature of the technology and its continuous evolution. As blockchain technology continues to mature, we can expect even more innovative projects to emerge, shaping the future of decentralized systems.
Editor-in-Chief since 2011. | <urn:uuid:2ace0b92-336a-4e68-8f15-e006698b6a0f> | CC-MAIN-2024-38 | https://blockchaintribune.com/how-many-blockchains-are-there/ | 2024-09-07T10:58:07Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650826.4/warc/CC-MAIN-20240907095856-20240907125856-00348.warc.gz | en | 0.907787 | 851 | 2.859375 | 3 |
As technology advances, the risk of cyber-attacks on financial institutions becomes more prevalent. Fintech companies are at the forefront of this battle, as they rely heavily on technology to provide services and store sensitive data. As a result, cybersecurity has become a critical issue for these companies because the consequences of a successful attack could be disastrous.
In addition to financial loss and damage to reputation, legal and regulatory consequences must be considered. As such, fintech companies are constantly seeking new and innovative ways to safeguard their systems and data from malicious actors.
In this article, we will delve deeper into the world of cybersecurity in fintech, examining the latest trends and best practices in this ever-evolving field.
The Importance of Cybersecurity in Fintech:
Fintech companies have been transforming the financial industry with innovative solutions, but they also face significant cybersecurity risks. Cybersecurity is crucial for fintech companies for several reasons:
- Protecting Customer Data: Fintech companies deal with the sensitive financial data of their customers, including bank account details, personal identification information, and transaction data. A data breach can lead to identity theft, financial fraud, and legal liability. This is especially true for online lenders like CreditNinja, who collect and store sensitive personal and financial information from borrowers.
- Compliance Requirements: Fintech companies must comply with various data protection regulations, such as the GDPR (General Data Protection Regulation) and the PCI DSS (Payment Card Industry Data Security Standard). Non-compliance with these regulations may lead to significant financial penalties and legal repercussions.
- Reputation Management: Cyber-attacks can severely damage the reputation of fintech companies, leading to loss of customers and trust in the brand. This can have long-lasting effects on the company’s growth and revenue.
- Preventing Financial Losses: Fintech companies are highly vulnerable to cyber attacks, which can lead to significant financial losses. Cybercriminals can use techniques like phishing, malware attacks, and social engineering to steal funds or initiate fraudulent transactions. These financial losses can harm not only the fintech companies but also their customers and partners.
- Ensuring Business Continuity: Fintech companies rely heavily on technology, and any system disruption can have significant consequences. For example, cyber attacks can cause system failures, downtime, and data loss, resulting in the inability to provide financial services to customers. Therefore, fintech companies need to have robust cybersecurity measures in place to ensure business continuity.
- Staying Ahead of Competitors: In the highly competitive fintech industry, cybersecurity can be a significant differentiator. Customers are increasingly aware of the importance of data privacy and security and prefer to do business with companies that prioritize cybersecurity. As a result, fintech companies that invest in robust cybersecurity measures can gain a competitive advantage and attract more customers.
How Fintech Companies Apply Cybersecurity:
Fintech companies use various cybersecurity measures to protect their data and customers from cyber-attacks. Here are some common practices:
- Encryption: It is the process of converting sensitive data into an unreadable format. Fintech companies use encryption to protect customer data, such as bank account details and personal information, from unauthorized access. Encryption ensures that even if the data is stolen, cybercriminals cannot read or use it.
- Multi-factor Authentication: Multi-factor authentication (MFA) is a security process that requires users to provide two or more forms of identification to access their accounts. For example, MFA can include a password, a fingerprint, or facial recognition scan. Fintech companies use MFA to prevent unauthorized access to customer accounts.
- Firewall Protection: It’s a network security system that monitors & controls incoming and outgoing network traffic. Fintech companies use firewalls to protect their networks from unauthorized access and malware attacks.
- Regular Updates and Patches: Fintech companies regularly update their software and systems to ensure they are protected against known vulnerabilities. They also install patches and security updates to fix any issues that may arise.
- Employee Training: Fintech companies provide regular cybersecurity training to their employees to educate them on best practices for data protection. Employees are taught to recognize phishing scams, avoid public Wi-Fi networks, and use strong passwords.
In conclusion, cybersecurity is crucial for fintech companies to protect their customers’ data and reputation. Fintech companies use cybersecurity measures such as encryption, MFA, firewall protection, regular updates and patches, and employee training to prevent cyber-attacks.
By implementing these measures, fintech companies can ensure the security of their data and build trust with their customers.
ABOUT THE AUTHOR
IPwithease is aimed at sharing knowledge across varied domains like Network, Security, Virtualization, Software, Wireless, etc. | <urn:uuid:9c280c7c-f076-4e5b-bd31-22c9eecd21a5> | CC-MAIN-2024-38 | https://ipwithease.com/cybersecurity-the-holy-grail-for-fintech-companies/ | 2024-09-08T16:44:16Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651013.49/warc/CC-MAIN-20240908150334-20240908180334-00248.warc.gz | en | 0.94041 | 995 | 2.671875 | 3 |
For the past five years the number of homeless people in the UK has been rising, with Crisis estimating that up to 200,000 families and individuals are now experiencing the most severe forms of homelessness, including rough sleeping.
Although temporary housing was available during the first few weeks of the pandemic, many people have now found themselves back on the streets. The ban on evictions put in place to protect tenants has now been lifted, and Covid-related job losses have increased the threat of homelessness.
According to the latest government figures, 68,250 English households approached councils for ermergency housing support between January and March 2021, indicating that the issue is showing no signs of abating. Many circumstances can lead to homelessness, including relationship breakdowns, fleeing domestic violence, job loss and eviction, but emergency housing services are reserved for people who have suddenly been made homeless and are deemed to be most at risk. For local councils they include care leavers, people with mental health conditions, veterans, pregnant women and those living with disabilities.
Challenges in finding accommodation
Local authorities have a responsibility to ensure residents are housed as quickly as possible in a safe, secure environment. Due to the increasing demand, resources are becoming more and more stretched, and many cases can be complex and difficult to manage from start to finish. Councils work closely with social workers to arrange the right emergency housing and often have to manage distressed, vulnerable people during the interim period.
They are also faced with numerous logistical challenges, which can take time to resolve. In addition to finding housing, it must be suitable for the individual and their needs. For example, a wheelchair user or person with certain medical needs would require access to a working lift or ground floor apartment. If they became locked out of a building due to a technical fault, this issue would need solving extremely quickly. Other individuals may have certain religious requirements, or there might be safeguarding issues. Emergency housing has been even more complicated by the pandemic due to the isolation requirements of different individuals and accommodation blocks. Meanwhile councils are struggling to find permanent accommodation, creating bottlenecks for emergency services.
Managing the demand
Emergency out of hours services within councils can be costly and logistically difficult to operate, and not every local authority is equipped with the staff trained to manage the calls that come in. Councils need the ability to upscale the services they have on offer, ensuring that everyone is able to access a seamless service, no matter what time of the day or night they call. They may wish to consider partnering with emergency out of hours services, retraining staff on the ways these callers can be supported and streamlining processes to meet individuals’ needs more quickly. Call handlers should be following scripts in every situation so that the service remains consistent and covers every base with residents. Local authorities can work with outside organisations to develop these, tailoring them exactly to their needs. For example, in an area with a high refugee population, it may be important to offer more translation options.
Investment in technology can also help local councils to better support their residents. From housing portals to call logs and apps that can link voluntary groups with housing managers, new innovations are constantly developing and could be a key tool in helping to manage the ongoing crisis. In addition, technology can help to support residents through the right channels, meaning they’re contacting the right part of the system immediately.
As government support for those impacted by the pandemic comes to an end, homelessness is likely to continue to increase. In order to meet growing demand, councils will need to collaborate with other organisations to ensure that vulnerable residents can reach emergency services at all times. | <urn:uuid:75d9527a-c01a-4122-8261-25c80e5be3fa> | CC-MAIN-2024-38 | https://www.capita.com/our-thinking/tackling-emergency-homelessness-crisis | 2024-09-08T15:20:09Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651013.49/warc/CC-MAIN-20240908150334-20240908180334-00248.warc.gz | en | 0.975839 | 741 | 2.578125 | 3 |
In recent years, the concept of sustainable finance has emerged as a crucial driver in transforming the global economy. As the world grapples with the twin challenges of climate change and resource depletion, the financial sector has recognized the need to shift from traditional investment strategies towards more sustainable practices. Sustainable finance integrates environmental, social, and governance (ESG) criteria into financial decision-making processes, aiming to foster economic growth that is both inclusive and environmentally responsible. This approach not only addresses the urgent global challenges but also opens new avenues for investors and institutions to contribute positively to society while securing long-term financial returns.
The rise of sustainable finance can be attributed to a growing awareness of the environmental and social impacts of business activities. Investors, regulators, and consumers are increasingly demanding transparency and accountability from companies, urging them to operate in a manner that is mindful of their ecological footprint and societal impact. This shift has led to the development of financial products and services that prioritize sustainability, such as green bonds, social impact bonds, and sustainable investment funds.
Green bonds, for example, are designed specifically to raise capital for projects that have positive environmental outcomes, such as renewable energy installations, energy efficiency upgrades, or sustainable waste management systems. These bonds provide investors with the opportunity to support environmental initiatives while earning returns on their investments. Similarly, social impact bonds focus on financing projects that address social issues, such as affordable housing, education, and healthcare, aligning financial incentives with positive social outcomes.
Another significant development in sustainable finance is the integration of ESG criteria into investment strategies. ESG investing involves assessing companies based on their environmental practices, social impact, and governance structures, allowing investors to make more informed decisions that align with their values. By prioritizing companies that perform well in these areas, ESG investing promotes responsible business practices and encourages companies to adopt more sustainable models.
The adoption of sustainable finance is reshaping the global economy in profound ways. One of the most notable impacts is the redirection of capital towards industries and projects that contribute to sustainable development. This shift is driving innovation and creating new markets for green technologies, renewable energy, and sustainable infrastructure. As a result, economies are becoming more resilient and less reliant on fossil fuels, paving the way for a transition to a low-carbon future.
Moreover, sustainable finance is playing a critical role in addressing the funding gap for achieving the United Nations Sustainable Development Goals (SDGs). The SDGs outline a comprehensive blueprint for addressing global challenges, including poverty, inequality, and climate change, by 2030. However, achieving these goals requires substantial financial resources, estimated at trillions of dollars annually. Sustainable finance provides a mechanism for mobilizing the necessary capital by aligning the interests of investors with the objectives of sustainable development.
The economic benefits of sustainable finance extend beyond environmental and social impacts. Companies that adopt sustainable practices often experience improved financial performance due to increased efficiency, reduced risks, and enhanced reputations. For instance, businesses that invest in energy efficiency can lower their operational costs, while those that prioritize good governance can mitigate legal and reputational risks. Additionally, companies that demonstrate a commitment to sustainability are more likely to attract and retain customers and employees who value corporate responsibility.
As the demand for sustainable finance grows, so does the need for professionals who are equipped with the skills and knowledge to navigate this evolving landscape. Sustainable finance training has become an essential component in building a workforce capable of driving the transition towards a more sustainable global economy. This training encompasses a broad range of topics, including ESG analysis, impact investing, climate risk assessment, and sustainable business models.
One of the key aspects of sustainable finance training is the development of expertise in ESG integration. This involves understanding how to evaluate companies based on their environmental, social, and governance performance, and how to incorporate these factors into investment decisions. Training programs often include modules on conducting ESG research, interpreting ESG data, and applying ESG criteria in portfolio management. By equipping professionals with these skills, sustainable finance training helps to ensure that investment decisions are aligned with broader sustainability goals.
Climate risk assessment is another critical area covered in sustainable finance training. As climate change continues to pose significant risks to the global economy, financial institutions must be able to identify and manage these risks effectively. Training in this area focuses on understanding the physical and transition risks associated with climate change, such as extreme weather events, regulatory changes, and shifts in consumer behavior. By incorporating climate risk assessments into their operations, financial institutions can better protect their assets and support the transition to a low-carbon economy.
Moreover, sustainable finance training emphasizes the importance of impact investing, which aims to generate measurable social and environmental benefits alongside financial returns. This approach encourages investors to go beyond traditional financial metrics and consider the broader impact of their investments. Training in impact investing typically covers topics such as impact measurement, investment strategies, and reporting standards, enabling professionals to make investment decisions that contribute to positive societal outcomes.
Despite its rapid growth, sustainable finance faces several challenges that must be addressed to fully realize its transformative potential. One of the main obstacles is the lack of standardized definitions and metrics for measuring sustainability. The absence of uniform criteria makes it difficult for investors to compare companies and assess their true impact, leading to concerns about greenwashing—the practice of misleading stakeholders about the environmental benefits of a product or service.
To address this issue, there have been efforts to develop standardized frameworks and reporting guidelines, such as the Task Force on Climate-related Financial Disclosures (TCFD) and the Global Reporting Initiative (GRI). These initiatives aim to enhance transparency and provide investors with the information needed to make more informed decisions. However, further work is needed to harmonize these standards globally and ensure consistent implementation across different markets.
Another challenge is the limited availability of sustainable investment opportunities, particularly in emerging markets. While sustainable finance has gained traction in developed economies, many developing countries still face barriers such as limited access to capital, inadequate infrastructure, and weak regulatory frameworks. To overcome these obstacles, there is a need for greater international collaboration and investment in capacity-building initiatives that support the growth of sustainable finance in these regions.
Looking ahead, the future of sustainable finance will likely be shaped by technological advancements and innovations in financial products and services. The rise of digital finance, for instance, has the potential to enhance the accessibility and efficiency of sustainable investments. Technologies such as blockchain and artificial intelligence can improve data transparency, reduce transaction costs, and enable new models of sustainable financing, such as peer-to-peer lending platforms for renewable energy projects.
Furthermore, as the global community continues to grapple with the impacts of climate change, there will be an increasing emphasis on resilience and adaptation. This will drive demand for financial products that support climate adaptation measures, such as insurance for climate-related risks and financing for climate-resilient infrastructure.
Sustainable finance is transforming the global economy by redirecting capital towards initiatives that promote environmental stewardship, social responsibility, and good governance. Through innovative financial products and the integration of ESG criteria, sustainable finance is fostering a more resilient and inclusive economic system. As the field continues to evolve, sustainable finance training will play a vital role in equipping professionals with the skills needed to navigate this dynamic landscape. Despite the challenges that lie ahead, the momentum behind sustainable finance is undeniable, and its potential to drive positive change on a global scale is immense. By aligning financial practices with sustainable development goals, the world can move closer to achieving a more sustainable and equitable future. | <urn:uuid:88bcca0e-5965-4ee6-b77f-8d3178231b98> | CC-MAIN-2024-38 | https://diversinet.com/how-sustainable-finance-is-transforming-the-global-economy/ | 2024-09-11T03:53:12Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651343.80/warc/CC-MAIN-20240911020451-20240911050451-00048.warc.gz | en | 0.938767 | 1,513 | 3.1875 | 3 |
For the first time, a team of researchers at the California Institute for Telecommunications and Information Technology (Calit2), have designed a 9-panel, 3-D visualization display from HDTV LCD flat-screens developed by JVC.
The technology, dubbed "NexCAVE," was inspired by Calit2’s StarCAVE virtual reality environment. The StarCAVE’s pentagon shape and 360-degree views make it possible for groups of scientists to venture into worlds as small as nanoparticles and as big as the cosmos.
"It’s always been our dream to make a projector-free LCD flat panel CAVE," says Tom DeFanti, Calit2 Research Scientist. "The trick was to get the form of the huge StarCAVE into the space of a living room. We took a speculative leap by overlapping 9 panels, and it turned out better than we thought."
When paired with polarized stereoscopic glasses, the NexCAVE’s modular, micropolarized panels and related software will make it possible for a broad range of scientists — from geologists and oceanographers to archaeologists and astronomers — to visualize massive datasets in three dimensions, at unprecedented speeds and at a level of detail impossible to obtain on a myopic desktop display.
The NexCAVE’s data resolution is close to human visual acuity (or 20/20 vision). The 9-panel, 3-column prototype that the team developed for Calit2’s VirtuLab has a 6000×1500 pixel resolution, while the 21-panel, 7-column version boasts 15,000×1500-pixel resolution.
"The NexCAVE’s technology delivers a faithful, deep 3-D experience with great color saturation, contrast and really good stereo separation," explains DeFanti. "The JVC panels’ xpol technology circularly polarizes successive lines of the screen clockwise and anticlockwise and the glasses you wear make you see, in each eye, either the clockwise or anticlockwise images. This way, the data appears in three dimensions. Since these HDTVs are very bright, 3-D data in motion can be viewed in a very bright environment, even with the lights in the room on”.
The NexCAVE’s LCD screens are scalloped "like turtle shells," which allows the screens’ bezels (frames) to be minimized by half because the screens are tucked behind one another.
DeFanti and his colleagues developed the NexCAVE technology at the behest of Saudi Arabia’s King Abdullah University of Science and Technology (KAUST), which established a special partnership with UC San Diego last year to collaborate on visualization and virtual-reality research.
The KAUST campus includes a Geometric Modeling and Scientific Visualization Research Center featuring a 21-panel NexCAVE and several other new visualization displays developed at Calit2.
According to DeFanti the team’s next goal is to make a screens that won’t require the use of special glasses. "And someday we hope to have organic LED screens with no bezels,” he concludes. | <urn:uuid:ed7e6b24-90e5-4a8f-8906-374192bb1328> | CC-MAIN-2024-38 | https://www.biz-news.com/hdtv/surround-3-d-tv-to-take-over-the-living-rooms/ | 2024-09-13T10:50:11Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651513.89/warc/CC-MAIN-20240913101949-20240913131949-00748.warc.gz | en | 0.932097 | 655 | 2.734375 | 3 |
Microsoft & Others Catalog Threats to Machine Learning Systems
Thirteen organizations worked together to create a dictionary of techniques used to attack ML models and warn that such malicious efforts will become more common.
November 2, 2020
In May 2016, Microsoft introduce a chatbot on Twitter, dubbed "Tay," that attempted to hold conversations with users and improve its responses through machine learning (ML). A coordinated attack on the chatbot, however, caused the algorithm to start tweeting "wildly inappropriate and reprehensible words and images" in the first 24 hours, Microsoft stated at the time.
For the software giant, the attack demonstrated that the world of ML and artificial intelligence (AI) would come with threats. Last week, the company and an interdisciplinary group of security professionals and ML researchers from a dozen other organizations took a first stab at creating a vocabulary for describing attacks on ML systems with the initial draft of the Adversarial ML Threat Matrix.
The threat matrix is an extension of MITRE's ATT&CK framework for the classification of attack techniques. The information should help secure not just the developers of ML systems but companies that are using those systems as well, says Jonathan Spring, senior member of the technical staff of the CERT Division of Carnegie Mellon University's Software Engineering Institute.
"If you're using a machine learning system — even if you're not the one developing it — you should make sure that your broader system is fault tolerant," Spring says. "You should be looking for people pressing on [attacking] the broader machine learning part of your system. And you can do those checks on your system without really knowing too much about how the machine learning is working."
Machine learning has become a key factor in companies' plans to transform their businesses over the next decade. Yet, most firms consider adversarial attacks on ML to be a future threat, not a current risk. Only three of 28 companies surveyed by Microsoft, for example, thought they had the tools in place to secure their ML systems.
Actual attacks on ML systems inhabit a spectrum of generic exploits of vulnerabilities to specific ML-reliant attacks on models or data. In one case, an attacker exploited a misconfiguration in the system of the facial recognition firm ClearviewAI to gain access to some of its infrastructure, which could have resulted in the attacker polluting the dataset.
"[W]e believe the first step in empowering security teams to defend against attacks on ML systems, is to have a framework that systematically organizes the techniques employed by malicious adversaries in subverting ML systems," Microsoft's researchers said in a blog post announcing the Adversarial ML Threat Matrix. "We hope that the security community can use the tabulated tactics and techniques to bolster their monitoring strategies around their organization's mission-critical ML systems."
The Adversarial ML Threat Matrix is based on the MITRE ATT&CK framework, which has grown in popularity since it was originally released in 2015. More than 80% of companies use the framework as part of their security response programs, according to an October survey published by the University of California at Berkeley and McAfee in October.
The threat matrix is the work of a baker's dozen of different organizations. Microsoft, Carnegie Mellon University's Software Engineering Institute, and MITRE are collaborating with Bosch, IBM, NVIDIA, Airbus, Deep Instinct, Two Six Labs, the University of Toronto, Cardiff University, PricewaterhouseCoopers, and Berryville Institute of Machine Learning on the framework. The team used a variety of case studies to identify the common tactics and techniques used by attackers and describe them for security researchers.
At the DerbyCon conference in 2019, for example, two researchers showed a way to use a data-based attack against Proofpoint's email security system to extract the training data and create a system that could be used by an attacker to as a test platform for creating email attacks that would not be caught by the messaging security product. Microsoft also mined its experience with the Tay chatbot to inform the threat matrix.
While the risks to ML and AI systems are real, they aren't the most common threats, Charles Clancy, chief futurist and general manager of MITRE Labs, said in an interview. "Typically, AI isn’t the first avenue for our adversaries, particularly regarding attacking our critical infrastructure," he said. "There's a truism in the power industry that the most dangerous adversaries to our electric grid are — squirrels. Keep that in mind — there are risks to AI, but it's also extremely valuable."
The Adversarial ML Threat Matrix is only the first attempt to capture all the threats posed to ML systems. The companies and security researchers called for others to contribute their experiences as well.
"Perhaps this first version of the Adversarial ML Threat Matrix captures the adversary behavior you have observed — [i]f not, please contribute what you can to MITRE and Microsoft so your experience can be captured," CMU's Software Engineering Institute stated in its blog post. "If the matrix does reflect your observations, is it helpful in communicating and understanding this adversary behavior and explaining threats to your constituents? Share those experiences with the authors as well, so the matrix can improve!"
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October 22, 2024 | <urn:uuid:cd4fe3b1-4f30-4fef-a23f-d0fd97551d03> | CC-MAIN-2024-38 | https://www.darkreading.com/vulnerabilities-threats/microsoft-others-catalog-threats-to-machine-learning-systems | 2024-09-13T11:05:51Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651513.89/warc/CC-MAIN-20240913101949-20240913131949-00748.warc.gz | en | 0.953788 | 1,136 | 2.59375 | 3 |
The reopening of schools in 2020 is still a decision fraught with uncertainty, one of the many things made more difficult by the COVID-19 pandemic. Nobody really knows what is best when it comes to education during a pandemic. The contingency plans prepared by authorities everywhere are probably based on studies and on the limited experiences of those countries that decided to take more risks. However, these may prove to be of little use in many instances. With lockdown measures still in question, especially with the number of cases on the rise, distance learning seems to be the safer bet.
Since there is no one-size-fits-all strategy available at this time, some schools will probably return to traditional teaching methods, while others have already announced plans to resort to holding classes remotely.
Reopening Schools Across the U.S. – A Risky Decision
A recent study shows that the reopening of schools without serious testing and contact tracing measures may create a second wave of the pandemic, either in December 2020 or February 2021. The research team involved in the study created a COVID-19 transmission model based on the particularities of the pandemic reported by UK sources. Considering the two strategies put forward for the reopening of schools – full-time or part-time (by rotation) –, six different scenarios have emerged. To sum up, the study showed that a strong recurrence of the pandemic can be avoided by aggressively testing all individuals showing symptoms of COVID-19, followed by effective contact tracing.
However, scientists also think that reopening schools may lead to a second and even more dangerous wave of the pandemic in December 2020, or February 2021, if the testing for active infection, followed by contact tracing those infected, falls below standards. Their findings suggest that this second wave can be more than twice as severe as the current one.
The Importance of Going Back to School
With these risks in mind, it’s also important to consider the fact that schools and daycare centers provide not only access to proper education, but also a safe and supportive environment for children and students. In doing so, schools also provide jobs for teachers and other personnel, while enabling parents and caregivers to work. Schools are among the most important institutions in the US because they provide services that fit in with the needs of children and parents alike. This is the reason why returning to school is a big step towards returning to normal because it allows parents to work and students to grow and evolve within their own communities.
According to the US Centers for Disease Control and Prevention (CDC), “school closure disrupts the delivery of in-person instruction and critical services to children and families, which has negative individual and societal ramifications. The best available evidence from countries that have opened schools indicates that COVID-19 poses low risks to school-aged children, at least in areas with low community transmission, and suggests that children are unlikely to be major drivers of the spread of the virus.” The CDC advises policymakers to keep in mind that reopening schools across the US is extremely important for the future of American children and, by extension, for the future of the country.
Back to School. Here’s What We Already Know
Reopening both schools and society itself is the ultimate goal of policymakers everywhere. However, when pursuing this important goal it’s important to take into account all the things we already know about the new coronavirus pandemic and how it spreads among children and young adults. An important number of schools in the US have already begun traditional classes, with states like Georgia, Indiana, Louisiana, Mississippi, and Tennessee being busy reopening their schools. The US is not alone in reopening schools this autumn. Denmark, the first country in Europe to impose a lockdown, reopened its schools in April, while Israel followed suit in May. Countries such as Taiwan, Nicaragua, and Sweden never closed their schools at all. For some of them, this decision came at a cost.
Several school employees have died of COVID-19 complications in Sweden, and the same thing may be occurring even closer to home. When Georgia, Indiana, Louisiana, Mississippi, and Tennessee schools that resumed traditional classes have also seen a resurgence of cases, other schools announced their decision to start the school year remotely.
The different experiences of countries around the world with the reopening of schools show that there is no one-size-fits-all strategy to prevent the spread of the virus in schools and communities. But one thing is certain: going back to school will be a very different experience this year. Compliance with protection measures is extremely important, and so is considering other strategies when it comes to schooling. For the moment, full-time remote learning and part-time rotation systems remain worthy strategies in fighting the COVID-19 pandemic. | <urn:uuid:f3b611f4-db01-4e5b-ad3b-30595af695eb> | CC-MAIN-2024-38 | https://educationcurated.com/editorial/back-to-school-means-saying-yes-to-distance-learning-heres-why/ | 2024-09-14T17:29:25Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651580.73/warc/CC-MAIN-20240914161327-20240914191327-00648.warc.gz | en | 0.971076 | 978 | 2.96875 | 3 |
We have seen robots diversifying in every possible field; we have robots for the military, outer space, exploration, farms, car industry, hospitals, retail stores, entertainment, and the list goes on.
Now the soccer robot is prepped up to solve the long-lived traffic problem. How? For that, the bot should be well trained and fed with historical traffic data and it should also have the potential to recognize when car can cause trouble.
Currently, the artificial intelligence that keeps the bots moving is being tested as a new way to keep clearways in Sydney moving.
“It’s a system that would automatically detect that a vehicle blocking a clearway based on traffic data,” said developer Jayen Ashar, the lead engineer at Clearway Tech.
The bot will be trained in such a way that, after it finishes the analysis, the system will automatically contact the NSW Transport Management Centre, asking for a tow-truck to be dispatched to remove a parked or broken-down car causing a hold-up.
“It’s finding the patterns when a vehicle is blocking a clearway," Ashar said. Ashar was a member of the University of NSW’s autonomous robot soccer team for over a decade, and he mentioned applying some theory from the football field to traffic problems. | <urn:uuid:9970b7b8-40ed-4387-b97e-3ef8f03ab734> | CC-MAIN-2024-38 | https://www.ciobulletin.com/it-services/ai-robots-to-control-traffic | 2024-09-15T22:44:58Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651668.26/warc/CC-MAIN-20240915220324-20240916010324-00548.warc.gz | en | 0.947179 | 272 | 2.609375 | 3 |
We are only a few years into the ’20s, but by any measure, it’s been an eventful decade so far. It’s frequently been said that we’ve already seen five years’ worth of technology-driven change packed into the last 18 months, mostly out of necessity, since the start of the Covid-19 pandemic. And artificial intelligence (AI) development certainly hasn’t lagged behind.
Back in 2019, in what seems like another lifetime, I had a stab at picking out what I thought were the most significant developments so far in the history of AI. With everything that has developed since then, I thought it would be a good idea to round up the biggest breakthroughs and most significant developments of the current decade.
Unsurprisingly, many of the biggest and most headline-grabbing developments have been in the area of healthcare. However, ongoing research has also pushed boundaries of what is possible with natural language processing and vehicle autonomy.
A major AI success story of the pandemic period has been the role it has played in helping with vaccine development. Developing new vaccines generally takes many years, but scientists had candidate vaccines at the human trial stage by March 2020, just three months after the first reported cases of Covid-19 emerged in China. This was done using machine learning models to blitz through the piles of data on immune system response and quickly identify which compounds were likely to be most effective.
Leading Chinese AI developer Baidu made its LinearFold algorithms available to the global scientific community. This was able to assist with the development of the new breed of mRNA vaccines that work by enabling cells to create proteins that provoke a response from the immune system.
Of course, creating a vaccine was not the end of the story due to the ability of Covid-19 to rapidly mutate into new variants. An algorithm created by the University of Southern California has been able to hugely speed up the time it takes to assess the suitability of vaccine candidates when presented with mutations and variants that could possibly make existing vaccines less effective. The algorithm has been shown to be capable of eliminating 95% of potential vaccine compounds within seconds – a process that traditionally takes several months.
Outside of vaccine development, AI has also been used to assist with contact tracing – one company uses computer vision to identify those who have been in close proximity with someone who has tested positive. On the other hand, it has to be noted that not every AI covid story is a success – several studies have reported that attempts to create algorithms that can diagnose the infection from X-rays and other medical images have not worked out.
In 2020, OpenAI unveiled the latest iteration of its Generative Pre-Trained Transformer language modeling algorithms. This deep learning model is capable of creating the most convincing and flexible natural language yet seen from an AI system. GPT-3 is even capable of automatically generating computer code, meaning it can theoretically be used to create computer software programs itself.
This is achieved by creating the most sophisticated and complex set of natural language algorithms ever devised, consisting of 175 billion machine learning parameters. This gives it the ability to create text (or code) in natural language, answer questions, automatically summarise and annotate content, and translate between different languages.
GPT-3 is not yet widely available outside of academic use, and its creators have said that due to its power, careful consideration has to be given to how it can be used ethically and responsibly – for example, we have to be sure that its output will be affected as little as possible by bias in the datasets it is trained on – which includes the public crawl set scraped from millions of web pages – and we all know that it isn’t uncommon to find bias online!
Alphafold – protein folding
In November 2020, Google subsidiary DeepMind announced that its AI had cracked a problem that had been challenging the scientific community for more than 50 years – namely, predicting the results of protein folding. This is the biological process that governs the way proteins create new copies of themselves – often thought of as nothing less than the fundamental building block of life itself. DeepMind’s AlphaFold algorithm allows the result of protein folding to be predicted more accurately than ever before, which has tremendous implications for everything from curing diseases to creating new, sustainable, and environmentally-friendly replacements for industrial materials and chemicals.
To mark this achievement, DeepMind released a public dataset and research tool including its predictions for all of the proteins cataloged so far in the human body - around 350,000 – only a third of which had previously been modeled. By the end of the year, this is planned to grow to 130 million protein structures. DeepMind's co-founder Demis Hassabis describes it as “The biggest contribution an AI system has made so far to advancing scientific knowledge.”
Tesla Level 2 autonomous driving hits the road, and robotaxis arrive in China
So they are a little behind schedule – Tesla CEO Elon Musk has famously claimed that he would have fully autonomous (level 5) vehicles ready by the end of 2020 (if he did, he hasn’t shown it to anyone yet!)
But 2021 did mark the rollout of a significant milestone – commercially available level 2 autonomy, available as an update to some owners of vehicles equipped with the Autopilot upgrade. Level two autonomous vehicles are capable of carrying out much of the basic driving behavior that would be expected of a human driver on a regular road but require that a human is "hands-on" with the controls at all times and ready to take over if the computer makes a mistake. Tesla is currently in the process of moving its autonomous vehicle research away from the radar and lidar sensor arrays which is currently used by most vehicle manufacturers, and focusing on systems that can navigate entirely using cameras. This would mean they are, in human terms, operating on vision alone – much as human drivers do. The update has been rolled out slowly – rather than being made available to all Tesla drivers right away – to allow the company to collect data and monitor its performance in a controlled manner.
Meanwhile, in China, Baidu launched the first autonomous “robotaxi” service, called Apollo Go, into public use in 2020. Its vehicles are still co-piloted by humans for reasons of safety and customer confidence, but the service operating in Guangzhou is capable of making autonomous journeys between 200 "stops." Baidu aims to expand the service – which also operates in Beijing, Changsha, and Cangzhou - to 30,000 vehicles operating across 30 Chinese cities by 2023.
The first autonomous trans-Atlantic crossing – maybe!
So, it hasn’t all been smooth sailing for the Mayflower – the ship that was due to make the world’s first fully autonomous journey between the UK and USA in 2020. After a lengthy delay due to Covid, it eventually set off in June this year. Unfortunately, though, it was forced to return to Plymouth, England, just a few days into its projected three-week journey due to damaging its exhaust system. The original Mayflower, which completed the journey carrying pilgrims to the new world in 1620, also had to turn back – twice – before it successfully made the crossing, so everyone is confident that the new Mayflower – a collaborative project involving IBM and the non-profit research organization ProMare – will make it eventually!
The Mayflower is a scientific research vessel – a particularly important use case for autonomous ships due to their need to spend long periods at sea without needing to return to port. It's also very environmentally friendly, as the lack of facilities required for human safety and comfort means it is very light and requires little energy to propel it.
The autonomous Mayflower gathers data from 30 sensors, including radar, GPS, cameras, and depth-detectors. This is then passed to the "AI Captain" – an edge-computing application that can make decisions without needing to relay the information to a base station on land. Assuming it completes its journey as expected, this will go down as a fantastic milestone in the history of autonomous shipping and AI in general. | <urn:uuid:961f4d8c-356b-4703-ba8e-a735270102e7> | CC-MAIN-2024-38 | https://bernardmarr.com/the-biggest-artificial-intelligence-milestones-of-the-decade-so-far/?paged1119=2 | 2024-09-18T10:56:00Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651895.12/warc/CC-MAIN-20240918100941-20240918130941-00348.warc.gz | en | 0.969265 | 1,678 | 3.109375 | 3 |
Windows 10 build 1809 was used for this test. Two processor cores and 3 GB of RAM are assigned to each VM.
The processor requirements for Windows 10 can change based on the build number and patch level. Processing and memory requirements for Windows 10 have increased over time with newer builds. One of the best ways to reduce the CPU and disk load for a Windows virtual machine is to use the . This tool is a consolidated interface that can be used to change the behavior of virtual machines to reduce their hardware requirements. Be careful if choosing the most-restrictive configurations, which can cause applications or even Windows features to stop working. This tool is designed to reduce the effort it takes to optimize Windows. It requires testing of the configuration to ensure sure all user applications still work correctly with the optimizations applied.
Another tool that was mentioned previously in this paper is . This tool redirects user data to one or more file shares based on certain conditions. This capability allows directing different types of data to different locations. User-profile data and documents can be pointed to home directories that are replicated. Temporary data such as application temp files that do not need to be saved are placed on volumes with no data protection. This approach reduces replication traffic and the overall storage load.
All user profiles are redirected to file shares to capture the user load for this test. The ability of the PowerStore array to host file shares consolidates storage management and reduces backup complexity. A single PowerStore appliance can host all end-user data.
The applications can be layered using VMware AppVolumes. It greatly improves application management and updating by removing the applications from the base image and managing them independently. When an update is required, the layered application is updated externally and the updated version is applied to the environment.
Layering applications enables rapid application provision and updating. The individual applications are managed independently with the ability to present groups of applications to user groups. The advantage is quick deployment of layered applications to new users or groups of users. | <urn:uuid:12acd176-8e1e-4cdb-83a0-f6c42c2c6ebb> | CC-MAIN-2024-38 | https://infohub.delltechnologies.com/en-us/l/powerstore-1-500-vmware-horizon-vdi-users/guests-4/ | 2024-09-19T17:47:29Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652055.62/warc/CC-MAIN-20240919162032-20240919192032-00248.warc.gz | en | 0.933983 | 402 | 2.515625 | 3 |
VoIP technology has opened up new possibilities in efficient, cost-effective communications. However, like other Internet-based technology, it remains vulnerable to cyber attacks.
Towards the end of 2016, Network World published an article warning about an increasing number of VoIP attacks. If your company plans to keep safely making calls over the Internet, it’s important to guard against cyber criminals and their unlawful and harmful intrusions.
How Can You Protect Your VoIP from Cyber Attacks?
Rely on monitoring. Monitoring technology can detect suspicious activities in your VoIP network, such as calls you can’t identify (and that may wind up costing you hundreds or thousands of dollars). When you use monitoring as one of your defenses, you’re adopting a proactive approach that emphasizes catching problems before they become severe.
Use firewalls. Firewalls are potent defenses against unauthorized VoIP traffic. They can pick up on attacks and strange call patterns.
Secure every piece of hardware on your VoIP network. Any unprotected hardware is a point of vulnerability for cyber criminals to exploit. Outdated software and hardware may contain security holes that need to get addressed.
Adopt encryption. Companies will find it beneficial to use encryption along every point on a channel of communication, decreasing the chances of an intrusion and loss of privacy.
Implement stricter user access. Who is allowed to use your VoIP system, and under what circumstances? The use of strong, complex passwords is critical, and there are other useful authentication measures, such as checking the device or network before permitting access.
Ultimately, VoIP security should involve a multi-layered approach and not simply one form of defense. Don’t hesitate to contact us for advice and assistance with strengthening security for your VoIP technology. | <urn:uuid:7689a3e7-8ba8-4b52-947f-da726a91d8b5> | CC-MAIN-2024-38 | https://www.aetechgroup.com/category/voip/ | 2024-09-19T18:10:35Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652055.62/warc/CC-MAIN-20240919162032-20240919192032-00248.warc.gz | en | 0.92745 | 364 | 2.53125 | 3 |
How Biased AI is Holding Us Back, and Two Things We Can Do About it
Like Hollywood and Washington, D.C., Silicon Valley and the tech world must step up to combat entrenched biases.
From the largest and most successful tech corporations to the smallest start-ups just finding their footing, most will agree that increasing diversity is in the best interests of customers, employees, and the general public. However, we in the tech world often fail to recognize the impact of our own biases. We sometimes think that, because our products and services are based on 0’s and 1’s, everything we put out into the world is fair and logical. Not true! This International Women’s Day (Thursday), let’s take a closer look at the biases that inhabit so much of our work, as well as some of the ways we can work toward a culture of inclusive AI.
The theme of this year’s International Women’s Day is #PressforProgress, a call for gender parity across countries, industries, and all kinds of organizations. As we celebrate the achievements of women and push for equality, we should recognize that harmful biases affect a range of communities. Examples of biased AI algorithms that have held us back include:
Microsoft and IBM’s facial recognition technologies failing to identify women, especially black women, at much higher rates than white men
YouTube and Twitter blocking LGBTQ content that would otherwise be deemed “safe-for-work”
Facebook’s “trending topics” list incorporating alleged liberal biases
Apple’s “animoji” feature portraying emoji created by Asian users as constantly squinting
Yes, each of these companies has pledged to address these controversial algorithms. And, there is no evidence that any of the algorithms behind them arose out of conscious decisions to exclude anyone. Still, we as an industry cannot pretend they are isolated incidents. The fact is that products and services based on artificial intelligence necessarily reflect the biases of the people who designed them.
The good news is that this simple truth also shows us the way forward. Engaging a diverse set of stakeholders throughout the AI lifecycle -- ensuring that those who are coding, developing the algorithms, analyzing the data and communicating it out represent the diverse populations touched by it -- can help us prevent biased AI from impacting the great products and services we put out into the world. Here are two of the most important ways to get started:
1. Creating a culture of inclusive AI begins with increasing access for diverse groups of young people, career-changers, and professionals interested in the field. The good news is that there are many organizations in the fight to #PressforProgress, including Black Girls Code, Girls Inc., PyLadies, and more, and we are starting to see results. One recent, promising outcome is that the number of female students who took an AP computer science exam in 2017 increased by 135 percent from 2016. This represents excellent progress, but we are still far from gender parity: Female students made up only 27% of the total number of students who took the exam last year. In my role as a senior data scientist at Metis, a data science training provider, I try to do my part to close the gap by seeking out diverse students to mentor, challenge, and celebrate. We also provide a bootcamp tuition scholarship for women and members of other underrepresented demographic groups. Cultivating diversity in these ways is actually a winning strategy for companies. McKinsey research shows those in the top quartile for racial and ethnic diversity are 35% more likely to have financial returns above their national industry medians, and companies in the top quartile for gender diversity are 15% more likely to do the same. It’s not hard to connect the dots and see that creating a culture of inclusive AI is a win-win for individuals and the organizations they work for!
2. In addition to cultivating younger talent in the field, those of us working in AI need to include diverse senior talent in our leadership structures. I’m proud to work for a tech company where the majority of leadership roles are filled by women, but I know this is not the norm. Again, not only is inclusion of all kinds a worthy goal to strive for in terms of morality and justice, it’s also a sound business strategy. According to McKinsey, for every 10% increase in racial and ethnic diversity on the senior executive team, earnings before interest and taxes rise 0.8%. Conscious decisions to fight bias and include deserving applicants in leadership roles are some of the first choices that have to be made on the path toward a culture of inclusive AI that benefits everyone.
But more needs to be done. The more students from diverse backgrounds we can attract to the field, and the more we support them as they seek to develop their skills, the stronger the tide of talent will be to change our culture from the bottom up. Simultaneously, the more we include women and individuals from historically underrepresented groups in leadership roles, the greater success we will have creating a culture of inclusive AI from the top down. As we work on the next great advancements in artificial intelligence that will transform the ways we work, play, and live, it’s crucial that we not leave anyone behind.
Sophie Searcy is a Senior Data Scientist at Metis, a leading data science training provider.
About the Author
You May Also Like | <urn:uuid:c27170df-8337-40ec-b7c2-fd9d2de48d27> | CC-MAIN-2024-38 | https://www.informationweek.com/machine-learning-ai/how-biased-ai-is-holding-us-back-and-two-things-we-can-do-about-it | 2024-09-19T18:11:00Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652055.62/warc/CC-MAIN-20240919162032-20240919192032-00248.warc.gz | en | 0.956819 | 1,113 | 3.109375 | 3 |
Microlearning is an approach which focuses on utilizing multisensory (using several senses at once) and multimodality (multiple literacies within one medium) in a short amount of time. The benefits of microlearning is the shortness in length, the content is straight to the point, it keeps concentration of the users, the users can choose what to learn, demonstration of the material and more. It can easily be integrated in your workflow. Before training employees in a business, it is important to plan the activities. This is a four phase plan on how to implement microlearning in your business.
Who are the users and how are they defined
Why should the users learn and what makes them put in the effort to learn
What will the users learn, what is the content and result of the learning
How do the users learn, what is the learning process
Microlearning focuses on participating and learning the information by activating the short-term memory and measuring the behavioral change based on educational experience and practice. There are several types of memory processes that occur during learning, including sensory memory, short-term memory, and long-term memory. Your short-term memory is overloaded by constant stimuli from your environment and learning content. To get attention and ensure that the learning content is transferred to the long-term memory, the users must realize the importance of the stimuli and find a pattern in the content that is presented.
A learning analysis can be used to measure how effective the design of the learning modules is. The collection of data and the depth of the data minimizing process can be extensive. For a microlearning module, should data from all the users be combined and analyzed. This includes the length from the content delivery to demonstration, effective use of the new provided information in job performance, feedback from participants, and observations of areas where the users were unengaged or found it challenging to understand the content. | <urn:uuid:37ce2c56-7344-49c4-8fbe-58f63820f95b> | CC-MAIN-2024-38 | https://infotechtion.com/microlearning-what-why-and-how/ | 2024-09-07T15:18:41Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650883.10/warc/CC-MAIN-20240907131200-20240907161200-00448.warc.gz | en | 0.943561 | 384 | 3.5625 | 4 |
Juniper SRX series device supports HA mode for redundancy. When it comes to serious networking, failure is not an option. So to get the devices working you can configure pair of SRX devices in High Availability mode. Before getting to know about differences of HA modes you should first have little knowledge of JunOS HA concepts. After knowing the concepts, you are now ready to learn about deployment concepts. There are two types of HA modes; active-active and active-passive. There are some differences between SRX HA modes.
SRX HA Modes
In the figure there are two SRX 240 routers in a cluster named node 0 and node 1. In active/passive mode, the node 0 is actively sending data traffic whereas the node 1 waits passively waiting for node 0 to fail. Upon failure of node 0, node 1 will pass traffic. While node 0 is active, it actively synchronizes sessions to node 1. But not all information is synchronized. For example, if node 0 fails, while it was learning routes for OSPF then it may not be able to synchronize routes fully with router B. This is disadvantage of this mode. In the figure above, there are two reth interfaces, reth 0 and reth 1 in same redundancy group 1. Reth 0 is for internet and reth 1 is for internal network. Since the node 0 is the primary RE data traffic is passing through interface of node 0 only i.e. ge-0/0/0 and ge-0/0/3. This is active-passive.
In this mode, node 0 have full load of the traffic whereas node 1 is free. This mode is mostly used in medium sized networks where traffic load balancing is not needed. This HA mode might have to tolerate some level of downtime because there is some risk in implementing this mode. The risk is that the node 1 device might not function when node 0 fails since node 1 was not sending/receiving traffic before. The device was idle for a long time and now the device has to pass the full traffic. This mode is also used in network where administrators have few knowledge of the device so that troubleshooting is easier in the future.
In active/active mode both devices in HA simultaneously pass the traffic. This mode is similar to active/passive but configured twice. The routers in cluster are active for their own redundancy group. Synchronization happens between both devices. The advantage of this mode over active/passive is, passing traffic by backup router ensures that backup router is ready and correctly functioning. Active/Active is great design because backup router is verified and traffic load is also shared between devices. But the downside of this mode is that it may be difficult to troubleshoot since traffic is going through both devices. Administrators have to spend more time looking for problem in both devices. This mode is used in network where 100% uptime is required despite of the complexity of the troubleshooting.
In the above figure, there are two SRX 240 routers in cluster i.e. node 0 and node 1. In this mode, both routers are sending and receiving traffic simultaneously. For interface reth 0 and reth 1, the redundancy group is 1 and for RG 1, the primary device is node 0. Similarly, for interface reth 2 and reth 3, the redundancy group is 2 and for RG 2 the primary device is node 1. Now, we can say that there are two active/passive mode configured in each device. After knowing about HA modes now you can configure high availability. | <urn:uuid:0c634a3b-1b64-47a4-97b6-0ecef06d5ccd> | CC-MAIN-2024-38 | https://www.mustbegeek.com/juniper-srx-ha-modes/ | 2024-09-10T00:18:34Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651164.37/warc/CC-MAIN-20240909233606-20240910023606-00248.warc.gz | en | 0.949243 | 727 | 2.65625 | 3 |
There's something interesting about technology revolutions, and in this blog post I will talk about two of the most profound technology revolutions in human history. I'll also touch on an emerging catalyst of the computer technology revolution ñ low code.
One of the most important technology revolutions of the last several hundred years has been the oil technology revolution. This technology has literally changed the world. When oil was first discovered and used, the "killer app" for oil, and by far its biggest use for the first 60 years, was for the production of kerosene for lighting as we moved away from candles. Next, we used oil for electric power generation. We moved from kerosene lamps to electric light bulbs. Soon, oil became diesel for railroad engines. The great expansion and higher levels of mobility started. The revolution in mobility continued with horseless carriages and then airplanes. Plastics and a thousand other products weaved its way through society.
What made this revolution so powerful was standardization and distribution. Every major industry ñ manufacturing, transportation, utilities ñ either transformed or perished.
Another revolution in technology started several decades ago, and that is the revolution of computer technology. At first, computers were calculators. Data was built faster and with more accuracy. Then computers became information processors. Soon, information derived from that data was processed at higher speeds, and became the back office for the modern enterprise. Manufacturing saw the rise of computer-controlled machines which improved safety, accuracy and the economics of consumer products. It was at that point that ñ like automobiles became "personalized" trains ñ computers became personal. Then mobile. Then social. And soon to be intelligent.
What made this revolution so powerful was, like oil, standardization and distribution. This time, that distribution was called the Internet. Every major industry has transformed--or is in the process of doing so--or will perish.
So, there's an interesting thing about technology revolutions: they have several things in common. At first, there's discovery. Then there's early adoption. Next, we see a virtuous cycle of standardization driving broad adoption (and vice versa). And before you know it, the world ñ with its industries, and conveniences and people ñ looks very different. That is transformation. It's amazing what a carbon molecule, some silicon and some electrons can do!
Without a doubt, the Internet ñ the distribution of computer tech ñ has had an incredible effect on our world. But how about standardization? This is still a work in progress. On the one hand, there are some fairly standardized apps, such as Gmail, browsers, word processors and even, to some degree, more sophisticated apps like CRM and ERP. (Your clue that there is some standardization is that there is a standard abbreviation.) On the other hand, you have standardized infrastructure upon which you can build what you want. This goes by the name of "cloud" and is provided by Google, Amazon, Microsoft, IBM, and the list goes on. So you have completely canned apps on one hand (with some configuration options), and standardized infrastructure where you can build what you want on the other.
But what if you need something between a fully canned application and some standardized infrastructure upon which you can build anything? That's where "low-code" fits in and why it is an important part of the revolution. As it turns out, there's a lot you don't need to build over and over like much of the user interface, simple branching workflow, etc. However, you still need to build what you need and what you want that is unique to you.
So low-code is the transformation that every company and industry needs. Embracing low-code is essential to every company that will prevail in this revolution. You can build "low-code" into your Digital Transformation plan, or your Innovative Technology plan, but reallyÖ. It needs to be part of your Business as Usual plan.
Appian is a software company that orchestrates business processes. The Appian AI Process Platform includes everything you need to design, automate, and optimize even the most complex processes, from start to finish. The world's most innovative organizations trust Appian to improve their workflows, unify data, and optimize operations—resulting in better growth and superior customer experiences. | <urn:uuid:7e34812e-e6b1-40db-bcf2-14b52e8e83c1> | CC-MAIN-2024-38 | https://appian.com/blog/2019/what-technology-revolutions-have-in-common | 2024-09-11T05:53:12Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651344.44/warc/CC-MAIN-20240911052223-20240911082223-00148.warc.gz | en | 0.966377 | 889 | 2.96875 | 3 |
DeepMind Unveils New AI Chatbot
The chatbot uses a live Google search and user response to create a safer, more accurate language model
Last week, Alphabet-owned AI lab DeepMind launched its new chatbot offering, dubbed Sparrow.
Designed as a conversational and informative tool, Sparrow was trained using DeepMind’s language model Chinchilla and is integrated with a live Google tool so it can rapidly search to answer users’ questions. Reinforcement learning was also used to hone Sparrow’s capabilities, with user feedback integrated into development of the tool.
The new chatbot is envisioned as an answer to ongoing issues in creating conversational AIs that scan the internet for information without relaying potentially harmful content, while retaining a level of conversational autonomy. As the Sparrow team wrote in a blog post, creating autonomous dialogue is a complex task as it features “flexible and interactive communication.”
“However,” they added, “dialogue agents powered by large language models can express inaccurate or invented information, use discriminatory language, or encourage unsafe behavior.”
By using human responses to develop its tool, DeepMind hopes to have reduced the amount of useless or harmful information being relayed by the bot. To test this, the team presented human participants with multiple potential answers to a question and had them select the most relevant or helpful response, using this to train the AI system on the kinds of answers it should give.
Creating a chatbot that pulls in information from external sources also, the team says, increases its accuracy, with the team saying Sparrow correctly cited evidence 78% of the time for factual questions.
Fears over the potential dangers of intelligent language tools have been growing as these devices have been made smarter, with demand for explainable AI now driving the market. The development also comes in the wake of controversies around Google’s chatbot being claimed as sentient by a now-fired engineer. While posing a different kind of potential danger, the effect is still to push demand for safer AI conversational models.
About the Author
You May Also Like | <urn:uuid:14c837ca-2d8e-4eff-86e5-4a5d8fc41426> | CC-MAIN-2024-38 | https://www.iotworldtoday.com/connectivity/deepmind-unveils-new-ai-chatbot- | 2024-09-13T14:29:11Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651523.40/warc/CC-MAIN-20240913133933-20240913163933-00848.warc.gz | en | 0.943149 | 432 | 2.6875 | 3 |
The “AI co-designers” would help the Pentagon rapidly blueprint secure weapons, vehicles and other network-connected platforms, and suggest designs humans haven’t yet conceived.
The Pentagon is exploring how artificial intelligence can help build more digitally secure vehicles, weapons systems and other network-connected platforms in a fraction of the time it takes today.
For years, cyber experts have urged agencies to make security a priority when building new systems, but that’s easier said than done, at least when it comes to military tech, according to the Defense Advanced Research Projects Agency.
Virtually every piece of military hardware includes a digital component and understanding how adversaries might attack these so-called “cyber physical systems” before they’re constructed requires a lot of manpower and computer modeling. Because the Defense Department works under tight deadlines, officials often limit the number of designs they consider, potentially passing up more effective but out-of-the-box options, according to DARPA.
But using artificial intelligence, the Pentagon could significantly accelerate the construction of cyber physical systems while also unlocking more effective—and yet unimagined—designs, the agency said.
On Tuesday, the agency kicked off a research initiative that will focus on building AI-powered tools that help the Pentagon rapidly assess different blueprints for cyber physical systems. According to DARPA, the tech developed under the Symbiotic Design for Cyber Physical Systems program would “be a game changer, and may result in a new generation of unexpected, counterintuitive design solutions.”
As it stands, the process for building cyber physical systems is decentralized, iterative and resource-intensive, officials said. Different teams design different parts of the system, and errors frequently arise as those components are pieced together, forcing the department to go back to the drawing board.
But with “AI co-designers,” the process would change dramatically: Humans would feed both project requirements and preliminary blueprints into the tech, and the tools would propose different designs for individual components of the system. Officials would then work with the machine to narrow down possible designs, and the system would test different component combinations to find the most effective overall system.
While today the Pentagon must constantly address vulnerabilities as they arise, using AI, officials would start building cyber physical systems with a blueprint that’s already been thoroughly tested and optimized.
“We expect order of magnitude improvement in design productivity, but equally important, the appearance of surprises, in the discovery of unconventional but highly performant designs,” officials said.
DARPA plans to divide the program into three tracks, with teams working together to design the AI co-designer itself, develop a way for humans to interact with the system and build a training regimen to teach the AI to learn from the successes and failures of previous system design.
The program is expected to run for about four years, and interested vendors must submit their final proposals by Oct. 14. | <urn:uuid:25784329-d8a6-4e1f-bcaf-1d7fa3328f28> | CC-MAIN-2024-38 | https://www.nextgov.com/artificial-intelligence/2019/08/pentagons-research-arm-wants-ai-help-design-more-secure-tech/159210/ | 2024-09-14T20:23:19Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651580.74/warc/CC-MAIN-20240914193334-20240914223334-00748.warc.gz | en | 0.951407 | 609 | 3 | 3 |
If you’ve researched and purchased ink for your printer, perhaps you been faced with deciding which type of ink you need. What are the differences between the inks available to you?
At one time, these were the only kind of ink available. Even today, though, dye-based inks are the most common type of printer ink used.
Dye-based inks offer a few important advantages, especially in an office setting where speed is just as important as quality. These inks result bright, rich colors on the paper and they dry almost immediately. Dye-based inks have a small molecular structure, which allows them to be absorbed by the printing surface quicker and reflect very little light, giving them a very vibrant look.
There are drawbacks, though. These tiny molecules are also water soluble, so they can run or smear when they come in contact with water, regardless of how long they’ve been left to dry. Dye-based inks are also not considered “archival”. The small molecular structure means that they are highly susceptible to oxidation and fading, so the superior colors they produce usually have a short lifespan. Lastly, their quick absorption rates can lead to colors overlapping or bleeding into one another, therby changing the intended color in a printed graphic.
Pigment-based inks are more expensive than dye-based inks. They are also much more archival than dy-based inks. Pigment-based inks have the ability to retain their original vibrancy for years – as many as 100, depending on the type of paper that’s used and how the resulting print is stored. (A print that is kept in a drawer is going to age much better than one that is continually exposed to sunlight.)
The durability of pigment-based inks comes from the fact that each color is made up of a neutral base and tiny colored particles. Because these particles are not organic and don’t break down when mixed with liquid – they are much more resistant to being broken down by environmental forces such as moisture and sunlight.
On the other hand, the mixture of a neutral base and pigmented color can produce a slightly diluted pattern, resulting in a print that is often less vibrant than one might find in a dye-based version. Drying times for pigment-based ink are also longer because their color is not in liquid form and can’t be absorbed by traditional paper.
Solid inks are relatively new to the world of printing. They are vegetable oil-based, wax-like blocks that are melted and applied to paper. Similar to pigment inks, solid inks are not absorbed into the printing surface and remain on the surface, resulting in little fading and deterioration over time.
However, since the printed colors aren’t broken up by a neutral base as they are with pigment-based inks, the final results are often more vivid. Solid inks are also environmentally advantageous. Unlike other kinds of ink, they do not come in plastic cartridges that eventually need to be disposed of.
The biggest drawback to solid inks is their lack of availability. Few manufacturers currently market them, and when they do they are relatively expensive. Solid inks, therefor, are usually used for specialized projects.
Other Types of Ink
There are other kind of inks that have been developed for specific uses.
Solvent inks, which contain color pigments and organic chemical compounds and become waterproof after heat is applied to the printed surface, are used to produce decals, billboards and artwork that might be exposed to the elements.
UV-curable inks, which result in color-rich, acrylic polymers when exposed to direct UV rays, are often used to print on substrate materials such as stainless steel, glass, and wood.
Dye-sublimation inks, which is a dye that transfers to fabric when heated, are commonly used to print on clothing, flags and other cloth materials. | <urn:uuid:d2cfa486-c682-4a62-b2d8-9cbbbb31d8b7> | CC-MAIN-2024-38 | https://www.capitalmds.com/lets-think-about-ink/ | 2024-09-17T08:19:26Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651750.27/warc/CC-MAIN-20240917072424-20240917102424-00548.warc.gz | en | 0.976145 | 816 | 2.796875 | 3 |
Three teams – in Boston, in China, and the Netherlands – have simultaneously announced that they’ve figured out ways to store entangled photons without breaking the entanglement, a critical step in building quantum repeaters, and, thus, scalable quantum networks.
The Boston team used silicon atoms embedded in diamond chips. A team in the Netherlands also used diamond crystals, but with nitrogen atoms instead of silicon. And the Chinese team used clouds of rubidium atoms. The American and Chinese teams both published their papers in this month’s Nature magazine, while the Netherlands research is available as a pre-print.
This is a big deal for two reasons. First, because it brings us closer to actually having secure quantum networks. And, second, because China is finally getting some competition in the quantum networking space, where it’s long held a substantial lead. | <urn:uuid:570bf01a-8e72-4972-9ef5-98bbb1afe244> | CC-MAIN-2024-38 | https://www.mariakorolov.com/2024/proof-of-concept-quantum-repeaters-bring-quantum-networks-a-big-step-closer/ | 2024-09-17T08:49:58Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651750.27/warc/CC-MAIN-20240917072424-20240917102424-00548.warc.gz | en | 0.918216 | 175 | 2.640625 | 3 |
Have you ever seen one of those old videos that shows a busy intersection with cars bumping into one another because there were no lights, signs, or protective measures in place?
By now we know that traffic regulations mitigate risk and contribute to uniformity and safety. And there are intrinsic rewards for conformance, such as not getting hit by another car—and avoiding fines.
Take this concept to cybersecurity, where in today’s cyber-regulated world, fines for violations can be hundreds of thousands or even millions of dollars.
Why are Cybersecurity Regulations Important for Society?
Adhering to cybersecurity regulations is crucial for society’s well-being for many reasons, including these top 5:
- Protection of Personal Data: Cybersecurity regulations help safeguard individuals’ personal and sensitive information, such as financial data, healthcare records, and personal identities.
- National Security: Cybersecurity regulations help protect critical infrastructure, government systems, and sensitive national security information, ensuring the stability and security of a country.
- Economic Stability: Cyberattacks and data breaches can disrupt businesses and economic activities.
- Public Trust: Trust is essential in the digital age. Cybersecurity regulations contribute to building and maintaining trust between individuals, businesses, and government entities.
- Reducing Cybercrime: Adherence to regulations can help reduce the occurrence of cybercrimes, protecting individuals and organizations from financial and emotional harm.
Keep Your Business Healthy: Neglecting cybersecurity regulations can lead to severe consequences, including financial losses, legal trouble, reputational damage, competitive disadvantages, and threats to your business’ long-term sustainability.
360 Advanced’s 360 Cyber Program 360 Cyber Program can help you improve your security posture and give your business the future it deserves. | <urn:uuid:84fe2aac-5db8-497a-9330-a1f15dbed8cc> | CC-MAIN-2024-38 | https://360advanced.com/cybersecurity-regulations-a-huge-burden-or-a-necessary-public-good/ | 2024-09-18T14:31:13Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651899.75/warc/CC-MAIN-20240918133146-20240918163146-00448.warc.gz | en | 0.934845 | 357 | 3.140625 | 3 |
Today’s highly automated industries require fast and reliable data transfer.
This evolution started the era of industrial Ethernet as a universal communication standard within Operational Technology (OT) environments.
Ethernet meets the availability and real-time communication requirements of Industrial Control Systems (ICS) and enables communication with external networks and systems.
However, increased connectivity brings numerous threats and vulnerabilities previously unknown to these systems.
This white paper provides an overview of ICS, including Supervisory Control And Data Acquisition (SCADA) systems, outlines common threat scenarios, and suggests strategies to meet event log management and passive network monitoring requirements.
Its intended audience is IT specialists unfamiliar with ICS/SCADA environments and ICS/SCADA specialists and managers looking to secure their systems.
Definition of SCADA
SCADA systems are a big part of modern Industrial Control Systems.
They provide real-time monitoring and supervisory control of industrial processes and equipment in industries like oil & gas, pharmaceutical, petrochemical, food & beverage, manufacturing, power, recycling, transportation, water & wastewater, mining, etc.
The primary function of SCADA is to acquire data from remote devices and provide visibility on their status in a single control center.
Operators rely on this data to monitor and control processes and respond to various situations effectively.
In addition, SCADA systems allow long-term archiving of data for analyzing and improving efficiency, informing decision-making, and preventing downtime.
SCADA software can combine data from numerous sources, process it, and send it to other systems in various formats.
Advanced SCADA systems can generate reports and automatically respond to certain conditions, for example, by generating alarms and warnings in hazardous situations or potential loss of product quality.
The main functions of SCADA systems are:
Controlling industrial processes locally or remotely
Monitoring, gathering, and real-time processing of data
High-performance data archiving
Analyzing process values (trends) and messages (alarm control)
Interacting with a wide range of devices using extended communication infrastructure
Communicating with external applications (ERP, MES, DBMS, spreadsheets, etc.)
SCADA is crucial for industrial companies, allowing them to control assets locally or remotely, gain operational insights, control processes, and make data-driven business decisions.
SCADA systems save a significant amount of time and money, increase the efficiency of operations, reduce downtime, and ensure product quality.
Structure of SCADA systems
An Industrial Control System comprises SCADA software interacting with numerous complex hardware devices over a network.
The overall structure of this type of ICS includes the following distinct levels:
Let’s discuss each level in more detail to understand how data is transferred and transformed between levels.
Field devices is a generic term used for sensors and actuators in industrial automation technology.
Generally speaking, a field device is a type of equipment used for measuring and controlling the industrial process and other similar equipment.
Sensors transform the physical parameters of a process into standardized signals (analog, discrete, digital, etc.) and relay data to the SCADA host software through a local PLC or RTU, where the data can be normalized or scaled.
Most control field devices, such as valves, pumps, etc., have been fitted with actuators, enabling a PLC or RTU to control the device.
Actuators allow the control system to optimize production or react quickly to abnormal events, such as shutting down the system in case of a hazard.
PLC and RTU
Early Programmable Logic Controllers (PLC) and Remote Telemetry Units (RTU) had distinct differences in design, but nowadays, their functionality overlaps.
PLCs are industrial controllers used to operate different electro-mechanical processes.
They use communication protocols to interact with SCADA/HMI systems or other controllers and cyclically execute internal logic to control process equipment (valves, pumps, etc.) according to digital/analog inputs.
RTUs are microprocessor-based devices that interact with physical objects and a SCADA system by transmitting telemetry data and altering connected objects' states.
They are an interface between the field sensors, actuators, and a SCADA central control unit.
RTUs are far more durable, resistant to harsh environments, and offer more comprehensive communication functionality, making them more effective for geographically distributed telemetry applications.
PLCs, on the other hand, are better suited for local control.
Some PLC and industrial automation hardware manufacturers include Siemens, Rockwell Automation/Allen Bradley, Schneider Electric, ABB, Honeywell, Emerson, Phoenix Contact, Mitsubishi Electric, Beckhoff, Omron, and B&R.
We live in a world of interconnectivity where different devices are continuously interacting.
The backbone of interconnectivity in the industrial world is complex industrial communication networks designed for real-time control and data integrity, allowing the transmission of large volumes of data with limited bandwidth in large plants and potentially harsh environments.
These industrial control networks are necessary to relay data between the different levels of the ICS hierarchy, such as:
This is the lowest level, including field devices such as sensors and actuators.
Devices operating at this level typically employ discrete signals, 4-20mA current loops, or serial point-to-point communication options (RS-232, RS-422, RS-485).
The most sophisticated communication technology used at this level is Fieldbus (e.g., PROFINET, PROFIBUS, HART, ControlNet, DeviceNet, CANBus, and Foundation Fieldbus), allowing distributed control among smart field devices and controllers.
This level typically includes PLCs, Distributed Control Systems (DCS), SCADA/HMI systems, and related network infrastructure.
Data is gathered and distributed to the various automation systems or PCs for supervisory control and monitoring at this level.
This is the highest level of an industrial automation system that handles higher-level management functions.
Here, process data is saved, processed, and analyzed.
Incorporating Ethernet technology into industrial networking blurs the difference between industrial and commercial networks.
However, the two have fundamentally different core requirements:
Industrial networks have a much more complex architecture with a hierarchy of three to four levels with different protocols and physical media.
In contrast, an organization’s commercial network may consist of Local Area Networks (LAN) connected by a backbone network or a Wide Area Network (WAN).
Industrial networks support critical industrial systems.
The failure of these systems may have severe effects, including damage to equipment, production loss, environmental damage, loss of reputation, and even loss of life.
Industrial equipment and control loops may need to operate in a high-speed mode that requires data to be transmitted, processed, and responded to as close to real-time as possible.
Systems in commercial networks do not have such strict response time requirements.
The data in the lowest levels of an industrial network must be transmitted in a predictable manner, which means bounded latency of a signal to predict when a reply to transmission will be received.
Industrial networks provide periodic data sampling and require the transmission of asynchronous events, such as alarms and state changes.
Industrial networks require determining transmission time and event order, e.g., for asynchronous events, using timestamps and synchronized clocks.
Since factory operations have become dependent on machine and production line data provided by automation systems, networking has become one of the core requirements of industrial systems.
ICS communication protocols
Each level of a typical industrial network uses specialized communication protocols that provide a set of rules and syntax to standardize information exchange between transmitters and receivers.
Some of these protocols may be proprietary or licensed.
Industrial protocols interconnect systems, interfaces, and instruments of an industrial control system in real-time.
Many were initially developed for serial communications over RS-232/422/485 physical connections (Modbus RTU/ASCII, PROFIBUS, CAN, etc.)
Various industry players designed these protocols, which eventually became standards.
Some of them are still popular and widely used due to the long life cycle of industrial systems.
Once industrial Ethernet gained popularity and became a de facto standard in industrial networking, many industrial communication protocols were adapted to operate over Ethernet-based solutions.
Industrial Ethernet is a cost-effective solution that supports higher speed, increased connection distance, and more nodes.
As a result, they are now widely deployed over various common industrial network infrastructures.
Various vendors drive many different industrial Ethernet protocols.
These protocols include PROFINET, Modbus TCP, DNP3, IEC 60870-5-104, IEC 61850, BACnet/IP, EtherNet/IP, etc.
SCADA is a multi-task software package based on a real-time database (RTDB) located on one or more servers.
Most SCADA systems support client-server architecture where each host can act as a server, a client, or both.
Server processes are responsible for data acquisition and handling, such as plant equipment polling, alarm checking, calculations, logging, and archiving.
It is also possible to have a dedicated server for each task.
The following is a list of possible server process types:
A dedicated communications server connecting diverse data sources to consolidate all plant and industrial data.
It acts as a communication protocol server providing data from specific vendors' PLCs and other factory devices.
It is responsible for servicing clients' read, write, and subscription requests and keeps up-to-date information by regularly retrieving data from each connected I/O device.
This process is responsible for assessing the conditions that define an alarm.
Controls the accumulation and logging of trend information to provide an up-to-date and historical plant overview.
Trend data helps to understand plant and equipment performance better and is used for visual analysis, production records, or recording of equipment status for maintenance.
Process dedicated to creating custom reports based on real-time or historical data.
It can design, schedule, or trigger complex reports containing any number of parameters from various sources, such as history or alarm databases.
A high-performance long-term archiving server storing process values and messages in a central database.
Clients provide the interface for evaluating and interacting with the system.
The most significant SCADA client is an HMI, i.e., operator interface.
The HMI visualizes process data in mnemonic schemes, graphs, charts, or user-friendly digital dashboards.
Operators leverage the HMI to view and manage alarms and perform sophisticated control.
Many vendors offer SCADA/HMI solutions, but the most significant players in this market are Siemens, Schneider Electric, AVEVA, Emerson, General Electric, ABB, YOKOGAWA, and Rockwell Automation.
Humanity employs a set of utilities that are critical for our vital activity.
These industries, such as water and wastewater, oil and gas, power generation, transportation, and communication, are classified as Critical Infrastructure.
A significant part of the world’s Critical Infrastructure relies heavily on industrial networks and ICS.
Disruption to any of the systems associated with these infrastructures could impact our society and safety.
Due to an attack’s potential impact, industrial systems are a very attractive target for hackers.
As a result, security for ICS has become a critical and widely discussed topic in recent years.
Operational Technology (OT) security challenges
Traditionally, ICS were isolated and did not necessarily need to connect to public networks.
However, today’s business needs for remote control and supervision require industrial networks connected to the internet and other third-party networks.
In addition, since adopting Ethernet as the de facto communication standard in industrial automation, industrial networks have become more sensitive to threats, bringing new OT security challenges.
The result is that these systems are now affected by many of the same security vulnerabilities affecting traditional IT systems.
Industrial networks mainly focus on availability, real-time data transfer with low latency, and deterministic response times but lack security mechanisms.
The closer you get to sensors and actuators, the less security-aware industrial networks are.
Historically, ICS used proprietary communication protocols that did not implement security.
However, even after adopting Fieldbus protocols for Ethernet-based communication, security is still lacking.
The criticality of processes controlled by ICS is a crucial difference from IT systems.
Unexpected system behavior results in a disrupted process that can cause production losses and damaged equipment.
For example, an attacker can compromise the process by changing setpoints, causing tanks to overfill, exceeding threshold temperatures, or damaging actuators by incorrect manipulation.
In addition, an infiltrated industrial network can prevent personnel from accessing the process and controlling equipment, leading to severe repercussions.
Table 1. OT vs. IT security
Often difficult or impossible to use
Passive scanning during planned outages is recommended to avoid disrupting operations
Complex, not possible due to legacy systems, or requires supplier approval
Incidental failure is manageable
Failure is not acceptable
Some degree of network and system interruption is acceptable
Network and system interruptions are not acceptable
Requires identifying risks
Occasional delays and network instability are expected and communication is not time sensitive
Occasional delays and network instability are not acceptable and teal-time communication is required
Little separation between networks at the same location
The information system network is isolated from the plant network
Security and awareness
The objective of industrial security is to fulfill three criteria:
Safety of personnel and the environment
Availability of assets and data
The integrity of operational and configuration data
In contrast, the IT domain focuses on data confidentiality, integrity, and availability.
Availability in the OT context is intertwined with safety.
When industrial systems malfunction or are not available, it can jeopardize the environment and safety of personnel.
Loss of availability for OT environments has more severe consequences than the loss of confidentiality.
Any failure of the ISC directly affects the devices underneath, leading to extensive material loss, potential human loss, and even environmental disaster in some uncommon cases.
Confidentiality in the OT context is less critical because data is often raw and must be contextually analyzed before it has any value.
The human factor is the most significant threat to ICS security.
Incorrect configurations, programming errors, and failing to monitor alerts are only a few possible threats caused by negligent or poorly trained personnel, disgruntled employees, contractors, or vendors.
They may disrupt the production process by sending incorrect commands or using parameter values that might cause process equipment to malfunction.
An employee with comprehensive knowledge of an industrial process may also become a threat due to financial gain, dissatisfaction, or unintentional human error.
Due to insufficient or nonexistent authentication or role-based access to restrict user activity, an employee may gain unlimited access to any device on the network, including SCADA applications and other critical components.
Many unauthorized accesses to ICS come through computers used to access the system for diagnostic or maintenance purposes rather than external devices.
These are primarily hacker attacks with the criminal intent to jeopardize the control system by causing operational disruption, damage, or espionage.
Importance of SCADA/OT log collection and passive network monitoring
As discussed in the previous section, protecting information from unauthorized access is standard procedure in IT systems.
However, the same level of protection is often lacking in OT, despite being increasingly more connected with IT systems.
The international standard ISA/IEC-62443 defines global industrial security recommendations for protecting ICS information, devices, and systems.
It focuses on personnel safety, the environment, and production quality and efficiency.
ISA/IEC 62443-3.3 "System security requirements and security levels" of the standard describes general ICS security requirements and contains two critical topics for the implementation of cybersecurity in industrial systems, namely "Auditable Events" and "Continuous monitoring."
SR2.8 - Auditable Events.
The control system shall provide the capability to generate audit records
relevant to security for the following categories: access control, request
errors, operating system events, control system events, backup and restore
events, configuration changes, potential reconnaissance activity audit log
events. Individual audit records shall include the timestamp, source
(originating device, software process or human user account), category, type,
event ID and event result.
Rationale and supplemental guidance.
The purpose of this requirement is to record the occurrence of important events
which need to be audited as significant and relevant to the security of
the control system.
Centrally managed, system-wide audit trail.
The control system shall provide the capability to centrally manage audit events
and to compile audit records from multiple components throughout the control
system into a system-wide (logical or physical), time-correlated audit trail.
The control system shall provide the capability to export this audit records in
industry standard formats for analysis by standard commercial log analysis tools,
for example, security information and event management (SIEM).
— NIST Cybersecurity Framework Core: Informative Reference Standards ISA 62443-3-3:2013
SR6.2 - Continuous monitoring
The control system shall provide the capability to continuously monitor all
security mechanism performance used commonly accepted security industry
practices and recommendations to detect, characterize and report security
breaches in a timely manner.
Rationale and supplemental guidance.
Control system monitoring capability can be achieved through a variety of tools
and techniques (for example, IDS, IPS, malicious code protection mechanisms and
network monitoring mechanisms). As attacks become more sophisticated, these
monitoring tools and techniques will need to become sophisticated as well,
including for example behavior-based IDS/IPS.
Monitoring devices should be strategically deployed within the control system
(for example, at selected perimeter locations and near server farms supporting
critical applications) to collect essential information. Monitoring mechanisms
may also be deployed at ad hoc locations within the control system to track
Monitoring should include appropriate reporting mechanisms to allow for a timely
response to events. To keep the reporting focused and the amount of reported
information to a level that can be processed by the recipients, mechanisms such
as SIEM are commonly applied to correlate individual events into aggregate
reports which establish a large context in which the raw events occurred.
Additionally, these mechanisms can be used to track the effect of security
changes to the control system (see SR 2.8 - Audible events). Having forensic
tools pre-installed can facilitate incident analysis.
— NIST Cybersecurity Framework Core: Informative Reference Standards ISA 62443-3-3:2013
Implementing a process for logging security-related events and monitoring network assets is also an essential requirement of security standards and catalogs such as NERC CIP-007 and the BDEW white paper.
Additional tools are often required to comply with the above requirements and provide an enhanced level of ICS security.
The following sections discuss this issue in more detail and propose a possible solution.
Most control systems based on SCADA or complete DCS and their components mostly comply with the ISA/IEC 62443-3.3 SR2.8 - Auditable Events requirement because they generate various events logged in plain text files, a dedicated database, syslog, or Windows Event Log.
We can categorize generated events into system events and process-related events.
System events refer to all important events generated by a system and its components.
These provide significant insight into internal system processes and can be used to investigate different types of issues.
Examples of system events include:
System services activities (Start/Stop, Activate/Deactivate)
Import/export and migration events
Monitoring system events is crucial, especially for control systems behind Critical Infrastructure.
These logs allow you to detect potential malicious cyber activity or unauthorized access to your ICS.
Process events represent ICS process status and activity.
For example, reaching the warning or emergency level of a controlled physical parameter, losing connection with a remote station or terminal, or a diagnosis event from the I/O module (input/output signal out of range).
Possible process-related events include:
Equipment failure and diagnosis events
Scheduled or triggered archiving (tag logging)
Process events are primarily stored in a dedicated database or a Historian database.
They are rarely found in plain-text files or proprietary formats.
Analyzing process event data may help predict, prevent, or investigate potential production incidents.
Why is continuous monitoring of network assets so important for ICS?
As discussed in previous chapters, ICS networks are complex, use legacy protocols designed for real-time exchange, and lack security mechanisms.
We also mentioned security threats inherent to ICS.
To better understand the benefits of network monitoring, we will consider a few scenarios.
Man in the middle (MitM)
An attacker gains access to the network between the control entity (e.g., SCADA, HMI) and the PLC or RTU.
Using simple network manipulation techniques (e.g., ARP spoofing), the attacker relays messages between the components as if they were talking to each other when the attacker controls the entire conversation.
A MitM attack has several repercussions:
Listening to the network traffic allows the attacker to retrieve information about processes' functions and the network’s structure.
An attacker can distort the information sent by the control entity, leading to potential damages.
This type of attack requires knowledge of the current process, devices, and industrial protocols.
An attacker can modify the information sent to the control entity.
This approach can hide malicious actions on the PLC or RTU by hindering the control entity from generating alarms or warnings.
A trespasser may also disrupt production by falsifying information from a remote monitoring point without directly accessing the SCADA system.
Denial of Service (DoS)
Network traffic is disrupted by flooding a targeted host or the entire network.
As a result, the targeted host cannot respond or crashes, preventing legitimate users from accessing the system and thus impacting availability.
To continuously monitor assets, you require various tools, from network packet sniffing and capturing to analyzing captured data by Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS).
IDS and IPS compare the gathered data against attack signature rules.
If they detect anomalous network activity, they can generate an event and forward it to a Security Information and Event Management (SIEM) system for further analysis.
Network monitoring is especially beneficial when monitored systems or devices such as RTUs, PLCs, and IEDs do not generate native logs.
Security Information and Event Management
Security Information and Event Management (SIEM) is a supervisory system that receives and aggregates data and correlates events from various sources.
In an industrial setting, a SIEM can aggregate and correlate system events, process events, and other events to detect possible incidents.
For example, correlation rules may deem a recurring event in a short period as a potential attack.
Likewise, an operator’s activity reported outside of their work hours or an engineer changing configuration outside of scheduled downtime or service period can be interpreted as a potentially harmful event.
SIEM systems also provide a unified view of the current security status of an organization, allowing filtering of data and generating reports.
This information is valuable for system administrators and security analysts.
The addition of a SIEM system extends security mechanisms and allows active process monitoring, helps to reduce the impact of malicious attacks, and provides the necessary information to prevent future incidents.
Log collection from ICS environments with NXLog
Integrating SIEM solutions with OT-specific tools and applications enables industrial organizations to extend visibility, security, and control across IT and OT operations.
You can achieve seamless interoperability by forwarding OT alerts and events to the relevant SIEM system.
NXLog Enterprise Edition is the ideal solution for collecting and processing events from diverse sources.
NXLog can be installed on various platforms and receive logs via UDP, TCP with TLS/SSL encryption, or HTTP(S).
It can also read events from files and databases and supports platform-specific sources such as Windows Event Log, Linux syslog and kernel logs, and the macOS Unified Logging System (ULS).
NXLog can perform advanced processing of log messages, such as rewriting, correlating, alerting, pattern matching, scheduling, and log file rotation.
After processing, NXLog can write logs to a central repository or forward events to a third-party platform.
NXLog Enterprise Edition supports passive network monitoring with a dedicated input module for capturing network packets (im_pcap).
This module supports various communication protocols, including industrial communication protocols such as BACnet, DNP3, Modbus TCP, IEC 60870-5-104, IEC 61850, PROFINET, and S7comm.
In addition, network packets can be parsed, processed, and converted to different data formats such as JSON, XML, CSV, syslog, etc.
Processing text-based log files
Many ICS store the majority of their operational and diagnostic logging in text files.
NXLog can collect these events and parse them into structured data for further processing and analysis.
The following example shows an authorization event generated by the Siemens SIMATIC WinCC runtime, a SCADA and HMI system used with Siemens controllers.
Example 1. Processing SIMATIC WinCC Operator logs
This input sample is from WinCC_Op_xx.log located in the SIMATIC WinCC general diagnostic folder C:\Program Files (x86)\SIEMENS\WinCC\diagnose.
The log file is UCS-2LE encoded.
NXLog supports passive network traffic monitoring of numerous protocols, including industrial communication protocols.
The following example captures and parses Modbus TCP packets, one of the most popular protocols used in ICS architectures.
Example 2. Capturing Modbus TCP packets
NXLog can collect network packets with the dedicated im_pcap input module.
Captured packets can be converted into various formats and routed to multiple destinations.
For example, the following samples show Modbus TCP query and response packets in JSON format.
The typical SCADA system handles tremendous volumes of data for various purposes.
This data may be stored in local or remote databases for additional processing.
Aggregating events from different database tables gives you insight into internal components and processes (e.g., tag data, process alarms, and process events.)
Analyzing this data helps you improve asset management, operations, safety of personnel, etc.
Example 3. Reading records from a database table
The following is a sample record from an AVEVA System Platform Alarm database table depicted in CSV format.
NXLog can be configured to collect events produced by various ICS and their components from Windows Event Log.
The following example shows the processing of events generated by Siemens SIMATIC WinCC services.
Example 4. Processing Windows events
This event sample is from the CCArchiveManagerService log source.
Industrial Control Systems are at the core of almost every industrial process.
Found in various facilities, they constantly face operations technology (OT) and information technology (IT) risks.
Moreover, exposing industrial infrastructure to the internet and third-party networks has given rise to a host of new threats that can be detrimental to the entire industrial process and have severe consequences.
Securing an ICS requires risk analysis and a deep understanding of the industrial process, making it a challenge for OT and IT network administrators.
Numerous recommendations and standards endorse the importance of event log management and continuous monitoring of industrial networks to protect against the growing number of threats.
Log data provides vital information, whether the goal is to increase security, improve operability, meet compliance goals, or gain business insights from IT/OT environments.
NXLog Enterprise Edition is an all-in-one log collection, processing, and forwarding solution that meets the logging requirements discussed in this paper.
It can collect logs from thousands of different sources and store or forward them in numerous data formats.
In addition, it supports passive network monitoring with a specialized focus on ICS protocols, making it one of the industry’s most flexible and powerful log collection solutions.
NXLog Platform is an on-premises solution for centralized log management with
versatile processing forming the backbone of security monitoring.
With our industry-leading expertise in log collection and agent management, we comprehensively
address your security log-related tasks, including collection, parsing, processing, enrichment, storage, management, and analytics. | <urn:uuid:b5f984be-6390-4fa0-88ab-99729badfa8c> | CC-MAIN-2024-38 | https://nxlog.co/whitepapers/industrial-control-systems-and-scada-security | 2024-09-19T22:03:20Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652067.20/warc/CC-MAIN-20240919194038-20240919224038-00348.warc.gz | en | 0.911317 | 5,985 | 2.546875 | 3 |
Over the past three decades, a handful of products like Google's search engine, Tesla’s electric vehicles, and Apple's iPhone have been the tech industry's game-changers, leaving previous products in the dust. I think we can safely add OpenAI’s ChatGPT to that list.
What puts ChatGPT on the same level as these other industry-defining innovations? There are massive announcements every year in the tech world. Engineers everywhere are constantly working to build the next big disruptive thing. What makes ChatGPT different?
ChatGPT is shaking up businesses everywhere
Let’s ask another question: What separates a game-changing tech from the status quo?
To answer, we’ll revisit a classic: The Innovator's Dilemma. In this book, author Clayton M. Christensen states that most new technologies are sustaining technologies that improve the performance of established products in ways mainstream customers traditionally value.
However, some technologies can be disruptive, offering a new value proposition. And while disruptive technologies may initially underperform established products in mainstream markets, they have other features that appeal to fringe customers, such as being cheaper, simpler, smaller, or more convenient.
To offer an example: the smartphone market. Apple originally disrupted this market by releasing the iPhone, a tool that introduced the touch screen, among other innovations — essentially launching the mobile-first era.
But, the smartphone of today has become a sustaining technology. Every year, cell phone manufacturers, including Samsung, Huawei, and Apple, release updated products to meet consumer demand. While there have been other innovations, such as folding screens, these haven’t transformed the market like the first iPhone did.
In a word: disruptive tech is practical. How a technology can be used is massively important to its success. It doesn’t matter how amazing your algorithm is if it isn’t useful or user-friendly.
To offer a second example, Google’s search engine revolutionized how we access and find information online. But this tool isn’t just helpful for someone trying to figure out whether or not Netflix streams their favorite TV show; it opened up a whole new world, playing a role in shaping both the online marketplace and the offline marketplaces. By prioritizing certain types of content and websites in the search results, the algorithm has influenced consumer behavior and the success — or failure — of businesses worldwide.
So, again: How does ChatGPT fit in? Its creator OpenAI took something previously mostly found in technical research papers, large language models (LLMs), and turned it into an accessible technology. Giving people everywhere a way to experience the power of LLMs via a simple, conversational interface revealed what’s possible to the masses. There’s no going back. Now, every product that claims to be conversational AI must offer a similarly magical experience or fall into obscurity.
Understanding the new AI stack
I doubt generative AI will stop at helping people write emails. Much like Google revolutionized the world with its search engine and Apple put a smartphone in everyone’s pocket — ChatGPT will transform how people do business.
That said — deploying GPT-class models in production is no simple task. It requires an advanced Machine Learning Ops platform, a team of human annotators to generate training data, and skilled engineers to optimize performance. Without prior experience using LLMs, it can take years to build the necessary infrastructure. However, companies with a history of using LLMs are in a good position to quickly adopt the capabilities of this tech in their products.
Suppose you’re someone who wants to incorporate conversational AI into your operations. The challenge for you is to figure out which conversational AI businesses are just hype and which are the real deal.
As more and more sales pitches from generative AI companies start filling your inbox, you need a surefire way to see through the marketing jargon and differentiate between the companies with the talent and experience to leverage this technology — and those that do not.
We’ll start with some basics: the conversational AI landscape can be divided into three layers: foundation, middle, and application.
1. The foundation layer: The base of the AI stack
ChatGPT is the latest in a long line of genuinely game-changing generative AI technologies. As good as it is, though, ChatGPT isn’t a silver bullet. It does a lot of things well — astoundingly well, even. It can serve information in tight sentences rather than long lists of blue links. It can explain concepts in ways that people can understand. And it can brainstorm business plans, term paper topics, business strategies, birthday gift suggestions, and vacation plans.
It has such a wide breadth of knowledge because it is based on a foundation AI model; specifically, an LLM called GPT-3.5. Foundation AI models make up the base of the AI stack, trained enough to offer a perspective on a wide range of topics. Products like GPT-3 for text, DALL-E-2 for images, or Whisper for voice are examples of how foundation models can be applied to deal with broad categories of outputs: text, images, videos, speech, and games.
But — there are a couple of significant challenges when using foundation models.
For one, foundation models, like GPT-3, are monoliths. Like every model, the only way to change the output is to change the input. Foundation models are frozen in time. The particular capabilities of a generative AI system depend on how it’s trained and the types of information it is given.
While you may have heard the term “prompt engineering” to describe the work people do to adjust and control model outputs of these models by inputting specific terms and structures, ultimately, their knowledge is tied to the original training data. A foundation model can’t look up dynamic data or any real-time information to tell you the current share price of Microsoft stock, for example. And they can’t create new ideas from scratch.
Perhaps more importantly, many of the big tech players have their own foundation models based on the massive amount of data they can access. Microsoft was smart to partner with OpenAI early, and they will capitalize on this investment fast. Though they aren’t leading the wave, Google’s PaLM is significantly bigger than OpenAI’s GPT-3, unlocking even more capabilities. These big cloud providers will fight to have some offerings in this space. And the smaller, newer companies don’t stand a chance.
2. The middle layer: Models powered by specialized data
While the foundation layer offers a wide breadth of understanding, it’s not enough for businesses requiring 99.9% accuracy. By definition, foundation models offer general information and are fundamentally unfinished, requiring substantial building and productizing to be turned into something useful for more nuanced work. And that’s where the middle layer — and later, the application layer — come into play.
Products that live in the middle layer build smaller models capable of taking on more precise jobs. Trained on highly detailed — and typically proprietary — data, these models can write a knowledge base article pulling on details from your IT ecosystem. Or they can re-create a writer’s style and word choice. Or they could even edit stock photos to fit your exact brand specifications.
Often developed for a particular application, industry, vertical, or use case, these more specific models outperform foundation models in their particular wheelhouses.
Here’s where — to me — things start to get interesting. Companies can differentiate themselves by taking a foundation AI model and fine-tuning it to the needs of a particular business or industry. This is particularly powerful in fields where data is highly sensitive and specific domain knowledge is required to make accurate predictions, like finance, healthcare, energy, and manufacturing.
To offer an analogy: If Facebook, Google, Microsoft, and other tech giants have their own massive and well-equipped kitchens, you won’t be able to compete by just having a recipe book. But, if you have access to a wide variety of unique and high-quality ingredients and use them to create specialized dishes that complement the menu of the big players while also incorporating human expertise and feedback — that's where the real culinary success lies. The recipe may be necessary, but the ingredients are key.
The same goes for generative AI. Ultimately it’s the data that matters. Models are children of the data they’re trained on. Companies can differentiate from the competition by incorporating the specialized data they can access. This approach results in more nuanced results and a more defensible product that’s not just a flash in the pan.
3. The application layer: A conversational user interface
The application layer is the last step that brings all these layers of models together. I’m referring to the interface where humans and machines collaborate, such as the workflow tools that make the AI models accessible in a way that enables business customers or consumer entertainment.
The application layer is crucial, especially in a post-ChatGPT world. Everyone is now expecting that magical conversational experience where anyone can write a prompt and get an answer.
The thing is that your product can’t just be an interface. Merely making API calls to other core foundation models isn’t enough to survive in such a competitive field. It may be easy to build these application layers, but they will struggle with retention and differentiation.
I've already run through at least ten different content generation free trials in the past few weeks alone, but I’m not intending to renew them. It’s clear from the steady stream of marketing emails that pressure for this type of company is already mounting. They’re now offering discounted, unlimited plans, and we’re barely seven weeks out from ChatGPT’s launch.
There are, inevitably, going to be winners in this approach, but there are going to be more losers. Think about website-building platforms. You could learn some HTML and CSS to build a website or just use Squarespace. And for every Squarespace, a hundred other web-builders didn't make it.
If a company only provides workflow tools on top of widely available technologies, it may struggle to compete with larger companies with their own versions of these tools. Is there a world where Google doesn’t release its version of ChatGPT on Google Docs? Or where Microsoft doesn’t leverage GPT-3 in its Office Suite? I don’t think so. The foundation layer is available for everyone, so it won’t be a differentiator.
Companies that can bring unique datasets, train solutions, and offer precise answers at the application and operating system layers are more likely to be successful and highly valued for their solutions. And then, the interface becomes invaluable. ChatGPT has proven the versatility of conversation, and now users have high expectations.
To be genuinely competitive, products can’t just be a thin veneer on top of existing technologies. The companies that can bring a unique dataset and find a way to productize are the ones that will really make it big time.
ChatGPT made the world pay attention to generative AI. Now, you have a rubric to see through the hype.
ChatGPT has raised the bar for conversational AI, but it’s ultimately a base capability universally available to every business in the world. If you want to write a compelling outreach email, ChatGPT and the many, many competing applications on the market are going to be extremely helpful, but if you want to, for example, run a cost-efficient support organization, you’re going to need something else with more nuanced capabilities.
This is to say that when you’re investing in a new tool, remember: What’s hard and what’s expensive are ultimately the differentiators. A product without a unique value proposition won’t survive an extremely competitive market. If a vendor is only offering an application layer on top of a foundation model — they aren’t going to make it.
That’s why you must be thoughtful about what use cases you’re trying to solve and what specialized data your prospective vendor can access. Because if you invest in the wrong direction, you will end up with a solution as obsolete as the Blackberry or Kodak.
In the near future, the next step in LLMs — GPT-4 — will be announced, and it is almost guaranteed to blow everyone’s minds again because ChatGPT made the world pay attention. This tool marked the beginning of what will become conversational AI's true potential in the enterprise. Billions of dollars are being scrambled to deploy it or similar technology into many products. Make sure your budget ends up in the right hands.
Moveworks is the leading enterprise conversational AI platform.
ChatGPT wasn’t made to help you improve the employee experience; Moveworks was.
We’re focused on building the world’s leading conversational AI platform and have been for the last six years. We’re constantly innovating, plugged into the latest advances in the field, and looking for ways to improve our platform.
Today, we offer what I — and our customers — truly believe to be the best conversational AI platform for employee experience:
- We understand exactly what employees need, no matter which language they use.
- We offer actionable recommendations for your support environment.
- You can implement our platform in days, not weeks or months.
No matter your industry, conversational AI from Moveworks can elevate your employee experience, improving every interaction throughout their journey. Don’t just take our word for it — leading companies like Hearst and Palo Alto Networks have experienced incredible results with our platform.
Let us show you all you can get from conversational AI in a quick demo with our team.
Contact Moveworks to learn how AI can supercharge your workforce's productivity.
Table of contents | <urn:uuid:3640d9cb-0657-4ed4-8f11-a36e9cc0d245> | CC-MAIN-2024-38 | https://www.moveworks.com/us/en/resources/blog/generative-ai-how-to-spot-the-real-from-the-hype | 2024-09-19T20:08:35Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652067.20/warc/CC-MAIN-20240919194038-20240919224038-00348.warc.gz | en | 0.932377 | 2,931 | 2.546875 | 3 |
Organizations need to understand what cookies are and how they work to be able to use them effectively to avoid being caught off guard with new data privacy regulations looming. This blog breaks down what a cookie is, how they help in advertising, and how you can conduct a cookie audit to get a sense of how cookies are being handled on your websites.
What is a cookie?
A cookie is a file that is saved onto users’ computers to enrich their user experience by allowing them to personalize their sessions, as well as tracking them to offer better functionality. Cookies help websites remember things about individual users, such as what products they added to their carts or how far along they’ve gotten in a game.
Another important aspect of cookies is their ability to track user activity to deliver personalized and targeted ads to users. You can thank cookies for personalized and targeted ads if you’ve found yourself browsing the Internet for cars and see ads relating to cars elsewhere on the web. Albeit, one of the most important uses of cookies is that they aid in the faster loading of previously visited websites.
How do cookies work?
On the other hand, third-party cookies are cookies that are served by the sites you visit on behalf of other websites. For instance, a blog might serve ads on behalf of an advertising company.
When a browser requests access to a page from a website’s server, it includes cookies that were saved onto the user’s device with the request. The server then reads this request along with the cookies in it to serve relevant content and may add new cookies to the page it delivers. The page is then read by the browser along with all the cookies sent to it by the server before finally displaying the page to the users. This continual cycle of exchanging cookies allow websites to track user activity to get a real-time understanding of usage patterns and other data that could aid in delivering personalized content and ads.
Cookies and advertising
However, third-party cookies that websites serve on behalf of advertising services is where the plot thickens a little. The question is often about whether the user consents to provide data to a third-party whose site and cookies they did not intend to request. It is also an ethical issue to consider whether websites can choose to share information with third-party ad providers for marketing without the consent of users. Many jurisdictions in the US and EU have ruled that websites must inform users of how their cookies will be used and require their consent to share this data with ad providers. Some jurisdictions also specify that users should be given the opportunity to opt-out of such cookie sharing with advertisers.
Advertisement providers often operate through networks of websites that consolidate cookies to build a profile of a user and deliver targeted advertisements based on it. Your browsing and internet activity across websites contribute to the profile, and it gets refined to the point where advertisers have an accurate idea of who you are, your interests, and what ads you would be interested in.
The increasing sophistication of cookies and how much data about you can be collected and used by these advertisement providers have called for more stringent data privacy regulations around the world.
Cookie laws were first brought into effect with Europe's amendment to the ePrivacy Directive in 2009 which made it mandatory to seek users' consent to access information stored on computers, phones, or other digital equipment under Article 5.3. This move would eventually lead the EU to address the need for specific personal data laws with the General Data Protection Regulation (GDPR).
The EU brought the General Data Protection Regulation or GDPR into effect on May 25, 2018, and brought cookies into the ambit of ‘personal data’, thereby allowing them to be regulated. This made it essential for any website serving residents of the European Economic Area to seek users’ consent before serving third-party cookies that weren’t fundamental to the website itself.
The institution of such laws has brought third-party cookie use down considerably. However, there is a large contingent of websites that continue to be non-compliant with the GDPR, often out of a lack of understanding of the laws.
New York’s Stop Hacking and Improve Electronic Data Security or SHIELD Act has defined what constitutes personal data and includes many of the parameters that cookies use.
California also brought in a comprehensive regulatory framework called the California Consumer Privacy Act or CCPA that gives residents an understanding of what personal data is being collected about them and the choice to disallow the sale of such data to third-parties.
GDPR and other data privacy laws such as those mentioned above require website owners to add a banner and buttons to their websites that would give users options to accept or deny consent to cookies as well as an option to give purpose-specific consent.
How to conduct a cookie audit?
It is in the best interest of website owners and hosts to ensure compliance with these laws and regulations to avoid heavy fines and penalties that such a default could cause. To ensure compliance with data protection laws, it’s important to conduct a website cookie audit.
You end up a lot of adding a lot of cookies that track users’ data and sell them to third parties as you add more features and elements to your website, and you might not realize it. While your intentions might not have been malicious, ensuring compliance with regulations is still your duty and, you can be held accountable for non-compliance. To ensure that you aren’t unknowingly serving third-party cookies that track personal data on your website, you need to know all the cookies that your website serves.
Conducting a cookie audit is a straightforward process that will help you:
- Analyze what data your website collects from users.
- Ensure compliance with data protection laws and helps resolve issues that might result in non-compliance.
- Remove any cookies that are not essential
- Comply with industry-specific standards and regulations
- Reduce the chance of data breaches by removing malicious cookies and encrypting cookies.
You can conduct a free cookie audit in three simple steps:
Step 1: Knowing What Cookies You’re Serving
Identifying what cookies your website is serving can be done by simply deleting your cookie history on your browser and revisiting your website. This is the simpler way to go about it; however, it might not be the best way to do it. Some cookies are delayed and aren’t downloaded until after a while, and others might be trigger-based, which are only downloaded when you perform certain actions on the website.
A comprehensive privacy audit tool like Privado can help you make sure you’re not missing any cookies and identify them all in an intuitive list form.
Step 2: Analyzing individual cookies
Going through each cookie will help you understand its purpose and source. This will allow you to identify which cookies are non-essential to your website and need to be removed. Make sure to keep an eye out for new or unfamiliar cookies.
Some things to keep in mind while investigating these cookies are whether the cookies collect personally identifiable data, if there’s any purpose the cookie serves, what tools it uses, and if it can be associated with a vendor.
Step 3: Ensuring Compliance
Once you’ve investigated each cookie, you should have an idea of what cookies could be problematic in terms of data protection regulation compliance.
Keep in mind that you still have to comply with users’ local regulations, even if your jurisdiction does not have laws concerning cookie use.
That’s it. You’ve successfully conducted a cookie audit!
Privado: Managing cookies made easier
Ensuring compliance with many jurisdictions can be a tedious task to do yourself. Using a comprehensive privacy solution like Privado can take care of that for you! Privado allows you to conduct comprehensive cookie audits, manage cookie consent from users, as well as automatically get rid of problematic scripts on your website.
Get Privado now to make compliance a breeze!
Vaibhav is the founder of privado.ai and a CIPM certified privacy professional. | <urn:uuid:ee952c09-6b3c-40e5-bd40-9095027fcffe> | CC-MAIN-2024-38 | https://www.privado.ai/post/how-to-conduct-cookie-audit | 2024-09-19T21:56:19Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652067.20/warc/CC-MAIN-20240919194038-20240919224038-00348.warc.gz | en | 0.953787 | 1,653 | 3.359375 | 3 |
It’s a sad truth that not all network devices are built with network device security in mind. Some ship with default credentials like admin / admin, with SNMP set to public, or with operating systems that haven’t been updated in years.
As with any other device, it’s important to practice good hygiene when managing network devices. Good hygiene means things like keeping firmware up to date, changing credentials away from the defaults, and refreshing end-of-life hardware and software.
If you’re already doing these things, great! You get a well-deserved pat on the back. By following these simple guidelines, you’re already in the front half of the network management pack. But what else can you be doing to continually improve the security posture of your network infrastructure devices?
Here we’ll go over what network device security is, how to secure network devices, and share five security best practices.
What is network device security?
Network device security is the use of policies and configurations that a network administrator sets to monitor and protect the network devices from any unwanted or unauthorized access, changes, or use. It is vital for any organization to have secure network infrastructure devices in order to limit disruptions or data loss. Network device security enables organizations to better control access to their network devices, and in turn better control access to their network.
What are the types of network security devices?
There are many types of network devices, but these are some of the most commonly used ones for securing a network.
For most networks, the firewall is one of the first lines of defense. Firewalls act to isolate your network and protect it from unwanted network traffic. Depending on your network, firewalls can be built into devices such as routers and switches or implemented as standalone protection.
Firewalls can operate in two ways:
- Whitelisting: The firewall blocks everything except specifically listed network traffic.
- Blacklisting: The firewall only blocks suspicious traffic from the network.
Deciding which of these policies to choose is part of determining how to manage a network, but more often than not, you’ll want to take a Whitelisting approach.
Network access control (NAC)
Network access control (NAC) is a network security device that checks the security settings of any devices trying to enter the network and either denying entry if settings do not meet predefined policy requirements or allowing entry to the network if settings match access requirements.
Intrusion Prevention and Intrusion Detection Systems (IPS / IDS)
Intrusion prevention and intrusion detection systems scan and alert you of any network attacks. They act in conjunction with the firewall and scan for anything that may have cleared the firewall and entered the network.
While intrusion detection systems notify you of any intrusions and require action on your part, intrusion prevention systems notify you and actively respond to the intrusion without your intervention.
Proxy servers provide network security by acting as a go-between for your network computer’s web browser and the server on the other end of the connection. Inappropriate and malicious websites are blocked by proxy servers and access control policies are enforced.
These are only some of your choices when it comes to types of network security devices, and no single one will do it all. Instead, it’s important to take a layered approach and utilize as many types of security as your network needs to ensure your network infrastructure devices remain protected and secure.
How do I secure a network device?
If you’re wondering how to secure network devices, there are actually several ways to enhance the security of network infrastructure.
It’s important to keep up-to-date inventories of all your network devices and to know exactly what security policies have been applied to each one. Taking inventory can be a time-consuming task when done manually, so opt for a network scanning tool that can do this for you like Auvik.
Identify devices at high-risk
By evaluating your devices and narrowing in on the ones with increased risk, you can proactively take additional measures to ensure your network remains secure. Be sure to also look at devices that contain sensitive information or are lacking in strict access permissions and implement greater security measures there as well.
Determine areas of device weakness
While you identify high-risk devices, also notice where these devices exhibit weaknesses that need attention. By finding these areas of device weakness, you can locate where patches are needed and deploy extra security to the device to protect it and your network.
Use configuration and management tools
Manually performing network configuration and security tasks is a time-consuming burden on your administrator, and these tasks can be done more efficiently and accurately with configuration and management tools. Repetitive tasks and standards maintenance are done automatically with configuration management tools, and any changes to network configurations are detected and flagged in real-time to ensure you know exactly what is happening when as well as who is making the changes. Auvik‘s network management system provides the tools you need with the security and privacy your network demands.
Routine reporting and audits
Regularly reviewing your devices is key to securing network devices. Utilize reports that analyze your device’s security measures and keep tabs on whether everything is working as it should or if you need to make any adjustments.
5 Security Best Practices for Network Devices
1. Limit the IP ranges that can manage network infrastructure
Do your users need direct access to switches or firewalls? How about the IP phone subnet? For nearly every person I talk to the answer is a clear ‘no’.
Most network devices allow you to select management IPs or apply access control lists (ACLs) to services such as SNMP and SSH. Use this feature to restrict access to a couple of management servers you have on site.
This is especially important for perimeter devices. If you’ve enabled SSH access to a firewall from the outside, it’s critical that access is locked down. Be careful not to lock yourself out though.
2. Use SNMPv3 throughout the network
SNMP has gone through a few iterations over the years. SNMPv2c, the most commonly used version, has been around for decades with little change. SNMPv3 is a great option for those looking to manage devices over SNMP while adding some network device security and encryption to that management.
Using SNMPv3 instead of v2c over public networks is obvious, but security-conscious service providers have increasingly been using SNMPv3 within private networks as well. That’s because v3 reduces the amount of management data traversing the network in clear text—in case someone is listening in who shouldn’t be.
3. Rotate network device credentials
It’s that time of year: Time to change your firewall password from Fall2019 to Winter2019, am I right?
While some may rightfully question your choice of passwords, good on you to rotate your credentials on a quarterly basis. We typically see teams rotating network device credentials at least annually. Credentials are an important method of securing network devices.
Already rotating regularly? You’re well ahead of the curve.
Credential rotation isn’t on your regular calendar yet? Start the habit now by setting a recurring ticket in your PSA.
4. Disable unused network ports
Helpful employees, malicious actors, shadow IT—these are all people who would love to plug something into an open Ethernet port on your switch. Trouble is, they can cause a broad range of issues, from broadcast storms to security breaches and unsanctioned hardware on your network.
If you have extra ports on routers, switches, and firewalls after completing the initial configuration, disable them. If they’re ever needed again, you can log back in and re-enable them.
5. Secure SSH on network devices
First of all, thank you for having SSH configured and not Telnet. (You do have Telnet disabled, right?)
There are a few things to consider when securing SSH:
- Disable SSHv1. Version 2 is newer and more secure.
- Enable an idle timeout so that any idle sessions are closed down.
- Ensure the network device software is up-to-date. Many network devices use OpenSSH, and over the past few years there have been many OpenSSH bugs identified and fixes put in place.
6. Bonus! Add a warning banner
Consider implementing a warning banner sanctioned by the legal team that users will see when they log in. While this won’t prevent access and won’t stop malicious actors, it may give an accidental hacker second thoughts.
It’s important to keep in mind that the steps to implement each of these recommendations will be different between network device vendors. You may also find that some settings discussed aren’t available on your network infrastructure devices. That’s OK—implement what you can and manage the risk around the others. What is network management without an individual approach to each network?
Achieving a secure network is a constantly moving target that relies heavily on network device security. If you’re not being proactive and continually re-evaluating and managing the risks, you’ll be behind before you know it. Auvik’s network monitoring and management software helps you prevent, detect, and resolve network issues quickly. Our cloud-based secure network management ensures you always know what’s on your network.
Get templates for network assessment reports, presentations, pricing & more—designed just for MSPs. | <urn:uuid:0d8ba2d3-5cce-4a5e-835e-066c13b80cd4> | CC-MAIN-2024-38 | https://www.auvik.com/franklyit/blog/network-device-security/ | 2024-09-21T02:28:05Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725701427996.97/warc/CC-MAIN-20240921015054-20240921045054-00248.warc.gz | en | 0.928552 | 1,989 | 2.734375 | 3 |
What Is Robotic Process Automation?
Robotic Process Automation is the process of applying automation to perform tedious business tasks of the workforce, such as data manipulation, response triggering, transaction processing, and other redundant tasks. According to a recent study by Snaplogic, 90% of the workforce are burdened with redundant tasks. This not only reduces their productivity but also consumes significant amounts of time with which they could perform higher-value tasks.
The Role Of RPA: Features That Enhance Business Process
Once your enterprise has decided to implement RPA, it is time for you to choose the right robotic process automation solution.
Traditional RPA software bots are known to handle only a specific task at a given time. When it comes to addressing high volumes, there is a necessity to clone these bots and run them simultaneously. RPA providers usually charge users for each concurrent process. This can become a costly affair for enterprises, especially during volume spikes. Thus, undue extra costs are a key factor to consider while choosing an RPA solution for your business.
RPA works as a virtual assistant and can handle complex processes starting from performing complicated calculations, data capturing to maintaining records.
In addition to prioritized work queues, user-friendly features, data analytics, and non-disruptive nature, the following are crucial features that enhance business processes:
- Non-disruptive nature: An enterprise can easily implement RPA into their workflows without having to disrupt or change the existing structure or risks.
- Data analytics: Gathering critical data from multiple sources, analyzing and storing the data, and creating reports have brought digital transformation to businesses with RPA. This enables accurate forecasts of sales data along with other Key Performance Indicators (KPIs).
- Prioritization of Internal Work Queues: Every RPA software consists of internal work queues. These work queues are used to extract data derived from various transactions for analysis. The extracted data is then stored on a cloud server and made available for access by the bots.
- User-friendliness: Employees can operate on the robots without any extra RPA knowledge. They only need to learn how the systems work.
- Scalability: With RPA, it is possible to upscale and downscale various robotic operations.
Types Of Robotic Process Automation Tools
RPA enhances robotic performance in different ways. The three major categories include Working Robots that are commonly used for Data Collection and Project Planning. Monitoring Robots detect faults and breakdowns, whereas Screen Scraping Robots provide data migration tasks for enterprises.
Robotic Process Automation tools come in varying sizes and shapes. Analyzing your business objectives is the most critical factor before deciding to choose a specific RPA tool for your business. A few of the major RPA tools are as follows:
- Attended Or Robotic Desktop Automation Tools
This type of automation always starts with the user via the user’s desktop. The user first launches the RPA code to perform required operations rather than waiting for the workforce to perform.
- Unattended Automation Tools
This type of automation completes business processes in the background and is used mainly to perform back-end tasks.
- Hybrid Automation Tools
This type of automation combines both attended and unattended automation tools to perform start to end operations.
How To Choose The Right RPA For Your Business
A clear set of objectives form the primary goal before opting a specific RPA tool for your business. The following are the key factors you need to consider before selecting an RPA tool for your business:
1. Easy-to-use Interface
Simple user experience is a major criterion for choosing the right RPA tool for your business processes. A simple user interface will ensure all employees work efficiently.
2. Proper Deployment
An RPA tool that can be quickly deployed with the existing technology stack is what is required.
Replacing tedious tasks performed by the human workforce is largely replaced by the bots. This process of automation saves costs. Employees can focus on their core tasks and spend time and effort on their skills rather than performing redundant and tedious tasks with the help of RPA tools. Purchasing an RPA software tool involves associated costs, such as cost of individual licenses, cost of the software, and other overheads.
Implementing an effective RPA tool enhances the business processes and leads to the growth of the enterprise. This growth is accompanied by hiring more resources. Thus an RPA tool can enhance the scalability of a business in the long run.
Data analytics, compliance, and financial transactions require a highly secure environment. A great RPA software tool ensures a secure solution for all business processes and updates as well.
The architecture of the RPA depends on where you plan on employing your RPA tool. The deployment and maintenance of an RPA tool depend on factors such as layered design, component reusability, robust delivery, popular language support system, easy accessibility, and so on.
Choosing an RPA suite that consists of solid inbuilt features is critical. Flexibility, scope, availability of wizards and GUIs, other extendable commands and supports are some of the features to consider.
8. Exception Handling Support
A robust RPA solution can detect errors during automation and automatically resolve without human assistance. In other cases where human intervention is required, an effective RPA tool must be able to send error messages.
9. Extended Support
Different vendors offer different support. A dedicated support team is necessary to ensure strong maintenance and support.
To make the best decision on choosing the right RPA solution for your business and access the full potential of RPA tools, get in touch with our experts today!
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As digitalization is gaining a lot of significance, many enterprises are turning to emerging technologies such as Robotic Process Automation(RPA) to streamline their operations and reduce costs. RPA automates mundane…… | <urn:uuid:9549c695-f289-49e7-99eb-a634a7c1ddd9> | CC-MAIN-2024-38 | https://www.fingent.com/ae/blog/robotic-process-automation-choosing-the-right-solution-for-your-business/ | 2024-09-07T16:29:57Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650898.24/warc/CC-MAIN-20240907162417-20240907192417-00548.warc.gz | en | 0.923701 | 1,370 | 2.75 | 3 |
Every state has its own parameters when it comes to data privacy, cybersecurity, and breach notification. But Texas? Yeah, don’t mess with it. (I know, I went there…)
Understanding the laws that regulate student data privacy is an important part of managing data at your school district. That’s why we’re here to help you out. Let’s explore the nitty gritty of Texas data privacy laws and what you can do to protect student data.
In truth, cybercrime is a nationwide phenomenon in the United States — and it’s getting worse. According to a recent study, cyberattacks increased 57% in 2022. And the worst part? Cybercriminals targeted the education sector more than any other industry.
Suffice to say, the United States has a long way to go in improving cybersecurity, especially when it comes to K-12 education. After all, school districts collect, process, and store massive amounts of sensitive student data. It only takes one data breach to expose personal information which could be used for any number of nefarious purposes, including identity theft.
So, why the focus on Texas? For one, Texas is among the leaders in enacting stronger cybersecurity and student data privacy laws.
Unfortunately, the Lone Star State also has a storied history of data security and privacy incidents over the past few years. Here’s a look at some of the most pertinent cases of compromised student data:
According to WFAA, the Texas Education Agency (TEA) released a list of over 70 districts that had experienced cyberattacks since 2019. However, this list was non-exhaustive. Why? Because per Texas law, schools aren’t required to report cyberattacks to the state agency as long as there’s no evidence that students’ personal information was stolen during the hack. In fact, the Texas legislature doesn’t require them to tell anybody whatsoever (but more on that later).
As the above examples indicate, data privacy is important. If your data security and privacy policies aren’t supported by ample cybersecurity measures every step of the way, your district runs the risk of falling victim in a similar fashion. Schools must also be aware of the Texas data privacy laws that impact them and their third-party technology vendors.
Generally speaking, all districts are subject to federal data privacy laws such as the Children’s Online Privacy Protection Act (COPPA) and the Family Educational Rights and Privacy Act (FERPA). However, the U.S. leaves it up to the state governments to set their own specific cybersecurity and breach notification requirements.
Texas, in particular, has a series of important laws that schools must follow. Let’s take a closer look at each one in more detail:
You can’t have data privacy without data protection, which is exactly what Senate Bill 820 is all about. In June 2019, Governor Greg Abbott signed this bill that requires districts to adopt an effective cybersecurity policy. Specifically, the Texas law mandates all schools to:
Notably, the bill only requires the Coordinator to report an incident to the Texas Education Agency and the parent or guardian of any student whose personal information has been compromised only if it constitutes a breach of security.
Enacted in June 2019, this bill amended the state’s previous breach notification laws, requiring businesses to provide:
The bill also specifically requires that any “person who conducts business in this state and owns or licenses computerized data that includes sensitive personal information” must disclose a breach of security. Thus, this law also applies to Texas school districts.
Originally enacted in 2009, this biometric privacy law prohibits the capture, sale or disclosure of a person’s biometric identifier without their consent. The law has largely lain dormant until recently when the Texas Attorney General brought a suit against Meta for allegedly collecting personal information via facial recognition.
How does this impact school districts? With smart home devices increasingly used in classrooms, one can only imagine the privacy implications in play if that information were to leak to the public.
Obviously, the Texas Student Privacy Act is the law that applies most directly to K-12 education. Enacted in 2017, this privacy legislation prohibits the sale of students’ personal data, bans advertisements to students based on the data they’ve shared with educational institutions or vendors, and broadly prohibits student data disclosure, with some limited exceptions.
What’s notable about this bill is that is defines multiple categories of protected information, including:
In its Biennial Performance Report, the Texas Department of Information Resources asked the state legislature to consider new laws requiring schools to disclose cybersecurity incidents within a standard timeframe. Although nothing is set in stone, it’s worth mentioning that schools should be on the lookout for new Texas data privacy laws that could go into effect in the near future.
Compliance is important, but what’s especially crucial is that your students’ sensitive personal information is kept under wraps and away from prying eyes. Question is: How do you make that happen?
That may seem like a complicated question, but the answer is just the opposite. When you squeeze an additional layer of cloud security between your district’s cloud domain and the threat vectors clawing at your data, you can simplify and streamline data protection — all in one dashboard.
Take ManagedMethods, for example. As a cloud security platform designed for Google Workspace and Microsoft 365, it automatically detects risks that could threaten your data, even the ones previously unseen. For instance, ManagedMethods can identify unauthorized third-party applications and help you remove any that pose a risk to your data. Not only does this help reduce your attack surface, but it also makes data security a painless, easy process.
But, don’t take it from us. Here’s what Cody Walker, director of technology at West Rusk County Consolidated ISD, had to say about the platform:
“ManagedMethods is going to be your best friend. In the beginning, it will relay more information to you than you want to know. But they have an awesome team that stands behind their product. I know a lot of vendors say that, but it’s the truth. From sales to support to the follow-up afterward, they’re committed to helping their customers.”
Want to learn more about how ManagedMethods can help you safeguard student data privacy? Request a free risk assessment today. | <urn:uuid:66c33b53-6896-45b0-b03d-5b8e02bc4a32> | CC-MAIN-2024-38 | https://managedmethods.com/blog/a-closeup-look-at-texas-data-privacy-laws/ | 2024-09-10T04:12:55Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651196.36/warc/CC-MAIN-20240910025651-20240910055651-00348.warc.gz | en | 0.948722 | 1,334 | 2.59375 | 3 |
Cells and tissues continuously use information from our environments—and from each other—to actively coordinate the aging process.
A new study from the University of Michigan Life Sciences Institute now reveals how some of that cross-talk between tissues occurs in a common model organism.
Recent research has shown that signaling between the intestine and brain can regulate a range of biological processes.
So far, research has focused mainly on how signals from the gut can affect neurological functions, including some neurodegenerative diseases.
Much less is known about how the brain communicates with the gut to affect certain biological process, such as aging.
LSI faculty member Shawn Xu, who is also a professor of molecular and integrative physiology at the U-M Medical School, and his colleagues wanted to determine how brain-gut signals might affect aging in Caenorhabditis elegans, or roundworms.
Because their nervous system is so well-mapped, these tiny worms offer clues about how neurons send and receive information in other organisms as well, including humans.
The researchers discovered that brain-gut communication leads to what Xu calls an “axis of aging,” wherein the brain and intestines work together to regulate the worm’s longevity.
The findings are scheduled for publication Feb. 28 in the journal Genes & Development.
Using different environmental temperatures, which are known to affect roundworms’ lifespan, the researchers investigated how neurons process information about external temperature and transmit that information to other parts of the body.
They identified two different types of neurons—one that senses warmth and the other coolness—that act on the same protein in the intestine, telling it to either slow down or speed up the aging process.
When the cool-sensing neuron detects a drop in temperature, it sets off a chain of communication that ultimately releases serotonin into the worm’s gut.
This serotonin prompts a known age-regulating protein, DAF-16, to boost its activity and increase the worm’s longevity.
The warmth-sensing neuron, in contrast, sends a compound similar to insulin to the intestine.
There, it blocks the activity of that same DAF-16 protein, shortening the worm’s lifespan.
Using these two paths, the brain is able to process cues from the external environment and then use that information to communicate with the intestine about aging.
What’s more, these signals can be broadcast from the intestine to other parts of the body, allowing the neurons to regulate body-wide aging.
And because many of the key players in these reactions are conserved in other species, Xu believes this research may have implications beyond roundworms.
“From our findings, it’s clear that the brain and gut can work together to detect aging-related information and then disseminate that information to other parts of the body,” Xu said. “We think it’s likely that this sort of signaling axis can coordinate aging not only in C. elegans, but in many other organisms as well.”
Funding: The research was supported by the National Institutes of Health, the Natural Science Foundation of China and the Ministry of Education of China. The study authors are: Jianke Gong and Shawn Xu of U-M; Bi Zhang, Wenyuan Zhang and Jianfeng Liu of Huazhong University of Science and Technology, China; and Rui Xiao of the University of Florida.
Source: Emily Kagey – University of Michigan
Video Source: Video credited to TheLSIatUM.
Original Research: The study will appear in Genes & Development. | <urn:uuid:34f33a22-c771-4ca2-b0f4-84d07d3bc5eb> | CC-MAIN-2024-38 | https://debuglies.com/2018/02/28/gut-brain-communication-demonstrates-organs-can-work-to-regulate-lifespan/ | 2024-09-13T22:52:18Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651540.48/warc/CC-MAIN-20240913201909-20240913231909-00048.warc.gz | en | 0.932066 | 749 | 3.484375 | 3 |
In mid-July, Australian Police warned curious locals to steer clear of the mysterious copper-hued cylinder that had washed up on a sandy beach north of Perth. A chemical analysis by the local fire department soon concluded that the ominous object didn’t pose a risk to the local community, but it took another week and a half of fevered speculation before its true origins became known. It came from outer space, the Australian Space Agency definitely did not intone in the voice of a 1950s B-movie narrator – specifically, from a spent Indian rocket that had failed to blaze brightly into a million petty fragments on its journey back to Earth.
What the world has not appreciated is that the rocket in question is the pride of India’s satellite industry. Launched 58 times from the country’s Satish Dhawan Space Centre with a success rate of 94%, the Polar Satellite Launch Vehicle is (usually) one of the world’s most reliable heavy-load rockets and the workhorse of an Indian space sector that has grown in stature and capability in recent years. That status has been hard won. Though Indian astronomers have been interested in charting the stars for millennia, the country’s attempts to actually reach them actually began in 1963, with the launch of a sounding rocket carried to the pad by a bullock cart. Since then, the Indian Space Research Organisation (ISRO) has developed full launch capabilities, deployed extra-terrestrial missions, and flung fleet after fleet of homegrown satellites into orbit.
Despite all these successes, however, India’s private space industry has – until very recently – struggled to get off the ground. Private participation in India’s space sector has long been stifled by strict government restrictions on satellite capabilities, but recent reforms, which were personally supported by Prime Minister Narendra Modi, have eliminated many of these regulatory hurdles. Estimates valued the global space-launch market at between $8bn and $14.5bn in 2022 – and India wants a slice of that sizable pie.
International investors, it seems, also want in on India’s emerging satellite-launch ecosystem. Consultancy firm Arthur D. Little has estimated that India’s space market could reach $100bn by 2040 – a figure that’s boosted by the nation’s growing satellite-launch capacities. “Deployment of a constellation of satellites in middle-earth orbits may emerge as a game changer for the Indian Space Business,” reads the report, which was published in July.
After a slow start, India is now home to at least 140 registered space start-ups, rising from just five at the beginning of 2020, according to the New York Times. Investors poured $119m into this ecosystem in 2022, according to Reuters. Geopolitical tensions might also be working in India’s favour. With Russia and China off the table for many Western firms, India looks set to emerge as the world’s new favourite cut-price destination for satellite launches. British satellite broadband company OneWeb, for example, launched 36 LEO satellites from India in March after the outbreak of Russia’s brutal war in Ukraine put a stop to its scheduled launches onboard Moscow’s famed Soyuz Rocket.
India’s space odyssey
The stars started to align for India’s private space sector in October 2020, when the country’s Department of Space released a draft of its New Spacecom Policy. This policy – which was finally fully unleashed, after some additional modifications, earlier this year – aimed to open India’s satellite-launch sector to private businesses. “It got everybody excited,” says Krati Hashwani, a specialist telecommunications lawyer at the law firm Trilegal in Bangalore. Even before the official enactment of the draft policy, Trilegal’s international clients already started working towards building business in India, while domestic players in the field accelerated their bids to cut the hefty costs of satellite launches.
The new policy replaced the Satcom Policy of 1997, a restrictive set of regulations that limited private and foreign participation in the sector and didn’t envisage the immense rate of technological development, explains Hashwani. The dawn of LEO (low-earth orbit) satellites, which are much smaller and cheaper than traditional geostationary satellites, has been an industry game changer, opening the doors for the rise of satellite broadband — a market that India’s particularly keen to capitalise on.
In June 2022, amid the widespread overhaul of India’s space ecosystem, Dhruva Space and Digantara Aerospace were announced as the first two private companies to receive authorisation from regulatory authority IN-SPACe to conduct space-related activities. In the case of Dhruva Space, this allowed the firm to test its homemade satellite deployers on ISRO’s PSLV in June 2022 and to launch its first CubeSats into low-earth orbit (LEO) in November 2022.
Timing has also been crucial to the unprecedented growth of India’s space ecosystem, explains Dhruva’s founder and CEO, Sanjay Nekkanti. Demand for telecommunications satellites is expected to balloon in the coming years – a fact Modi explicitly identified in his push to open up India’s space ecosystem. “The global supply chain needs to be robust and strong,” says Nekkanti. “Dhruva Space works actively in the ecosystem with 400-odd companies that have been building small yet important components for the Indian Space Programme for many decades now. By working with these vendors, Dhruva Space can deliver missions and send up missions faster, economically without impacting reliability.” With this in mind, Nekkanti continues, “India’s space industry is primed for a stellar trajectory.”
Vikram-S, India’s first privately-built rocket, lifted off from Satish Dhawan Space Centre on 18 November 2022. It was developed by Skyroot Aerospace, a start-up founded in 2018 by former engineers and scientists from ISRO. The company, which is based in Hyderabad, has raised a total of $68.1m, according to Crunchbase. They’re hoping that Vikram-S will pave the way for Skyroot’s future rockets, which are projected to carry far heavier – and more profitable – payloads into space. Founders Pawan Chandana and Bharath Daka told Reuters they’re hoping to launch their first satellite into orbit in 2023 at just half of the cost of more-established launch companies.
There’s also Chennai-based Agnikul Cosmos, which has promised to cut costs for satellite launches. The start-up, which has raised $34.5m, plans to develop a small-scale rocket, called the Agnibaan, that’ll be capable of placing a 100kg satellite into a 700km orbit. Progress has been slow: the first launch was previously projected for 2022, but none have come to fruition. Nevertheless, co-founder Srinath Ravichandran told Bloomberg he’s still confident that Agnikul can achieve its new goal of completing four launches in 2024 by taking advantage of India’s newfound embrace of space start-ups.
It may have taken a while for India’s private space industry to get off the ground “but it’s only uphill from here”, says Hashwani. “We’ve already overcome the biggest hurdle, which was for the [New Satcom Policy] to see the light of the day.”
Nevertheless, India’s newly unleashed ecosystem still has hard work ahead of it. Launching satellites is a notoriously tricky and capital-intensive endeavour, and India’s capabilities are still trailing far behind the likes of China’s. There might be lots of near-term opportunities, but any unforeseen delays can, given the rapid rate of technical developments, be immensely costly – causing India’s emerging launch providers to lose out to nimbler competitors. | <urn:uuid:c6719dfd-064d-45ee-be20-eebcd031b813> | CC-MAIN-2024-38 | https://www.techmonitor.ai/hardware/networks/the-stars-have-finally-aligned-for-indias-satellite-launch-industry | 2024-09-13T22:42:51Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651540.48/warc/CC-MAIN-20240913201909-20240913231909-00048.warc.gz | en | 0.953509 | 1,670 | 2.578125 | 3 |
Ready to learn Data Science? Browse Data Science Training and Certification courses developed by industry thought leaders and Experfy in Harvard Innovation Lab.
In the past, business leaders made decisions using productivity programs such as Excel, while only academics used complex software for analyzing complex data. Today, business leaders are increasingly recognizing the value in making decisions based on comprehensive information analysis. As a result, contemporary enterprises that span nearly every field and industry employ data scientists to evaluate information so that organizations can improve their performance outcomes. This is especially important for B2C firms that want, or need, to reduce expenses and improve customer satisfaction. In this capacity, data scientists create value using information, drive innovation and improve organizational operations.
Data scientists are highly trained specialists who possess exceptional talent in business, digital, problem solving and project management skills. They train in advanced mathematics, such as linear algebra, multivariable calculus and statistics to work in the field. Mathematics skills are especially valuable at firms where their service is defined by information. Specialists who work for large enterprises use their knowledge of machine learning to make meaningful use of massive amounts of data. When data scientists routinely work with large bodies of unstructured or imperfect information – such as strings with missing values or formatting inconsistencies– data wrangling is an invaluable skill.
A Realistic Look at the Field
Like any other career path, there are benefits and drawbacks to working as a data scientist. Data scientists must acquire a large amount of training to grow proficient in their field. Upon entering the workforce, some specialists are tasked with rebuilding a company’s information structure from scratch. At other firms, institutionalized executives may want the benefits of the latest information technology, but aren’t willing to provide the requisite funding to launch a full data initiative.
Fortunately, the good outweighs the bad for data scientists seeking employment in the current market. There’s a much higher demand for talent than there are skilled data scientists. Meanwhile, the yearning to harness the power of information is continuing to grow among business leaders, and today’s data scientists have access to analytic software that’s easy to use – at least for data scientists. Furthermore, data scientists earn a handsome salary that averages $120,931 a year in the United States. Additionally, the specialists receive yearly bonuses that range from approximately $4,000 to $27,000 each year.
The Desire for Business Growth Is Driving Demand in the Field
Business leaders employ data scientists find ways to improve their operations and drive enterprise innovation. The current crop of analytic programs allows data scientists to perform deeper evaluations than ever. This capability provides enterprises with invaluable insights gleaned from people, places and things that generate information daily.
Even though big data technology is in its infancy, researchers have uncovered empirical and quantifiable data that proves there are benefits in making decisions based on information analysis. In fact, as early as 2012 experts determined that businesses that make data-driven decisions consistently outperform their competitors. At that time, enterprises that made data-driven decisions outperformed their peers by 5-percent in productivity and 6-percent in profits. This difference, reported researchers, was statistically significant, economically relevant and resulted in improved stock performance.
Today, smart devices and the industrial and consumer Internet of Things (IoT) create a rapidly expanding body of information. As this continues, American enterprises need more experts who can collect, store and analyze vast volumes of information, and the demand will continue to rise as big data analysis becomes a standard practice for enterprises across all fields and industries.
Due to high demand and renumeration, the professional data science learning track is growing in popularity among career hopefuls. In the academic setting, data science students learn collaboration, consulting and communication skills that will be vital to their work. To prepare the next generation of data science professionals, forward-thinking academics are working to promote a learning environment where students train in near real-world environments and conduct interviews with field experts. Furthermore, data science advocates worry that if the talent shortage in their field continues, United States business performance will suffer along with the economy. Without the knowledge and skills of trained data science specialists, America’s enterprises could fail to achieve their full growth and potential.
Data scientists report that their work is rewarding and satisfying. Part of the job involves witnessing the result of a positive outcome that was made possible by detailed information analysis. The kind of work creates special moments in the business environment. When these moments occur, enterprise leaders learn something new and valuable about their organization and are empowered to make critical business decisions. | <urn:uuid:a58be9ad-5f25-4601-a9d3-9fec3dbe3b3c> | CC-MAIN-2024-38 | https://resources.experfy.com/bigdata-cloud/all-about-the-new-data-scientist-job/ | 2024-09-16T06:08:26Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651676.3/warc/CC-MAIN-20240916044225-20240916074225-00748.warc.gz | en | 0.94018 | 928 | 2.84375 | 3 |
A new research paper claims to offer a quantum-powered code-breaker of spectacular power. “If it's true, it's pretty disastrous,” says one expert.
Late last month, a group of Chinese scientists quietly posted a paper purporting to show how a combination of classical and quantum computing techniques, plus a powerful enough quantum computer, could shred modern-day encryption. The breakthrough–if real–would jeopardize not only much U.S. military and intelligence-community communication but financial transactions and even your text messages.
One quantum technology expert said simply “If it's true, it's pretty disastrous.”
But the breakthrough may not be all it’s cracked up to be.
The paper, “Factoring integers with sublinear resources on a superconducting quantum processor,” is currently under peer review. It claims to have found a way to use a 372-qubit quantum computer to factor the 2,048-bit numbers of in the RSA encryption system used by institutions from militaries to banks to communication app makers.
That’s a big deal because quantum experts believed that it would require a far larger quantum computer to break RSA encryption. And IBM already has a 433-qubit quantum processor.
The Chinese researchers claim to have achieved this feat by using a quantum computer to scale up a classical factoring algorithm developed by German mathematician Claus Peter Schnoor.
“We estimate that a quantum circuit with 372 physical qubits and a depth of thousands is necessary to challenge RSA-2048 using our algorithm. Our study shows great promise in expediting the application of current noisy quantum computers, and paves the way to factor large integers of realistic cryptographic significance,” they wrote.
Lawrence Gasman, founder and president of Inside Quantum Technology, says he’s a bit skeptical, but “It's enormously important that some people in the West come to some real conclusions on this because if it's true, it's pretty disastrous.”
Gasman said the paper’s most alarming aspect is the idea that it might be possible to break key encryption protocols not with a hypothetical future quantum computer but a relatively simple one that could already exist, or exist soon.
“If you look at the roadmaps that the major quantum computer companies are putting out there, talking about getting to a machine of the power that the Chinese are talking about, frankly, I don't know. But you know, this year, next year, very soon. And having said that, I tend to be a believer that there's going to happen soon.”
Yet Gasman said he was concerned about the numbers cited in the paper: “There's a lot of hand-waving in there.”
Andersen Cheng, CEO of the company Post-Quantum, said via email: “The general consensus in the community is that whilst these claims cannot be proven to work there is no definitive evidence that the Chinese algorithm cannot be successfully scaled up either. I share this skepticism, but we should still be worried as the probability of the algorithm working is non-zero and the impact is potentially catastrophic. Even if this algorithm doesn’t work, a sufficiently powerful quantum computer to run Shor’s algorithm”—a method of factoring the very large numbers used by RSA—”will one day be designed – it is purely an issue of engineering and scaling the current generation of quantum computers.”
Defense One reached out to several U.S. government experts, who declined to comment on the paper. But University of Texas at Austin Computer science professor Scott Aaronson was a bit harsher on the paper in his blog earlier this month. To wit: “No. Just No.”
Wrote Aaronson: “It seems to me that a miracle would be required for the approach here to yield any benefit at all, compared to just running the classical Schnorr’s algorithm on your laptop. And if the latter were able to break RSA, it would’ve already done so. All told, this is one of the most actively misleading quantum computing papers I’ve seen in 25 years, and I’ve seen…many.”
So is the paper a fraud, a “catastrophe,” or something in between? Gasman says that while the political race for quantum supremacy is tightening, it would be uncharacteristic of the Chinese research community to make a bold, easily punctured false claim. He described the majority of published quantum research out of China as fairly “conventional” and said it’s unlikely that China would risk its stature as a leader in quantum science by pushing bunk papers.
“Nobody's going to say, ‘Oh, it's the Chinese and they, you know, they're dissembling and it's all about the rivalry with the West or the rivalry with the [United States]’,” he said.
Gasman added that while China leads in some aspects of quantum science (such as appalled networking) and quantum computer science, having built the world’s “fastest” quantum computer, the United States leads in many other aspects..
Even if this paper turns out to be wrong, it is a warning of what’s to come. The U.S. government has become increasingly concerned about how quickly key encryption standards could become obsolete in the face of a real quantum breakthrough. Last May, the White House told federal agencies to move quickly toward quantum-safe encryption in their operations.
But even that might be too little, too late. Said Cheng: “We need to be prepared for the first [Cryptographically Relevant Quantum Computer] to be a secret – it is very likely that when a sufficiently powerful computer is created we won’t immediately know as there won’t be anything like mile-high mushroom clouds on the front covers, instead, it will be like the cracking of Enigma – a silent but seismic shift.” | <urn:uuid:fc77eaaf-0c61-49c0-8d5f-165d77336fbc> | CC-MAIN-2024-38 | https://www.nextgov.com/emerging-tech/2023/01/china-about-destroy-encryption-we-know-it-maybe/382070/ | 2024-09-17T11:18:23Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651773.64/warc/CC-MAIN-20240917104423-20240917134423-00648.warc.gz | en | 0.953692 | 1,248 | 2.96875 | 3 |
Encryption is a term used to describe the methods that hide the true meaning of messages using code, especially to prevent unauthorized access to the information in the messages.
Not all users of virtual private networks (VPN) care about encryption, but many are interested and benefit from strong end-to-end encryption. So let’s have a look at the different types of encryption and what makes them tick.
We have discussed the different types of VPN protocols elsewhere, and pointed out that a big factor in many of the important properties of a VPN is the type and strength of encryption. To accomplish end-to-end encryption a process called VPN tunneling is needed.
What is a VPN tunnel?
A VPN tunnel is an encrypted link between your device and an outside network. But there are significant differences between VPN tunnels and not all of them are equally effective in protecting your online privacy. The strength of a tunnel depends on the type of protocol your VPN provider uses. One of the key factors is the type of encryption.
What is encryption used for?
Encryption is used to hide the content of traffic from unauthorized readers. This is often referred to as end-to-end encryption since usually only the sender at one end and the receiver at the other end are authorized to read the content.
Privacy of Internet traffic is, or should be, a major concern, because we use the Internet in all its forms to send a lot of sensitive information to others. For example:
- Personal information.
- Information about your organization.
- Bank and credit card information.
- Private correspondence.
Since human-based code is far too easy to crack by modern computers, we rely on computers to encrypt and decrypt our sensitive data.
Types of encryption
“What are the types of encryption?”, you may ask. Computerized encryption methods generally belong to one of two types of encryption:
- Symmetric key encryption
- Public key encryption
Public-key cryptography is sometimes called asymmetric cryptography. It is an encryption scheme that uses two mathematically related, but not identical, keys. One is a public key and the other a private key. Unlike symmetric key algorithms that rely on one key to both encrypt and decrypt, each key performs a unique function. The public key is used to encrypt and the private key is used to decrypt. The mathematical relation makes it possible to encode a message using a person’s public key, and to decode it you will need the matching private key.
This type of encryption is called symmetric because you need to have the same substitution mapping to encrypt text and decrypt the encoded message. This means that the key which is used in the encryption and decryption process is the same.
Symmetric key encryption requires that you know which computers will be talking to each other so you can install the key on each one. This way each computer has the secret key that it can use to encrypt a packet of information before being sent over the network to the other computer. Basically, it is a secret code that each of the two computers must know in order to decode the information. But since this design necessitates sharing of the secret key, this is considered to be a weakness when there is a chance of the key being intercepted.
Advanced Encryption Standard (AES)
The best example of symmetric encryption is probably AES, which the US government adopted in 2001. The government classifies information in three categories: Confidential, Secret or Top Secret. All key lengths can be used to protect the Confidential and Secret level. Top Secret information requires either 192- or 256-bit key lengths.
How is AES encryption done?
The AES encryption algorithm defines numerous transformations that are to be performed on data stored in an array. The first transformation in the AES encryption cipher is substitution of data using a substitution table; the second transformation shifts data rows, and the third mixes columns. The last transformation is performed on each column using a different part of the encryption key. The key length is important because longer keys need more rounds to complete.
To deal with the possibility of a symmetric key being intercepted, the concept of public-key encryption was introduced. Public-key encryption uses two different keys at once. A combination of a private key and a public key. The private key is known only to your computer, while the public key is provided by your computer to any computer that wants to communicate securely with it.
To decode an encrypted message, a computer must use the public key, provided by the originating computer, and its own private key. The key pair is based on prime numbers of a long length. This makes the system extremely secure, because there is essentially an infinite number of prime numbers available, meaning there are nearly infinite possibilities for keys.
VPNs use public-key encryption to protect the transfer of AES keys. The server uses the public key of the VPN client to encrypt the key and then sends it to the client. The client program on your computer than decrypts that message using its own private key.
Why is end-to-end encryption important?
End-to-end encryption is important to create a secure line of communication that blocks third-party users from intercepting data. It limits the readability of transmitted data to the recipient. Most VPN services use asymmetric encryption to exchange a new symmetric encryption key at the start of each VPN session. The data is only encrypted between you and the VPN server. This secures it from being inspected by any server in-between you and the VPN, such as your ISP or an attacker operating a rogue WiFi hotspot. The data transferred between the VPN server and the website you’re visiting is not encrypted, unless the website uses HTTPS.
This is why we said in an earlier post that using a VPN is shifting your trust to a new provider. When you use a VPN you transfer access to your traffic to a third party, the VPN provider. All that visibility that users balk at relinquishing to their ISP has now been handed over to their VPN provider. Careful consideration should be given to the trustworthiness of said VPN provider. | <urn:uuid:d28d954b-e597-4f5b-bf71-c7ceccb34a8b> | CC-MAIN-2024-38 | https://www.malwarebytes.com/blog/news/2021/05/what-is-encryption-and-why-it-matters-in-a-vpn | 2024-09-20T01:37:09Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652073.91/warc/CC-MAIN-20240919230146-20240920020146-00448.warc.gz | en | 0.935293 | 1,251 | 3.578125 | 4 |
How A Cyber Attack Transformed Estonia
Cyber-attacks, information warfare, fake news - exactly 10 years ago Estonia was one of the first countries to come under attack from this modern form of hybrid warfare.
It is an event that still shapes the country today.
Head bowed, one fist clenched and wearing a World War Two Red Army uniform, the Bronze Soldier stands solemnly in a quiet corner of a cemetery on the edge of the Estonian capital Tallinn.
Flowers have been laid recently at his feet. It is a peaceful and dignified scene. But in April 2007 a row over this statue sparked the first known cyber-attack on an entire country.
The attack showed how easily a hostile state can exploit potential tensions within another society. But it has also helped make Estonia a cyber security hotshot today.
From outrage to outage
Unveiled by the Soviet authorities in 1947, the Bronze Soldier was originally called "Monument to the Liberators of Tallinn". For Russian speakers in Estonia he represents the USSR's victory over Nazism.
But for ethnic Estonians, Red Army soldiers were not liberators. They are seen as occupiers, and the Bronze Solider is a painful symbol of half a century of Soviet oppression.
In 2007 the Estonian government decided to move the Bronze Soldier from the centre of Tallinn to a military cemetery on the outskirts of the city.
The decision sparked outrage in Russian-language media and Russian speakers took to the streets. Protests were exacerbated by false Russian news reports claiming that the statue, and nearby Soviet war graves were being destroyed.
You Might Also Read: | <urn:uuid:e332b231-f396-4fa5-84be-e7fa6034987a> | CC-MAIN-2024-38 | https://www.cybersecurityintelligence.com/blog/how-a-cyber-attack-transformed-estonia-2373.html | 2024-09-07T20:12:58Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650920.0/warc/CC-MAIN-20240907193650-20240907223650-00648.warc.gz | en | 0.971896 | 331 | 2.59375 | 3 |
Industries are exploring and leveraging the newer benefits of pressure sensor tech not only to stay relevant but to drive optimization as well.
FREMONT, CA: History has shown that advancements in technology and material science are the essential drivers of the development of sensor technologies. Today, pressure sensors play a critical role in several processes in various industrial applications. The sky is probably the limit when it comes to applications of pressure sensors. Here is more to it.
• Energy Conservation
Energy conservation is highly important to reduce excessive power consumptions and its associated costs for an enterprise and to minimize the environmental impact, including a business' ecological footprint. For enhanced energy conservation, accurate pressure measurements are required. Pressure sensors allow reducing energy consumption and saving money by optimizing the indoor climate in offices and homes as well. Pressure sensors in buildings also open up a wide range of possibilities to conserve energy. This technology improves the inhabitants' quality of life, monitors parameters, including temperature and pressure in buildings while also boosting energy efficiency. Pressure sensors are also used to control the cooling levels in cars and weather stations, and in testing, devices measuring diesel truck emissions levels, wind energy systems, and wind engineering concerning new building designs for the same purpose of energy conservation.
• Quality Control and Data Acquisition
Applications of pressure sensors increase based on the need for more rigidly controlled processes associated with quality control requirements. Monitoring of pressure and vacuum can detect the need for equipment maintenance before untimely failures that cause excessive downtime and increase manufacturing costs. Pressure sensors also play an increasing role in applications such as, bottle and equipment leak detection, compressed air pressure monitoring, gas detection, suction check, pneumatic controls, and many others which require static measurements. Brewing and dairy applications use individual sanitary pressure transducers to measure the pressure in bottling lines. Pressure sensors are of the most significant utility for industrial and laboratory data acquisition too. Useful data acquired using pressure sensors include inlet-outlet or system pressure in the engine test setup, pressure drops for preventive maintenance, fluid height levels in tanks, sanitary pressure in bio or pharmaceutical industry—all of which contributes to performance monitoring and preventive maintenance.
• Safety Instrumentation
The devices used in the mining industry, including cranes, haul trucks, and hydraulic shovels can be operated with great care with pressure sensors to avoid accidents. Heavy equipment typically has numerous safety features based on pressure sensor technology. They can detect a change in pressure and convert the changes to an electrical signal that is relayed to the operator through a dial, gauge, monitor, or other instruments. Pressure sensors also reside in hydraulic booms, measuring the load to ensure it is within the capacity to avoid dangerous tip-over. These sensors can detect overloads both at initial loading and when the load shifts during transport, warning the operator to take necessary steps to prevent a loss of load. Mining sites function in all climatic conditions so that mining equipment is designed to operate across a broad range of temperatures, making pressure sensors an integral part of them. To detect a gas leak, utility providers will need a reference pressure against which the pressure that is going into the tank is measured. Pressure sensors can be of great help, indicating the presence of the leak.
Pressure sensor technology is relevant in almost all aspects of various industries, including safety, security, surveillance, monitoring, and energy efficiency. Pressure sensors are becoming central to multiple sectors, and, inevitably, they can further improve the world in many ways.
Check Out: Energy Tech Review | <urn:uuid:1a167d46-f9d6-4f06-a3da-59f30f40fdf6> | CC-MAIN-2024-38 | https://www.enterprisetechnologyreview.com/news/what-s-exciting-about-pressure-sensor-tech-today--nwid-387.html | 2024-09-11T14:01:45Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651387.63/warc/CC-MAIN-20240911120037-20240911150037-00348.warc.gz | en | 0.938667 | 707 | 3 | 3 |
When it comes to achieving sustainability in the data center, public discord can make it difficult for operators to rise above the noise. Even what it means to be ‘sustainable’ is inconsistently defined, which only serves to muddy the waters further.
We decided we needed an authority on the subject, so DCD sat down with CBRE, to find out the what, why, and how of sustainable success in the data center. But first thing’s first, what does it all actually mean? The CBRE team offered definitions for some of the key vocabulary to establish baseline principles.
Sustainability: The avoidance of the depletion of resources (environmental, social, or cultural) in order to maintain a balance. It is meeting the needs of the present without compromising the ability of future generations to meet theirs.
Environmental Social Governance (ESG): Using environmental, social, and governance factors to evaluate companies and countries on their level of advancement as it relates to sustainability. The Global Reporting Initiative (GRI) provides the world’s most widely used standards for sustainability reporting.
Science-Based Targets initiative (SBTi): Emissions reductions targets adopted by companies to reduce greenhouse gas (GHG) emissions are considered “science-based” if they are in line with the level of decarbonization required to keep global temperature increase below 2°C compared to pre-industrial temperatures, as described by the Intergovernmental Panel on Climate Change (IPCC).
Scope 1 emissions: Scope 1 emissions are direct GHG emissions that occur from sources that are controlled or owned by an organization (e.g., emissions associated with fuel combustion in boilers, furnaces, vehicles).
Scope 2 emissions: Indirect GHG emissions associated with the purchase of electricity, steam, heat, or cooling. Although scope 2 emissions physically occur at the sites where they are generated, they are accounted for in an organization's GHG inventory because they are a result of the organization's energy use.
Scope 3 emissions: Emissions that are the result of activities from assets not owned or controlled by the reporting organization but impact the organization’s value chain. Scope 3 emissions include all sources not within an organization's scope 1 and 2 boundary.
Decarbonization: Starting with a baseline performance year, decarbonization is the long term (and permanent) removal of carbon (scope 1, 2 and 3 emissions) from every element of an organization’s value chain. Through this removal, a target performance year, aligned with an organization’s ambitions and goals, is set to track ongoing progress towards full removal of GHG emissions as implementation of solutions occurs, as defined by CBRE.
Carbon neutral: Achieving a balance of carbon dioxide emissions with equal amount of CO2 removal through the application of market-based tools such as Renewable Energy Certificates (RECs), Power Purchase Agreements (PPAs) and/or carbon offsets.
Net-zero: Achieving a scale of value chain emission reductions consistent with the depth of abatement achieved in pathways that limit warming to 1.5°C with no or limited overshoot. Neutralizing the impact of any source of residual emissions that cannot feasibly be eliminated by permanently removing an equivalent amount of atmospheric carbon dioxide.
“From our perspective sustainability all begins with data integrity. That means measuring resource consumption, whether it’s energy or water. Measuring greenhouse gas emissions and commitments that may have been made for energy efficiency, green power, recycling, and waste management, to name a few,” says Ross Oakley, global director, energy and sustainability, CBRE.
This definition, centered on data integrity (data that is accurate, complete, and consistent) is very much shaped by the current drivers for sustainability. And although it would be nice to think the catalyst for greener data centers was the future of our beloved planet, public image, as well as benefits to the bottom line are certainly motivating factors.
“Companies are becoming more and more aware that their take on ESG is increasingly impactful in their shareholders' investment decisions. This has spurred many of our clients to react and adopt ambitious carbon reduction goals," says Ryan Carter, global energy and sustainability account director at CBRE.
This heightened investor scrutiny, combined with new regulations mandating greater transparency and public disclosure of emissions in certain geographies, has companies clamoring for change faster than any climate crisis ever could. And to make matters a bit more complicated, different geographies mean different regulations.
“Here in the US there's one ruling that looks like it could have a gigantic impact, and that is the Securities and Exchange Commission (SEC) ruling that may require companies to disclose their greenhouse gas emissions and climate-related risks that can impact their business,” says Oakley.
“Due to our global footprint at CBRE, we have to make sure that we understand what sort of legislation is moving through which governments, where they are, and the status and impact of that legislation.”
This kind of knowledge is invaluable to organizations looking to achieve their ESG goals (or actually set some). Without it, they not only risk non-compliance, but costly reputational damage.
So, what can companies do to prevent this?
“There's always a concern around public opinion that spurs companies to adopt frameworks that add credibility to their ambitious carbon reduction goals, such as the Science Based Targets initiative (SBTi) framework,” says Carter.
Targets are considered ‘science-based’ if they are aligned with what the latest climate science deems necessary to meet the goals of the Paris Agreement, such as limiting global warming to below 2°C above pre-industrial levels and pursuing efforts to limit warming to 1.5°C.
Roughly 39 percent of global CO2 emissions are generated from the built environment and 28 percent come from facility operations. The best science we have tells us we need to limit global temperature increase to 1.5 degrees Celsius to mitigate the most extreme effects of climate change. Decarbonization is a solution to reverse this trend, otherwise we will cross the point of no return in 10 years if we emit more than 500 gigatons (GT) of CO2 emissions.
Both CBRE and its key clients have net-zero goals in line with the SBTi framework. Working with these goals helps cut through the aforementioned noise, encompasses all mission Scopes, 1, 2 and 3 and provides a clearly defined pathway for companies to reduce greenhouse gas emissions.
Interestingly, it isn’t just this framework, or customers that have spurred clients into action.
Despite one of CBRE's global IT clients having procured an impressive 85 percent of its energy from renewable sources as of this year, employee engagement surveys have revealed that their employee base is still asking for more, in the form of on-site solar. This serves to highlight that the pressure to implement sustainable practices is not only coming from potential investors, stakeholders, and customers, but from workforces demanding real progress from their employers.
This amalgamation of customer and employee feedback, alongside the use of the SBTi framework, indicates that a siloed approach to sustainability won’t be sufficient and a holistic, forward-looking strategy is now a necessity.
“We’ve definitely seen a switch in the industry from, say, certifying buildings or seeking individual pieces of equipment towards a more holistic view,” says Carter.
“There was once a time when there was a budget for seeking a certification or a plaque on the wall of a facility, whereas now the goal is the much larger, more meaningful, more ambitious target of net-zero. That goal now determines what the budget is going to be.”
Work with what you’ve got
So, with a newfound understanding of local regulations, and a set of clearly defined ESG goals for your data center in line with the SBTi, now you have to achieve them. But how?
The advent of new technology, like AI, automation, and innovative cooling techniques may suggest a solution to every challenge, but upgrading can be expensive and isn’t always the best solution.
“There's quite often an opportunity to optimize existing equipment and building materials and make the most use out of current systems before leaping to the next technology, which would be part of your Scope 3 emissions,” says Carter.
“It’s important to ensure we're making the most out of the materials we have currently available, rather than extracting new virgin materials. Although there is a need for early adopters to drive the technological solutions to climate change, all too often blatant greenwashing is entirely ignored, with high priority given to the marketability of the new and shiny rather than focusing on the ultimate goal of decreasing life cycle emissions.”
Looking at the long-term lifecycle cost of these projects, rather than a short-term focus on simple payback, will not only make data centers more valuable and more efficient, but presents them as a far sounder investment for potential buyers if they were ever to be sold.
And the bottom line is what it all boils down to. Despite the fact we’re trending in the right direction, spiking energy costs, particularly in the EU, have meant operators have had to become even more aggressive when it comes to reducing operational costs. With companies spending millions of dollars per month on energy, CBRE is uniquely positioned to help its clients understand that energy is a controllable cost and can offer practical advice on how to manage it.
CBRE takes a holistic approach that considers every asset in the portfolio and its alignment with client decarbonization target performance goals. Utilizing portfolio decarbonization solutions, CBRE demystifies the journey to carbon abatement for clients, with the goal of reaching net-zero carbon emissions or better.
Once goals have been identified, CBRE will create a decarbonization roadmap for clients with clear actions and measurable outcomes. With a project management team of more than 10,000, CBRE can also help clients implement these strategies at scale quickly and affordably.
“Every client is in a different place on their decarbonization journey. We meet them where they are at today, orchestrate where they want to be in the future with their stakeholders, and provide services with solutions to reach their future target performance goals. This allows our clients to focus on their core business while we focus on their ESG and decarbonization efforts,” says Sarah Spencer-Workman, global director of decarbonization at CBRE.
Back to basics
With cooling accounting for anywhere between 40 to 60 percent of a data center operator’s total energy bill, cooling is a good starting point for reducing operational costs and optimizing energy usage. However, you need to be able to walk before you can run and CBRE can help ensure the correct process is followed.
“We need to ensure all the basics are taken care of first. The first step is measuring PUE. The next step is optimizing air flow, preventing hot and cold air from mixing, and eliminating hot spots. The final step is turning up temperatures – basically allowing the whitespace to reach higher temperatures without exceeding any client SLAs,” says Oakley.
Then and only then can you start exploring other solutions. For instance, CBRE suggests maximizing your building management system via the optimal placement of sensors to ensure it has the ability to grab more data points. Once accurate data has been captured, the opportunity to optimize by introducing new technology tools becomes available.
For those just starting out on their sustainability journey or others who might be at an impasse with their current strategy, CBRE’s dedicated team of experts are on hand to help educate clients on what it will take to meet their goals and help identify the areas of highest opportunity across the portfolio.
Once you’re on the road to green, you will soon see the impact and competitive edge a sustainable operation provides. Not only in relation to the bottom line, but the ability to attract and retain new talent, customers, and investors who are looking for those truly committed to sustainable data centers both now and in the future, greenwashers need not apply.
To find out more about CBRE's data center services click here.
More from CBRE
Dive into management & operations with this DCD>Talk from our live DCD>Connect Silicon Valley event
And they decided to sponsor the DCD award | <urn:uuid:2fd83109-cf98-4fdb-8a32-126d6d97b341> | CC-MAIN-2024-38 | https://www.datacenterdynamics.com/en/marketwatch/sustainability-the-bigger-picture/ | 2024-09-12T19:15:08Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651491.39/warc/CC-MAIN-20240912174615-20240912204615-00248.warc.gz | en | 0.948092 | 2,576 | 2.609375 | 3 |
What is the Norwegian Personal Data Act 2018?
Although Norway is not a member of the European Union (EU), it is a member of the European Economic Area (EEA), which ensures the country enjoys the same four fundamental EU freedoms of movement of goods, services, persons, and capital.
Norway’s laws regarding data protection include the Law on the Processing of Personal Data (Personal Data Act or PDA) of June 15, 2018. The PDA aligns closely with the EU’s General Data Protection Regulation (“GDPR”) that came into effect in May 2018, but it does contain certain specific national variations and additions. It replaces earlier national data protection laws, ensuring Norwegian legislation fully complies with GDPR standards.
Because Norway is an EEA country, judgments from the EU’s Court of Justice (CJEU) aren’t directly applicable in the country. However “Datatilsynet,” which translates to Data Protection Authority in English, is Norway’s official data protection authority.
Historical Perspective: Data Protection in Norway
Data protection law in Norway began with the Data Protection Act in 1978, one of the first of its kind globally. This Act established the Data Inspectorate, now known as the Datatilsynet, to oversee data protection and ensure compliance.
As digital technology evolved, Norway updated its data protection laws to address emerging privacy challenges. The most significant shift came with the GDPR in 2018, prompting Norway to adopt the PDA and align national law with the GDPR. This underscored its commitment to stringent data protection standards, enhancing individual rights, and imposing stricter obligations on organizations.
Relevant provisions of the PDA include:
- Age of consent. Section 5 of the PDA sets the age of consent at 13 years. There is no general age at which a child can handle the processing of personal data on their own, but several exemptions allow children to consent in some instances.
- Freedom of speech. Only certain Articles of the Act apply when personal data is processed “exclusively” for journalistic purposes.
- Employment context. Certain personal data categories can be processed in an employment context when necessary for duties or rights under labor laws.
The law also allows special personal data categories to be processed without data subject consent if they are necessary for archival purposes in the public’s interest or if they relate to statistics or scientific or historical research.
A noteworthy provision in the Act is that imitation surveillance cameras, or signs that imply an area is being monitored when it’s not, are prohibited if real cameras processing personal data would be prohibited in the same areas.
GDPR and the NPD Act: A Symbiotic Relationship
The GDPR was incorporated into the EEA agreement and became effective in July 2018. Norway is bound to it in the same way as EU member states. There are no national law variations from the GDPR, and current exemptions generally align with GDPR standard permissions when it comes to:
- National security and defense.
- Freedom of expression and information.
- Public access to documents.
- Research and statistics.
- Employment law.
The collaborative relationship between the NPD and GDPR ensures that Norway adheres to international data protection standards while retaining the right to address specific national needs and legal traditions. It functions as follows:
- Uniformity and consistency. The GDPR provides a uniform framework for data protection across all EU and EEA member states, including Norway. Aligning its PDA with the GDPR ensures Norway’s data protection standards are consistent with those of other countries in the region, facilitating easier data flow and cooperation across borders.
- Local adaptations. The GDPR sets minimum standards but also allows member states some flexibility to adapt certain provisions to reflect local laws and practices.
- Enhanced protection and rights: The GDPR’s emphasis on entitlements, such as the right to access, rectify, and erase personal data, as well as restrictions on data processing and the movement of data, are all embedded within the PDA. This enhances Norwegian citizens’ protection by providing them with rights that have a strong backing from EU legislation.
- Regulatory oversight and compliance. The GDPR mandates establishing or designating a national supervisory authority, which in Norway is Datatilsynet. This body ensures both legislations are enforced, providing a mechanism for compliance and addressing grievances.
- Response to technological and social changes. The GDPR and the PDA are designed to be dynamic, addressing ongoing changes in technology and data usage. This allows Norway to adapt to new data protection challenges promptly while remaining aligned with broader European standards.
Key Provisions of the Norwegian Personal Data Act
The Norwegian PDA provides a robust framework for data protection, emphasizing transparency, security, and accountability in data processing practices. Key features include:
- Individual rights. Individuals enjoy various rights regarding their personal data, such as the right to access, rectify, and delete their data, and the right to object to certain types of processing.
- Data processing requirements. Organizations must ensure that personal data is processed lawfully, transparently, and for specified, explicit purposes. The data collected should be adequate, relevant, and limited to what is necessary in relation to the purposes for which they are processed.
- Consent: Like the GDPR, the PDA emphasizes the importance of consent, which must be freely given, specific, informed, and unambiguous. Data subjects have the right to withdraw consent at any time.
- Data protection officer (DPO). Certain organizations must appoint a DPO who oversees compliance with data protection laws, including training staff and conducting audits.
- Data breaches. Organizations must promptly report data breaches to the Norwegian Data Protection Authority (Datatilsynet) and, in certain cases, to the affected individuals, especially if the breach poses a high risk to the rights and freedoms of individuals.
- Cross-border data transfers. Transferring personal data outside the EEA is restricted and allowed only under specific conditions to ensure the level of protection afforded to personal data is not undermined.
- Enforcement and penalties. Datatilsynet is tasked with enforcing the Act and has the power to issue warnings, ban processing, and impose fines for violations.
Datatilsynet is an independent administrative body established under Norwegian law to ensure an individual’s personal data is processed in compliance with the Norwegian PDA and other relevant privacy laws. It operates under the Ministry of Local Government and Modernization but acts independently when performing its duties.
Key functions and responsibilities include:
- The Authority oversees and ensures public and private entities comply with data protection laws when processing personal data. This includes reviewing how organizations handle personal information and enforcing laws through audits and inspections.
- Guidance and advice are provided to individuals and organizations on how to comply with data protection regulations. The Authority also educates the public and businesses about their rights and obligations under these laws.
- Datatilsynet receives and investigates complaints from individuals who believe their data protection rights have been violated.
- The Authority contributes to the development of national and international policies on data protection and privacy.
- Datatilsynet has the power to issue administrative fines and other sanctions to enforce data protection laws.
- The Authority is responsible for keeping a registry of data processing operations that require notification under Norwegian law. It also reports on its activities and the state of data protection in Norway.
Datatilsynet plays a crucial role in safeguarding personal privacy rights in the digital age, ensuring data protection practices are conducted transparently, responsibly, and legally across Norway.
Who Does the Norwegian PDA Apply To?
The PDA applies broadly to all public and private entities that process personal data within Norway. This includes:
- Organizations headquartered in Norway as well as foreign entities that process the data of individuals residing in Norway as part of their business activities.
- Any organization involved in data processing activities such as collecting, storing, using, or sharing personal data, must ensure that these processes adhere to legal standards of transparency, security, and accountability.
- Individuals and entities outside Norway if their data processing activities affect Norwegian residents.
Compliance with the Norwegian Personal Data Act
Many Norwegian businesses struggle to meet PDA compliance requirements; it’s estimated that up to 80% of the country’s small businesses are likely violating privacy policies daily. An analysis conducted in 2022 found that more than half of Norwegian business websites violate privacy rules by sharing data about their users with Google, Facebook, and other platforms without their consent. Reasons for this range from vague legal language to a insufficient resources to comply with GDPR requirements. Many organizations also find it challenging to keep up with data management and storage, as they don’t have the latest technological solutions or expertise.
Ready or not, organizations operating within Norway or dealing with the personal data of Norwegian residents need to understand current requirements and implement measures to protect personal data in accordance with the PDA. Potential penalties for non-compliance with key laws include:
- Administrative remedies from regulators and law enforcement up to EUR 20 million or four percent of the total worldwide annual turnover of the preceding financial year, whichever is higher.
- Criminal penalties from law enforcement and regulators.
- Private remedies, including individual complaints with the data protection authorities and claims of material or non-material damages. | <urn:uuid:6d194430-8247-4a17-8bb5-2e890d447424> | CC-MAIN-2024-38 | https://www.velotix.ai/privacy-regulations/norwegian-personal-data-act/ | 2024-09-17T15:02:21Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651800.83/warc/CC-MAIN-20240917140525-20240917170525-00748.warc.gz | en | 0.931244 | 1,926 | 2.734375 | 3 |
SOA Patterns > Capability Composition Patterns > Capability Composition
Capability Composition (Erl)
How can a service capability solve a problem that requires logic outside of the service boundary?
A capability may not be able to fulfill its processing requirements without adding logic that resides outside of its service’s functional context, thereby compromising the integrity of the service context and risking service denormalization.
When requiring access to logic that falls outside of a service’s boundary, capability logic within the service is designed to compose one or more capabilities in other services.
The functionality encapsulated by a capability includes logic that can invoke other capabilities from other services.
Carrying out composition logic requires external invocation, which adds performance overhead and decreases service autonomy.
Inventory, Composition, Service
The individual capabilities of services can be aggregated to collectively help solve the large problem from which they were originally derived. | <urn:uuid:82b828aa-37b5-4a42-a24d-d6ee5a1a04dd> | CC-MAIN-2024-38 | https://patterns.arcitura.com/soa-patterns/design_patterns/capability_composition | 2024-09-18T22:26:04Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651941.8/warc/CC-MAIN-20240918201359-20240918231359-00648.warc.gz | en | 0.91383 | 188 | 2.625 | 3 |
As digitisation ramps up, industry leaders are utilising IoT technology more frequently. Paul Keely, Chief Cloud Officer at Open Systems, discusses this in further detail; explaining what IoT and OT is, as well as drawing our attention to the importance of understanding the most significant issues that put IoT and OT systems at risk.
Corporate deployments of Internet of Things (IoT) devices are growing briskly as more and more connected devices are deployed by businesses worldwide both big and small. From smart refrigerators in breakrooms, to copiers that order their own toner, to sensors for the early identification of breakdowns in mission-critical equipment, IoT enables companies to monitor, automate, control and manage many aspects of their business operations.
However, these devices and their network connections represent a potential increase in corporate attack surfaces and offer more weaknesses for attackers to exploit. A major reason for this is that these devices often have in-built weaknesses that are often overlooked, or even unknown to IT staff, as smart devices are seldom managed as carefully as their traditional IT counterparts.
Simply put, the IoT is a system in which devices and sensors are interconnected for the collection and exchanging of important data. IoT devices connect to the Internet through a variety of networks, such as Wi-Fi, cellular, Bluetooth and Zigbee. Additionally, these devices can also use Google Home, Amazon Echo and other such gateways for Internet connectivity.
The wide variety of IoT devices includes simple sensors for detecting and monitoring temperature, motion, sound, light, gasses and other factors, as well as complex devices including smart thermostats and even cars. The data collected by IoT devices can be used to monitor and control the devices, as well as to track and manage the data collected by the devices.
Turning our focus to the industrial uses of IoT; we enter a category of these devices called Operational Technology (OT). This more business-focused category of IoT, refers to the hardware and software used to identify, monitor and control physical devices, processes and events in an organisation.
An early adopter of OT is the agricultural industry, which has enthusiastically embraced it. Connected devices are widely used for the real-time monitoring of sunlight levels, soil moisture, humidity, temperature and other factors affecting crop health. This data is then used to automate irrigation along with other farming operations. Similarly, both local and national governments employ a wide variety of smart devices in monitoring energy usage and water and air quality.
What are the security issues for IoT and OT?
One of the main issues with IoT devices is the lack of awareness that IT organisations have over their estate – this primarily applies to IoT and not so much to OT devices. The reason for this is that OT devices usually cost a lot of money and actually control the business functions that a company uses to do business; such as the CNC machine tools used by an industrial manufacturer. IoT devices on the other hand suffer from ‘device sprawl’, whereby it’s easy for relatively cheap devices to be deployed to office buildings, the majority of which just use Wi-Fi for connections.
This lack of awareness means that these devices are not part of the corporate patching and firmware updating processes. In particular, this failure to routinely update firmware has thus far been quite an issue.
Data breaches, cyberattacks and privacy issues are often the result of IoT devices being compromised. Once a vulnerable IoT device has been breached, bad actors can often move laterally within a company’s network, depending on the network’s architecture and the device’s type of connection.
More worryingly, we’re now seeing IoT devices falling victim to command-and-control (C2) attacks. It was recently determined that Trickbot, a malware that previously targeted computers and IT systems, is now affecting IoT devices. Trickbot has compromised IoT devices and then used those devices to attempt lateral movement and gaining access to the target network with more critical data.
As if this wasn’t enough, the growing adoption of OT in many industries – and manufacturing in particular – presents bad actors with a potential opportunity to conduct cyber-kinetic attacks in which their attack in cyberspace impacts the physical word. For instance, by preventing a centrifuge from automatically slowing down at a set point, an attacker could cause the centrifuge to continue spinning until it breaks down which could injure nearby workers.
The potential for such attacks to disrupt or even shut down business operations is real. To ensure adequate protections against these attacks, it is important to first understand the most significant issues that put IoT and OT systems at risk:
- Lack of visibility
The old saying; ‘you can’t protect what you can’t see’ is just as applicable to IoT and OT as it is to other IT environments. Unfortunately, many companies lack the necessary instrumentation to discover all of their IoT assets and gain visibility into their entire IoT estates.
- Poor patch management
Most of the standard device management toolsets like Microsoft’s Configuration Manager are not capable of patching IoT devices. Even when organisations account for the IoT devices in their environment, they don’t always manage them appropriately.
- Insecure software and firmware
It is an unfortunate truth that IoT and OT devices often have inherent software and firmware vulnerabilities, despite the hard work of the staff administering the systems. There are frequent reports online showing insecure devices being sold with known vulnerabilities years after they are detected.
- Account and password mismanagement
The failure to properly manage accounts and passwords remains a critical issue. Thousands of security cameras used by numerous organisations were breached after an administrator’s account credentials were posted on the Internet.
- Weak and inconsistent monitoring
Effectively using SIEM and other cybersecurity tools to properly monitor IoT and OT devices and reliably detect threats has been extremely hard. This often results in these devices being monitored by a secondary system, or manually checked, or sometimes not monitored at all.
Though the threats are real and the issues limiting effective security challenging, the value of IoT and OT are too great to ignore.
Fortunately, properly securing IoT and OT devices is fairly straightforward. It starts at deployment when devices should be correctly configured. Promptly installing patches is also key as is practicing good cyber hygiene at all times. Additionally, maintaining an up-to-date inventory of all IoT and OT devices is essential. Without such an inventory – which should include relevant information about all these assets – companies won’t have the visibility to protect these devices.
Click below to share this article | <urn:uuid:8dc6f4ae-1d1f-4844-9599-b47376b162e5> | CC-MAIN-2024-38 | https://www.intelligentciso.com/2022/09/21/iot-and-ot-security-the-challenges-benefits-and-why-you-should-care/ | 2024-09-20T04:29:24Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652130.6/warc/CC-MAIN-20240920022257-20240920052257-00548.warc.gz | en | 0.95814 | 1,342 | 2.6875 | 3 |
Just as with early developments in racial and gender diversity in industry, and mental health at work, discussion about neurodiversity within the workforce has so far been driven by those who are personally associated with it. It is now time for this discussion to step up to the next level. Our industry needs clearer and more specific efforts towards neuro inclusiveness for the benefit of all and to showcase how inclusiveness can lead to organisational advantage.
What is neurodiversity?
Neurodiversity is the term used to cover a range of differences in brain function and behavioural traits. It generally includes conditions such as ADD, ADHD, Autism and Asperger’s syndrome, as well as Dyslexia and Dyspraxia. In essence, neurodiversity recognises that our brains interact with the world in different ways, which can create challenges, but, most importantly, also advantages.
What is the current situation for the neurodiverse?
It is estimated that around 15 per cent of the UK population is neurodiverse in one or more identifiable or “diagnosable” way. Whilst the last two decades have seen progress, we are still at the early stages of awareness of neurodiversity, both in terms of scientific research and societal response. Our education systems have been attempting to adapt, serve and support neurodiversity for many years, but in the workplace and amongst the adult population, neurodiversity can still be seen to carry a stigma, and be perceived as a weakness or a nuisance.
The National Autistic Society says that 68 per cent of autistic adults in the UK are unemployed, and yet 77 per cent of those surveyed, state that they want to work. NeuroCyber, a not-for-profit group that is working to improve outcomes for neurodiverse individuals, juxtaposes these statistics with the predicted 3.5 million skills gap that the cybersecurity sector is expected to suffer globally by 2021.
Data trends vs stereotyping
Stereotyping of neurodiverse people should be avoided, and we are quick to educate those who repeat the myth that autistic people are all great at maths but struggle to empathise or communicate. Addressing neurodiversity is not about legitimising pigeon holes into which we can place people, it is about acknowledging that we are all different and that individuals need to be supported with, and valued for, their unique strengths and weaknesses. We know we should be incredibly cautious of sweeping statements about the inherent capabilities of individuals who have a particular diagnosis. So when NeuroCyber states that up to three quarters of cogitatively able neurodiverse adults may possess the aptitude and skillset for a successful career in cybersecurity. How do we handle the conflict? What data is available to ensure this statement is more than just a stereotype? The answer is: we need more.
A shortage of data
There are two ways we can address this void of information. The first is better data on the aptitudes found within individuals in conventionally challenging parts of the neurodiversity spectrum. Data on neurodiverse populations is hard to find, which is why we often step back into the more abundant, yet narrow, autism data sets. But even there we do not have much in the way of statistical evidence of aptitude.
This data will be found through academic research; something that needs funding. In today’s public spending climate, we need altruistic private companies to step up and fund this research with no guarantees of what the results will find.
Unpicking prejudices and negative associations around neurodiversity (“can be a little blunt” or “isn’t very sociable”) requires us to add positive associations to the mix. We need data to prove that autistic people have a high attention to detail, can spot patterns, trends and anomalies and are able to make independent unbiased decisions. Otherwise we are going on a positively intentioned hunch. All my life experience tells me that neurodiversity can be an enormous asset in cybersecurity, but we can’t expect to convince people to make changes based on anecdotal evidence.
The second way we can address the data shortage is to better assess the impact on organisational performance of having a genuinely neurodiverse workforce. We have seen this approach, as an example, employed to good effect by those championing greater female inclusion at the higher echelons of business.
Years ago, discussions around gender diversity in the workplace moved on from consideration of HR and compliance, towards assessment of the performance of organisations with and without women on the board. It was no longer imperative to attest that a specific woman was better than a specific man, because it could be proven that excluding the women was detrimental to the business. We now state as fact that companies with women on the board outperform those without.
We need to analyse the relationship between company performance and the extent of neurodiversity within the workforce to be able to conclusively prove our hypothesis that neurodiversity is an asset and move beyond discussions of the specific traits of individuals.
We are seeing the start of this research in the cybersecurity industry, championed by progressive employers who are driven by market need to make the necessary changes. Organisations like NeuroCyber, the National Autistic Society and employers such as HSBC, the civil service and GCHQ, to name a few, have shown the value of neurodiversity inclusiveness.
However, despite the data and the discussion, we must not overlook the stigma that can go alongside a spectrum diagnosis. The National Police Autism Association states on its website “Autism would be an additional hurdle to overcome during the assessment centre and initial training”, and a google search will leave many aspiring pilots concerned that a diagnosis is likely to restrict their ambition.
We use a very few labels to describe a vast spectrum of human neuro characteristics, and it is resulting in confusion and prejudice. Just as many are battling to make mental health less taboo, broadly understood and better supported, so we need to open up awareness of the natural variation in our healthy brains and support neurodiverse role models to prove that a diagnosis can be a certificate of aptitude, not a limiter on achievement.
A version of this article was first published by IT Pro Portal. | <urn:uuid:51b382e0-5d1a-4a13-b37f-ce95fd2667f8> | CC-MAIN-2024-38 | https://www.netskope.com/es/blog/supporting-neurodiversity-in-cybersecurity | 2024-09-20T04:43:06Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652130.6/warc/CC-MAIN-20240920022257-20240920052257-00548.warc.gz | en | 0.954332 | 1,271 | 2.984375 | 3 |
What does DNS do?
The DNS, or the Domain Name System, maps domain names to IP addresses and is the glue that holds our modern Internet together.
A Brief History of the DNS
Thirty years ago, when the Internet was still in its infancy, whenever you wanted to visit a website you had to know the IP address of that site. That’s because computers are and were only able to communicate using numbers. An IPv4 address looks something like this: 192.168.1.25. It’s long, hard to remember, and we (humans, I presume) are not robots. We needed a way to translate computer-readable information into human-readable. And it had to be fast, lightweight, and scalable.
In the early 1980’s, Paul Mockapetris came up with a system that automatically mapped IP addresses to domain names.. and the DNS was born. This same system still serves as the backbone of the modern Internet, today. And yet, only a small subset of the world knows that it exists, and an even smaller group understands what it does. The real problem is that the people that need to know how it works and could actually benefit from this knowledge… don’t take the time to learn. If you’re a webmaster, web designer, front-end developer, IT, or technical support you need to know the basics of how DNS works and how it can help you manage your domain’s presence on the Internet. | <urn:uuid:a59142ee-1294-4426-9b52-785ffbcc9a6a> | CC-MAIN-2024-38 | https://support.constellix.com/support/solutions/articles/47000862623-what-is-dns- | 2024-09-09T04:58:57Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651072.23/warc/CC-MAIN-20240909040201-20240909070201-00648.warc.gz | en | 0.946926 | 308 | 3.25 | 3 |
Authors: Rod Scrimger, Paul LaSalle, Mridula Parihar and Meeta Gupta
TCP/IP is the protocol suite that runs almost every network environment today. Consequently there are tons of books about TCP/IP – some deal with network implementation issues, some with applications, others are about security implications, and still further you can find books on protocol theory and protocol analysis. Finally there are books which try to give you an overview, a starting point on everything there is to know about TCP/IP. “TCP/IP Bible” is one such book. Who are the authors and have they done a good job?
About the authors
The book is written by a team of 5 authors: Rob Scrimger, Paul LaSalle, Mridula Parihar, Meeta Gupta and Clay Leitzke. All of them are network specialists, hold various certifications in networking topics (mainly from the Microsoft certification programme), and work as trainers and educators. The Indian pert of the team (Parihar and Gupta) work for India’s leading IT training and education company NIIT Ltd.
Inside the book
As one would expect from people with extensive experience in teaching and training, the book offers a clear writing style and a systematic presentation of the topics – as is evident from a first glance inside its covers.
The book is organized in four parts, each with several chapters covering individual topics.
Part I – Understanding TCP/IP Communications, deals with the various layers of the TCP/IP stack. First, the OSI reference model is introduced and then you see how this translates in practice into the TCP/IP stack model. Each chapter in this part covers a particular layer of the stack: physical, network, internet, transport and application.
In Part II – Working with TCP/IP, you get all the information needed to install and configure TCP/IP on today’s most popular operating systems. The authors included instructions for manual configuration on a typical Linux distribution, as well as on all the Windows systems from Microsoft.
Automatic configuration is examined next. Here you’ll find information on protocols for automatic configuration of TCP/IP nodes: Bootstrap protocol (BOOTP) and Dynamic Host Configuration Protocol (DHCP). Closing part II is a chapter on naming and name resolution issues. The local HOSTS file, DNS, NetBIOS naming and WINS are crucial topics when designing a network, and in this chapter you’ll get an overview of these topics as well as some implementation details (for ex. configuring DNS on Windows 2000).
Part III – Common TCP/IP Applications is about the most popular applications that run on TCP/IP. But first of all, the authors examine the issues with providing internet access to your network. Private network addressing is covered as well as guidelines for designing a private network. Since connecting a network to the internet is a high security risk, the authors included overviews of firewalls (from simple packet filters to stateful packet inspection firewalls and applications proxy firewalls), network address translation (NAT), VPNs and tunneling protocols. You will notice these are the features integrated in most security appliances now available on the market.
The next chapters cover the individual applications:
- file utilities (NFS, DFS, FTP);
- remote command utilities (telnet, remote login, remote shell, secure shell, remote execute and terminal servers);
- printing over the network (configuring network printing both in the Linux and MS world);
- www applications and protocols (covers overviews of HTML, HTTP, web servers and related technologies);
- mail and news (SMTP, POP, IMAP, NNTP protocols are covered here, including an introduction to how the mail process works);
- enterprise information services (this is the chapter about network directory services; the X.500 standard, LDAP, Network Information Service and Active Directory are introduced).
The fourth and last part of the book, Building and Maintaining TCP/IP Networks, is focused on implementation and maintenance guidelines. The chapters in this part contain very useful information on planning, building and monitoring your network. First of all the authors focus on how to determine your addressing scheme, calculate address needs and the amount of traffic users will generate in a single day. This information is very important while planning a network. Next chapter is about designing routing for the network, and some advices for server placement follow. Also, a chapter on network security is included, which covers authentication, encryption, PGP and SSL.
The following chapters are devoted to troubleshooting network and connectivity problems and monitoring TCP/IP networks (including tools for packet capture i.e. sniffers). Particularly useful here is a dissection of the typical network troubleshooting process. Finally, the last chapter is about technologies that are just being introduced or will be in the near future: IPv6, TCP/IP in the wireless world, and smart appliances.
After reading the book, what are my thoughts?
TCP/IP Bible is perhaps an unfortunate choice for a title. In fact, the book contains instructions and guidelines for setting up a whole network, from the physical assemblage to the implementation of various network based services in an organization. It is not merely about the TCP/IP protocol suite, it contains much more.
Trying to round up and collect all there is to know about TCP/IP networking into a single volume, seems like a monstrous task. Yet, the authors managed to do just that, in a very accessible way. On the other hand, most of the topics covered are treated only as an overview or introduction to the subject. If there was a detailed discussion of each topic, the book would be 10 times longer (and heavier), not the 600 pages you get with this volume. Therefore my suggestion is: don’t read this book if you seek detailed discussion of TCP/IP protocol suite inner workings.
I couldn’t really decide whom the book was intended for. The publisher advertises it as suitable for all reader levels, from beginning to advanced. Maybe the best answer is given by the authors themselves: they acknowledge the book is intended as a primer, a starting point on the TCP/IP protocol. And in this sense it’s a very good book, especially for those who have already started working with TCP/IP, perhaps implemented a simple network and some basic services, but want to find out what else is there to know. As for intermediate and advanced users, this book can be at best a reference on TCP/IP, not a source of in-depth knowledge.
The authors did a particularly good job in explaining the “theoretical” part of TCP/IP – the OSI model and its correspondence to the TCP/IP layers. This may seem like esoteric stuff, but in order to gain a deeper understanding of how networking really works, some theoretical background is indeed required. And this knowledge will certainly pay off as better analytical and troubleshooting skills, essential for IT staff. Also, the authors have invested an effort to cover both the Linux and the Windows world, especially when providing information on configuring various TCP/IP-based services and applications.
This book is a Bible in the sense it provides basic knowledge on TCP/IP related technologies. It’s a very good primer, but for further enlightenment you’ll have to explore further, perhaps choose a more specialized book. | <urn:uuid:b6e291be-fdec-457d-844b-957c571349d1> | CC-MAIN-2024-38 | https://www.helpnetsecurity.com/2003/05/19/tcpip-bible/ | 2024-09-10T09:44:49Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651241.17/warc/CC-MAIN-20240910093422-20240910123422-00548.warc.gz | en | 0.933749 | 1,535 | 2.515625 | 3 |
In this section: |
There are several ways in which you can define the operating environment for FOCUS. You can:
UNIX environmental variables enable you to define the operating environment for FOCUS. The focus shell script assigns default values to these variables. If you wish to assign values other than the default, you can declare the desired variables and export them before you start FOCUS. In addition, you can assign values for some of the variables on the focus command line.
To declare a variable and assign a value before you start FOCUS, issue the following commands:
variable=value export variable
Is the name of the variable you wish to declare.
Is the value you wish to assign.
Is a UNIX command that makes the variable available to all subsequent processes.
If the values you wish to assign are permanent, consider including the declarations in your UNIX profiles, the MI file, or in a .*rc file in your home directory.
Environment variables can be set and then read while in the FOCUS environment using the FGETENV function.
You can define the FOCUS operating environment using command-line parameters. The syntax is:
focus [option ... option]
The following list summarizes the available options:
-f script |
Starts FOCUS, with input from file script.t3i, and output to file script.t3o. |
-x "command" |
Starts FOCUS with a single command as input. Output goes to the terminal. |
Starts the FOCUS Database Server (sink machine). |
Stops the FOCUS Database Server (sink machine). |
Is used in conjunction with -traceon. Provides an option to gather and package trace files and other diagnostic information for Customer Support Services. |
Turns on tracing. |
Turns off tracing. |
You can specify more than one option. However, if you do so, you must precede each option with a dash (-). You cannot combine options according to the UNIX convention of using a single dash followed by a list of options.
Information Builders | | <urn:uuid:1759d348-913a-4fdc-964f-4cabc3a07db9> | CC-MAIN-2024-38 | https://ecl.informationbuilders.com/focus/topic/shell_7706/FOCUS_OverviewOperEnv/source/05focooe40.htm | 2024-09-11T16:23:53Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651390.33/warc/CC-MAIN-20240911152031-20240911182031-00448.warc.gz | en | 0.796498 | 447 | 2.671875 | 3 |
The advent of the Internet of Things (IoT) has given rise to the prefix ‘smart’ for a whole variety of consumer products. With IoT also spilling over into the industrial world, the same can be said for industrial components and systems used in production facilities. While pneumatic components have been used in production facilities for a wide variety of applications, they were utilized for their simplicity, reliability, speed, and power, and were not known for being smart. However, with the rise of the Industrial Internet of things (IIoT) and the Industry 4.0 movement, smart pneumatics has assumed greater importance today. For starters, energy efficiency is a hot topic for manufacturers and end users alike, as they strive to reduce energy costs amid a global push to reduce the carbon footprint. To this end, manufacturers have realized that developing smart pneumatic components is necessary, not only to address the current demand for energy-efficient products, but also to remain competitive in the market in the future. While IIoT/Industry 4.0 is still in the nascent stage, it is expected to become more popular over the next 5–10 years, as sensor costs decrease and Ethernet penetration increases. Smart pneumatic products are also effective in slowing down migration toward electric equipment, which is a visible trend in some end-user industries, such as automotive, semiconductors, and packaging. The slower-than-anticipated rate of adoption of IIoT/Industry 4.0 solutions should not deter manufacturers, because demand for smart products could significantly increase in the near future, and not being able to offer smart products could eliminate a manufacturer from the competition altogether. Within the context of the pneumatic equipment market, some products that come under the purview of smart products include pneumatic valves, pneumatic actuators, and pneumatic grippers.
Compressed air is often considered the fourth utility in manufacturing plants owing to the ubiquitous presence of compressed air systems in production facilities across multiple industries. While air is considered free, compressing air for use in pneumatic systems is an expensive process. The US Department of Energy (DoE) estimates that nearly three-quarters of a compressor’s lifecycle costs is attributed to the electricity costs associated with compressing air. Additionally, pressure drops due to ineffective design or component failure or air leaks result in wastage of the compressed air. Wasted air results in increased energy costs, as the compressor is always running, sometimes at a higher power setting to compensate for the pressure drop. It is estimated that for every 1 psi increase in operating pressure, power consumption of the compressor increases by 0.5%. In this climate, reducing air consumption has direct benefits, as lower air consumption increases energy efficiency, and consequently reduces the end-user’s energy costs in a production facility.
Pneumatic valves are one of the most critical components in a pneumatic system and are used to control and direct the air flow in a pneumatic system. With IIoT and Industry 4.0 increasing in popularity, pneumatic valves have emerged as the focal point of the smart movement. A smart valve can be defined as any pneumatic valve that incorporates sensors and other electronics to provide operational feedback to the controller. This information is used by the controller to optimize valve operation and help smart valves reduce air consumption, and by consequence lower energy consumption for end users. Besides energy efficiency, smart valves also promise enhanced connectivity. Along with the popular fieldbus protocols, smart valves are increasingly becoming Ethernet compatible, which not only offers faster data transmission but enhanced diagnostic capabilities. By adding more sensors in the pneumatic circuit and integrating software with hardware, various types of data are exchanged between machines, enabling real-time condition monitoring. Condition monitoring provides useful feedback about valve functionality, and users can take action if a valve is not performing according to the manufacturer’s specifications. However, the real benefit of smart valves is that they enable predictive maintenance. Data analytics enables users to identify operational profiles that indicate possible component failure, enabling valve replacement at the next scheduled maintenance. Unscheduled maintenance is usually costly, as it is not easy to identify the failed component, especially if there are hundreds of valves in a production facility. Furthermore, production stoppages and manual inspections are a time consuming and costly exercise. Similarly, while preventive maintenance does not affect productivity as much as an unscheduled maintenance event does, it could result in the premature replacement of valves. Therefore, predictive maintenance provides end users with a useful middle-ground that allows them to predict when a valve could probably fail, thereby synchronizing the valve replacement with a scheduled maintenance event, with minimal interruption to production. Smart valves are also usually designed to be universal, allowing easy replacement of parts due to a common footprint. Hence, smart valves not only offer lower energy consumption, but also offer increased operational efficiency.
Pneumatic actuators are also critical components in a pneumatic system. A smart actuator, much like a smart valve, can be defined as any pneumatic actuator that uses sensors and other electronics to provide operational feedback to the controller. These can include useful data such as speed, force, end-of-travel, stroke length, and cycle time. Collection of this data enables condition monitoring to determine if an actuator is performing according to the manufacturer’s specifications. For example, condition monitoring systems alert the user when an actuator takes longer to actuate, or is travelling faster or slower indicating deteriorating performance. By using this information, actuator performance can be optimized, saving end users time and money. Additionally, as with the case of the smart valve, actuator failure can also be predicted in a similar manner. In addition to valves and actuators, another product that is attracting attention for being smart is the pneumatic gripper. Pneumatic grippers are end-of-arm tools and are available in several configurations, such as parallel grippers (2 or 3 finger), angular grippers, and vacuum grippers. Grippers are becoming more popular across multiple industries owing to the growth of robotics, and pick-and-place systems. Smart grippers offer increased energy efficiency, enhanced connectivity, as well as greater precision and safety. Grippers can carry items as light as a few hundred grams and as heavy as a few thousand kilograms, depending on the gripper’s configuration and the robot’s payload.
While IIoT/Industry 4.0 adoption is slow in the pneumatics market, the adoption of smart pneumatic products is slightly faster, on account of the quick return on investment offered by smart products. While end users are aware of IIoT/Industry 4.0, they are still not sure about how these concepts are applicable in their production environments. A significant portion of end users (mostly Tier II and Tier III companies) would prefer to wait until there is a clear consensus on industry standards, especially with respect to connectivity and cybersecurity. However, the advantages of smart products are more clearly understood by end users. In addition to the quick return on investment, smart products also offer a lower total cost of ownership (TCO), increased productivity, and easier maintenance. Over the last few years, there has been an increasing threat to pneumatic equipment from electric technologies, as the latter involves lower TCO. However, pneumatic equipment suppliers have shown that TCO can be significantly lowered by using smart pneumatic products. With the decreasing cost of sensors and other peripheral equipment, Frost & Sullivan anticipates that smart pneumatic products will help slow down the migration away from pneumatic equipment towards electric equipment. | <urn:uuid:7aba6e10-d1fc-4f8a-a481-070d746e3d6e> | CC-MAIN-2024-38 | https://www.frost.com/growth-opportunity-news/smart-pneumatics-slowing-down-end-user-electrification/ | 2024-09-11T16:06:39Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651390.33/warc/CC-MAIN-20240911152031-20240911182031-00448.warc.gz | en | 0.947498 | 1,560 | 2.703125 | 3 |
Table of contents
In the ever-evolving landscape of the digital age, information search is paramount to navigating the vast sea of knowledge that engulfs the internet. With the advent of Generative Pre-trained Transformers (GPT), the way we seek out information is being revolutionized. This innovation is not just an incremental upgrade; it's a seismic shift in the very fabric of online inquiry. As we stand on the brink of this new era, understanding how GPT is shaping the future of information search becomes imperative for anyone looking to stay ahead of the curve. Whether you're a researcher, a student, or simply a curious mind, the ramifications of this technology will touch every aspect of your online experience. This piece invites you to delve into the intricacies of GPT and its role in revolutionizing information search. Embrace the journey of discovery as we explore the transformative capabilities of this technology and its potential to redefine our approach to finding information online.
The foundations of GPT and information retrieval
The inception of Generative Pre-trained Transformer (GPT) models has heralded a new era in the domain of online information retrieval. At the heart of GPT lies an intricate blend of machine learning and natural language processing, technologies that empower these systems to understand and generate human-like text. Unlike traditional search algorithms that rely on keyword matching and static databases, GPT utilizes transformer models to interpret the nuances of language in a context-rich manner. This approach allows for a more intuitive interaction between users and information systems, where queries receive responses that resemble human conversation.
The significance of machine learning within GPT cannot be overstated; it enables the model to learn from vast amounts of data without explicit programming. As a result, GPT can process and predict language patterns with remarkable accuracy. Natural language processing further enhances GPT's capabilities by providing the means to comprehend and generate coherent and contextually relevant text. This synergy between machine learning and natural language processing is what sets GPT apart from previous information retrieval methods. By understanding the GPT basics, we gain insight into a pivotal innovation capable of transforming how we search for and interact with online information.
Advantages of GPT for search experiences
Generative Pre-trained Transformer, commonly known as GPT, has revolutionized the realm of online searches by injecting advanced AI capabilities into the process. One of the primary benefits that GPT offers is an improvement in search accuracy. By utilizing deep learning algorithms, GPT understands the nuances of human language, enabling it to deliver more precise responses to queries. Additionally, GPT's contextual understanding is a game-changer for online search experiences, as it analyzes the intent behind a user's question to provide relevant results that go beyond keyword matching. This is known as semantic search, which focuses on deciphering the meaning and context of search phrases.
Moreover, GPT has made strides in the realm of conversational AI, allowing for interactions that closely mimic human conversation. This level of engagement is not just impressive but also functional, as it fosters a more natural and efficient user interaction. Users can now expect a two-way dialogue with the search system, making the retrieval of information feel less robotic and more like interacting with a knowledgeable assistant. As a specialist in conversational AI and user experience design, it is evident that GPT's ability to understand and generate human-like responses significantly elevates the search experience, making it more intuitive and user-friendly. In a world where time is of the essence, the introduction of GPT in online searches is indeed a substantial advancement toward smarter and faster access to information.
The Impact of GPT on Content Creation and Consumption
The introduction of Generative Pre-trained Transformers (GPT) has significantly altered the information landscape, bringing about a monumental shift not only in how we seek out information but also in the mechanisms of content creation and consumption. These advanced content generation algorithms have far-reaching implications for content creators, necessitating a reevaluation of content strategy to stay relevant in a rapidly evolving digital ecosystem. In the wake of these changes, creators must now consider how GPT can be leveraged to produce a richer and more diverse array of content, thus enhancing the user experience and engagement.
From a content strategy perspective, the utilization of GPT facilitates the generation of material that is not only high-quality but tailored to the nuanced demands of various audiences. Content consumption patterns are shifting as users become accustomed to receiving instant, relevant responses to their queries. The inherent capacity of GPT to understand and generate human-like text has set a new standard for personalized content. As a result, creators are now tasked with designing strategies that integrate these algorithms to maintain a competitive edge.
This transformative effect extends to the breadth and depth of content that can be produced. With GPT, the potential for diverse content creation is exponentially increased, allowing for the exploration of topics and stories that may have previously been inaccessible due to resource constraints. For content consumers, this leads to an enriched and more engaging information experience, while creators can tap into previously untapped market segments or niches, propelling the industry forward in both scope and creativity.
Challenges and considerations with GPT-driven search
With the advent of Generative Pre-trained Transformer (GPT) technologies in search engines, a myriad of challenges and ethical considerations has surfaced. Among the primary concerns is data privacy. As GPT models require vast datasets to operate effectively, the collection and use of personal data pose significant risks. Ensuring that user information is handled with the utmost care and in compliance with data protection laws is paramount. In parallel, the surge of misinformation remains a persistent threat. These advanced algorithms can inadvertently generate or propagate false information, necessitating robust mechanisms to verify and fact-check content before it reaches the user.
Furthermore, the notion of human oversight cannot be overstressed. While GPT can enhance the efficiency and accuracy of search results, it is imperative to retain human judgment to address nuances and context that the algorithm may overlook. This is closely linked with ethical considerations, where the moral implications of algorithmic decisions must be evaluated to prevent biases and unfair outcomes. Additionally, search engine challenges include the need for algorithmic transparency, where stakeholders can understand how and why specific search results are generated. This transparency is vital for trust and accountability in search technologies.
As we navigate these complex challenges, it is essential to balance innovation with responsibility, ensuring that GPT-driven search engines serve the public interest without compromising ethical standards. Among these, helpful hints for safe internet practices and information literacy could be integral in equipping users to discern the reliability of online content effectively.
The future and evolution of GPT in information search
Peering into the horizon of search technology evolution, the trajectory of Generative Pre-trained Transformer (GPT) development paints a transformative picture for the online search landscape. With ongoing research pushing the boundaries of artificial intelligence, these advancements promise to redefine the very fabric of how we access and interact with information. The future advancements in GPT may well lead to a paradigm shift wherein search engines not only retrieve data but understand and anticipate the complex needs of users. This progression towards more intuitive and insightful search capabilities is driven by a deeper integration of natural language processing and machine learning. As algorithms become more advanced, the potential for GPT to contextually analyze vast amounts of data and provide concise, accurate information in real-time becomes increasingly tangible. The foresight of predictive modeling suggests that the seamless interaction with digital information is just over the horizon, marking a significant leap forward in our capacity to navigate the ever-expanding digital universe. | <urn:uuid:251099dd-6725-4c28-81c6-56c3fa2eda17> | CC-MAIN-2024-38 | https://amarketresearchreport.com/understanding-gpt-the-future-of-online-information-search | 2024-09-12T21:49:43Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651498.46/warc/CC-MAIN-20240912210501-20240913000501-00348.warc.gz | en | 0.906562 | 1,548 | 3 | 3 |
January 20, 2021
With the release of 5G wireless, organizations are looking for ways to leverage the technology to improve their network connectivity. 5G is the fifth generation of wireless technology, which greatly improves the speed and performance of wireless technology. Because of the constant increase in connected medical devices, many wireless networks are left with an enormous amount of bandwidth strain. With its improved support, 5G could drastically improve network connectivity in the healthcare industry.
The Benefits of 5G in Healthcare
Deploying a 5G network in the healthcare industry will vastly improve network connectivity for healthcare organizations and hospital facilities by eliminating dead zones within hospitals and freeing up bandwidth for connected medical devices. Obviously, these medical devices are being used to keep people alive and monitor their vitals, giving doctors a real-time snapshot of their patients’ health at any given moment. In addition to facilitating an improved network connection for devices, 5G will also help to improve communications within the healthcare facilities. The building materials used to construct hospitals do not encourage connectivity and communication within the facilities – concrete, steel, energy efficient glass – leading to dead zones and dropped calls throughout the facility, especially basements, closets, and stairwells.
IoT Devices for Healthcare Environments
Facilities that use robotics, haptic internet, virtual reality, and IoT devices may benefit the most from 5G technology. Healthcare organizations are eager to adapt IoT devices for their systems to save money and keep patients out of hospitals. IoT devices are much more than connected medical devices; they provide the potential of an ecosystem that improves operational efficiency and patient care. Further, as IoT devices are used to stretch medical professional’s reach beyond four wall, robust, reliable connectivity is needed within the facility to receive the critical information. From providing routine health information on outpatients, to enabling first-responders to use IoT-enabled devices to transmit information instantaneously when onsite in emergency situations, 5G opens the door wide open to support IoT devices and drive further hospital efficiencies when it matters most.
Enable 5G at your Healthcare Facility Today
Connectivity Wireless can provide a customized solution for deploying a 5G network within your healthcare facility. We are committed to connecting patients and doctors through innovative technology that will change the way healthcare operates, completely optimizing your performance. Connectivity is a necessary utility, and healthcare organizations need to be equipped with the latest technologies to support the latest devices and provide the highest degree of care. Contact our team today to learn how 5G technology can help your organization. | <urn:uuid:143e6adc-1361-4b5e-9cec-5519249c205e> | CC-MAIN-2024-38 | https://connectivitywireless.com/5g-and-healthcare/ | 2024-09-12T21:53:25Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651498.46/warc/CC-MAIN-20240912210501-20240913000501-00348.warc.gz | en | 0.943356 | 512 | 2.65625 | 3 |
Access lists are filters used by FortiGate unit RIP and OSPF routing. An access list provides a list of IP addresses and the action to take for them — essentially an access list makes it easy to group addresses that will be treated the same into the same group, independent of their subnets or other matching qualities. You add a rule for each address or subnet that you want to include, specifying the action to take for it. For example if you wanted all traffic from one department to be routed a particular way, even in different buildings, you can add all the addresses to an access list and then handle that list all at once.
Each rule in an access list consists of a prefix (IP address and netmask), the action to take for this prefix (permit or deny), and whether to match the prefix exactly or to match the prefix and any more specific prefix.
The FortiGate unit attempts to match a packet against the rules in an access list starting at the top of the list. If it finds a match for the prefix, it takes the action specified for that prefix. If no match is found the default action is deny.
Access lists greatly speed up configuration and network management. When there is a problem, you can check each list instead of individual addresses. Also its easier to troubleshoot since if all addresses on one list have problems, it eliminates many possible causes right away.
If you are using the RIPng or OSPF+ IPv6 protocols you will need to use access-list6, the IPv6 version of access list. The only difference is that access-list6 uses IPv6 addresses.
For example, if you want to create an access list called test_list that only allows an exact match of
10.10.10.10 and 22.214.171.124, enter the command:
config router access-list edit test_list
config rule edit 1
set prefix 10.10.10.10 255.255.255.255 set action allow
set exact-match enable next
set prefix 126.96.36.199 255.255.255.255 set action allow
set exact-match enable end
Another example is if you want to deny ranges of addresses in IPv6 that start with the IPv6 equivalents of
10.10.10.10 and 188.8.131.52, enter the command access-list6 as follows:
config router access-list6 edit test_list_ip6
config rule edit 1
set prefix6 2002:A0A:A0A:0:0:0:0:0:/48 set action deny
next edit 2
set prefix6 2002:B0B:B0B:0:0:0:0:0/48 set action deny
To use an access_list, you must call it from a routing protocol such as RIP. The following example uses the access_list from the earlier example called test_list to match routes coming in on the port1 interface. When there is a match, it will add 3 to the hop count metric for those routes to artificially increase . Enter the following command:
config router rip config offset-list
set access-list test_list set direction in
set interface port1
set offset 3
set status enable end
If you are setting a prefix of 184.108.40.206, use the format 220.127.116.11/1. The default route, 0.0.0.0/0 can not be exactly matched with an access-list. A prefix-list must be used for this purpose
How RIP works
As one of the original modern dynamic routing protocols, RIP is straightforward. Its routing algorithm is not complex, there are some options to allow fine tuning, and it’s relatively simple to configure RIP on FortiGate units.
From RFC 1058:
Distance vector algorithms are based on the exchange of only a small amount of information. Each entity (gateway or host) that participates in the routing protocol is assumed to keep information about all of the destinations within the system. Generally, information about all entities connected to one network is summarized by a single entry, which describes the route to all destinations on that network.
This section includes:
- RIP versus static routing
- RIP metric — hop count
- The Bellman–Ford routing algorithm l Passive versus active RIP interfaces l RIP packet structure | <urn:uuid:5904d0ff-2783-4f1d-aba4-c5e24b4d5cef> | CC-MAIN-2024-38 | https://www.fortinetguru.com/2016/06/routing-information-protocol-rip/4/ | 2024-09-14T05:42:46Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651548.18/warc/CC-MAIN-20240914025441-20240914055441-00248.warc.gz | en | 0.836149 | 913 | 2.875 | 3 |
Immersive learning has come into the picture since the time AR (Augmented Reality) and VR (Virtual Reality) were introduced to the world. More and more businesses are adopting immersive learning environments for their L&D training programs. This learning approach helps companies to demonstrate real-life challenges and opportunities to their employees so they can be better prepared for every situation. Immersive learning can also be used as collaborative learning in virtual environments for businesses with remote team setups. Let’s discuss how immersive virtual learning environments can foster teamwork and collaboration or communication skills among your teammates.
In the not-so-distant past, corporate training often meant hours of tedious slide presentations or e-learning modules that felt disconnected from the day-to-day work reality. Well, those days are fading away as immersive learning takes center stage. VR and AR create an Immersive Learning experience that brings a sense of presence and engagement, making learning an experience rather than a task.
Before we discuss the collaborative aspect, let’s understand immersive learning. It’s not just about cool gadgets or the latest tech trends. Immersive learning is an experience that engages multiple scenes and creates an environment that feels real. VR and AR simulations transport employees into scenarios mirroring their everyday work challenges. This kind of learning goes beyond textbook knowledge and allows individuals to learn by working on real-life projects. Employees can gain a deeper understanding of concepts. But how does it help in fostering teamwork?
One of the most significant challenges in traditional corporate training is the physical and geographical constraints that limit face-to-face interactions. Immersive learning erases these boundaries, creating virtual spaces where team members can come together regardless of their location.
Employees from different locations can gather to solve a complex problem. They can interact with each other, share their unique ideas, and collectively work together on projects as if they were in the same room. This collaborative approach promotes global teamwork and productivity and allows individuals to experience different perspectives and strategies.
There are many advantages of immersive learning in cultivating teamwork and collaboration skills. Let’s discuss some of these advantages:
Immersive learning brings authenticity to team interactions. Avatars in a shared virtual space allow team members to communicate in a more lifelike manner. This bridges the gap between physical separation. Facial expressions, gestures, and body language create a more realistic and engaging experience. Team members can build a strong and authentic connection among them even when they are physically miles apart.
Traditional communication tools often limit interactions to voice and text. On the other hand, immersive learning allows gestures and expressions to become integral parts of communication. In the virtual world, team members can use non-verbal indications to converse with each other. This approach makes conversations richer and deeper in nature. Beyond typed messages or muted microphones, immersive learning creates a more dynamic and expressive form of collaboration.
In an increasingly globalized workforce, teams are often spread across different time zones and continents. Immersive learning breaks the geographical barriers with its collaborative learning experience regardless of the team’s physical location. This advantage helps overcome time differences and creates a sense of community and shared purpose among diverse team members who may never meet face-to-face.
One of the most significant advantages of immersive learning is that it provides hands-on experiences. In collaborative virtual environments, teams can work on real-world challenges that need to be solved collectively. This approach helps build strong team bonding by involving communication, coordination, and collective decision-making. Employees can apply the knowledge gained from their learning in a practical and collaborative setting.
The immersive nature of virtual spaces captures attention in ways traditional training methods may struggle to achieve. When employees are actively engaged in scenarios that require collaboration, the retention of information is significantly higher. This increased engagement creates a more profound understanding of teamwork principles.
Collaborative learning in virtual spaces enables immediate feedback and iteration. Instead of waiting for post-training assessments, teams receive instant feedback on their actions and decisions within the simulation. It allows for continuous improvements and promotes a culture of learning from both successes and failures. This advanced feedback feature of immersive learning builds collaboration skills by highlighting the importance of adaptability and learning from shared experiences.
Immersive learning offers scalable solutions for training large teams consistently. Whether a company has 50 employees or 5000, virtual environments provide a standardized learning experience for everyone. This means all team members can receive the same training regardless of their role, level of experience, or location. It creates a common ground for collaboration as everyone is equipped with a shared set of skills and experiences.
Virtual spaces provide an opportunity for inclusive learning experiences. Businesses can tailor their immersive learning platforms to accommodate different learning styles, languages, and cultural backgrounds. This customization creates an inclusive environment where everyone can feel comfortable. By acknowledging and addressing individual differences, immersive learning contributes to building a collaborative culture that values diversity.
Let’s take a closer look at how immersive learning is making waves with a few industry-specific examples.
In a virtual emergency room simulation, healthcare professionals can practice teamwork, communication, and decision-making in high-pressure scenarios. This improves their individual skills and strengthens the overall success of the medical team.
Immersive learning allows sales teams to engage in simulated client meetings, refining their pitch, objection-handling, and negotiation skills. Marketing teams can collaborate on virtual campaigns and experience the real-time impact of their strategies.
For software development teams, virtual environments provide a space to code, troubleshoot, and innovate collaboratively. This shared digital workspace quickens the development process and encourages knowledge sharing among team members.
Just as with any other new information technology, immersive learning also comes with its fair share of challenges. Let’s look into these challenges and their solutions.
- Not everyone has the latest gadgets, and technical hiccups like software glitches or slow networks are bound to happen. Organizations need to ensure that everyone has access to the basics and offer alternatives for those without high-tech gear. Keep it user-friendly to avoid technical glitches.
- Virtual collaboration can lack the personal touch of face-to-face interaction. It might feel a bit cold and distant. Encourage regular team-building activities, even in the virtual world. Foster an open environment where people feel comfortable sharing ideas and emotions.
- Sharing sensitive information in virtual spaces raises security and privacy concerns. No one wants a data breach on their hands. Clear guidelines are the solution in this case of data security. Regularly update participants on privacy measures and ensure your virtual platform has robust security features.
- Implementing new tech can be expensive, especially for smaller businesses. If high-tech gear is a stretch, explore cost-effective options. Pilot programs on smaller scales or consider phased implementations to manage costs without compromising the benefits.
- Traditional metrics might fall short in measuring the success of virtual collaboration. Get creative with assessments; consider peer reviews, real-world simulations, or interactive activities to measure how well teams are really working together.
In today’s corporate world, more and more businesses are joining the virtual bandwagon. Even employees prefer working remotely while being comfortable in their preferred spaces. However, communication and collaboration have become essential for businesses to ensure the team is well-connected even if they are not physically present at the office or available face-to-face. Immersive learning helps in such cases to build a strong bond between the team members and foster collaboration among them. | <urn:uuid:1435cd82-fc5a-41a0-ba76-d4aabf43698c> | CC-MAIN-2024-38 | https://coruzant.com/business/immersive-learning-in-fostering-teamwork-and-collaboration-skills/ | 2024-09-17T17:48:07Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651829.57/warc/CC-MAIN-20240917172631-20240917202631-00848.warc.gz | en | 0.936059 | 1,512 | 2.921875 | 3 |
In this lesson, we’ll take a look at EIGRP (Enhanced Interior Gateway Routing Protocol), which is Cisco’s routing protocol. If you are unfamiliar with distance vector and RIP, I highly recommend reading my Introduction to RIP first before continuing.
EIGRP stands for Enhanced Interior Gateway Routing Protocol and is a routing protocol created by Cisco. Originally, it was only available on Cisco hardware but for a few years, it’s now an open standard. EIGRP is called a hybrid or advanced distance vector protocol, and most of the rules that apply to RIP also apply here:
- Split Horizon
- Route Poisoning
- Poison Reverse
EIGRP routers will start sending hello packets to other routers just like OSPF does, if you send hello packets and you receive them you will become neighbors. EIGRP neighbors will exchange routing information which will be saved in the topology table. The best path from the topology table will be copied into the routing table:
Selecting the best path with EIGRP works a bit differently than other routing protocols, so let’s see it in action:
We have three routers named R1, R2, and R3. We are going to calculate the best path to the destination, which is behind R3.
EIGRP uses a rich set of metrics, namely bandwidth, delay, load, and reliability, which we will cover later. These values will be put into a formula, and each link will be assigned a metric. The lower these metrics, the better.
In the picture above I have assigned some values on the interfaces, if you would look at a real EIGRP router you’ll see the numbers are very high and a bit annoying to work with. R3 will advertise to R2 its metric towards the destination:
Basically, R3 is saying to R2: “It costs me 5 to get there”. This is called the advertised distance. R2 has a topology table, and in this topology table it will save this metric, the advertised distance to reach this destination is 5.
We are not done yet since there is something else that R2 will save in its topology table. We know the advertised distance is five since this is what R3 told us. We also know the metric of the link between R2 and R3 since this is directly connected. R2 now knows the metric for the total path to the destination, this total path is called the feasible distance, and it will be saved in the topology table:
You have now learned two important concepts of EIGRP. The advertised distance, your neighbor tells you how far it is for him to reach the destination, and the feasible distance which is your total distance to get to the destination.
Let’s continue! R2 is sending its feasible distance towards R1, which is 15. R1 will save this information in the topology table as the advertised distance. R2 is “telling” R1 the distance is 15: | <urn:uuid:58a47217-4bc7-47a6-8bd3-a734d5fe8a49> | CC-MAIN-2024-38 | https://networklessons.com/cisco/ccna-routing-switching-icnd2-200-105/introduction-to-eigrp | 2024-09-17T18:06:08Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651829.57/warc/CC-MAIN-20240917172631-20240917202631-00848.warc.gz | en | 0.957803 | 630 | 3.109375 | 3 |
API security for developers is crucial in today’s interconnected world. Ensuring that your APIs are secure from attacks can protect sensitive data and maintain the integrity of your applications.
Here are quick tips for getting the most out of a voice API for developers:
- Use Secure Authentication: Implement OAuth2 or JSON web tokens (JWTs).
- Rate Limiting: Protect against brute-force attacks by limiting request rates.
- Encrypt Data: Always use HTTPS for data transit.
- Validate Input: Avoid injection attacks by sanitizing user inputs.
- Monitor and Audit: Regularly check your APIs for any vulnerabilities.
APIs are the backbone of modern apps, allowing different systems to communicate and share data seamlessly. But as APIs become more integral to software architecture, their security becomes vital. Poorly secured APIs can lead to severe security breaches, exposing sensitive data and compromising systems.
Your backend framework must follow best practices in API security to build robust applications. Proper security improves your application’s reliability, making it trustworthy for users and businesses alike.
Understanding API Security
API security is crucial for developers and IT leaders, especially in the field of Communications Platform as a Service (CPaaS). It ensures that APIs are protected from attacks, safeguarding sensitive data and maintaining the integrity of backend systems.
API Security Definition
A voice API built for developers is only as good as its security features and developer knowledge. API security involves protecting APIs from malicious attacks and misuse. It encompasses a range of practices to ensure that only authorized users and applications can interact with the API, and that the data exchanged is secure.
Sensitive Data Protection
APIs often handle sensitive data like user credentials, financial information, and personal details. Protecting this data is paramount. Encryption, such as Transport Layer Security (TLS), ensures data is encrypted during transmission, preventing eavesdropping and tampering.
A robust backend framework is essential for effective API security. It should incorporate:
- Secure Authentication and Authorization: Use OAuth2 or JSON Web Tokens (JWTs) to ensure only authorized users can access the API.
- Rate Limiting: Prevent abuse and denial-of-service (DoS) attacks by limiting the number of requests a user can make.
- Input Validation and Sanitization: Always validate and sanitize user inputs to prevent injection attacks.
- Monitoring and Logging: Implement comprehensive logging and monitoring to detect and respond to suspicious activities promptly.
Example: According to Noname Security, 76% of organizations encountered an API-related security vulnerability in 2022. This underscores the importance of robust API security measures.
Implementing these strategies can protect your APIs from common vulnerabilities and ensure the secure exchange of data across your applications.
Common API Security Vulnerabilities
APIs are the backbone of modern applications, but they also have a set of vulnerabilities. Understanding these common vulnerabilities can help you better secure your APIs.
Injection attacks occur when untrusted data is sent to an interpreter as part of a command or query. This can lead to unauthorized data access or manipulation.
Example: SQL injection is a common type of injection attack. An attacker can use it to execute arbitrary SQL code and gain access to sensitive data.
Prevention: Use prepared statements with bind variables and validate all user inputs.
Broken Authentication and Session Management
Authentication verifies the identity of a user, while session management maintains the user’s state within an application. Flaws in these areas can allow attackers to impersonate users.
Example: Weak passwords and predictable session IDs can be exploited through brute force attacks, allowing unauthorized access.
Prevention: Implement strong password policies, use multi-factor authentication, and ensure session IDs are random and expire properly.
Cross-Site Scripting (XSS)
XSS attacks involve injecting malicious scripts into web pages viewed by other users. These scripts can steal session tokens or perform unauthorized actions.
Example: An attacker can inject a script into a comment section, which then executes in the browser of anyone viewing that comment.
Prevention: Sanitize and validate user inputs, and use Content Security Policies (CSPs) to restrict the sources of executable scripts.
Cross-Site Request Forgery (CSRF)
CSRF attacks trick users into taking actions they did not intend to take by sending unauthorized requests from their browsers.
Example: An attacker can create a malicious link that, when clicked, changes the victim’s account settings without their knowledge.
Prevention: Use CSRF tokens to validate requests and ensure they originate from the intended user.
Insufficient Encryption and Transport Layer Protection
Sensitive data transmitted over APIs needs to be encrypted to prevent interception and tampering.
Example: If an API does not use HTTPS, an attacker can intercept and read the data being transmitted.
Prevention: Always use HTTPS and strong encryption algorithms to protect data in transit.
Understanding these vulnerabilities is the first step in securing your APIs. In the next section, we’ll dive deeper into API Security Best Practices, exploring secure authentication methods, rate limiting, and more.
API Security Best Practices
Use Secure Authentication and Authorization Methods
Authentication and authorization are the first lines of defense for securing your APIs. Implementing protocols like OAuth2 and using JSON Web Tokens (JWTs) are essential.
- OAuth2: This open standard helps third-party applications access user data without exposing user credentials. Instead, users grant access through tokens. This is crucial for maintaining security and privacy.
- JWTs: These tokens securely transmit information between parties. They include claims that provide essential details about the user and their permissions. JWTs are compact, secure, and easy to verify.
Implement Rate Limiting
Rate limiting is critical for preventing API abuse and brute-force attacks. By limiting the number of requests a user or application can make within a specific time frame, you can protect your API from being overwhelmed.
- Brute-force attacks: Attackers often try multiple combinations to guess credentials. Rate limiting can thwart these attempts by restricting the number of login attempts.
- API abuse: Excessive requests can degrade performance and availability. Rate limiting ensures fair usage and protects your resources.
Encrypt Requests and Responses
Encrypting data in transit is non-negotiable for protecting sensitive information. Always use HTTPS and Transport Layer Security (TLS).
- HTTPS: This protocol ensures that data transmitted between the client and server is encrypted, preventing interception and tampering.
- TLS encryption: An advanced form of encryption that secures data during transmission. It’s essential for protecting sensitive data like passwords and credit card information.
Validate and Sanitize User Input
Proper input validation and sanitization are vital for preventing common security vulnerabilities, such as SQL injection and Cross-Site Scripting (XSS).
- Input validation: Ensure that data meets specific criteria before processing. This helps prevent malicious data from entering your system.
- Input sanitization: Remove any potentially dangerous content from user input. This is crucial for preventing SQL injections and XSS attacks.
Monitor and Audit APIs
Regular API monitoring and logging are essential for identifying and mitigating security threats. Implementing security assessments can help keep your APIs secure.
- API monitoring: Keep an eye on API traffic to detect unusual patterns or potential threats.
- Logging: Maintain logs of all API interactions. This helps in forensic analysis in case of a security breach.
- Security assessments: Regularly test your APIs for vulnerabilities using tools that can scan for issues like SQL injection and XSS. This proactive approach helps identify and resolve security gaps before they can be exploited.
By following these best practices, you can significantly improve the security of your APIs. In the next section, we’ll explore Key Strategies for API Security for Developers, including using gateways and centralized OAuth servers.
API Security for Developers: Key Strategies
Always Use a Gateway
An API gateway is your first line of defense. It centralizes traffic management and applies security features to every request. This includes rate limiting, blocking malicious clients, and logging activities. Without a gateway, you’d have to manually secure each endpoint, which is time-consuming and error-prone.
Benefits of using an API gateway:
- Rate Limiting: Prevents brute-force attacks and API abuse by controlling the number of requests a client can make.
- Logging: Keeps track of all API interactions, aiding in forensic analysis if a breach occurs.
- Blocking Malicious Clients: Identifies and blocks clients that exhibit suspicious behavior.
Use a Central OAuth Server
A centralized OAuth server should handle all token issuance. This server manages the complex processes of client authentication, user authentication, and token signing. By centralizing these tasks, you avoid the pitfalls of having multiple entities issuing tokens, which can lead to security lapses.
Why use a centralized OAuth server:
- Efficient Token Management: Simplifies the process of issuing and managing tokens.
- Improved Security: Reduces the risk of token-related vulnerabilities by centralizing control.
Implement Zero-Trust Security
A Zero-trust approach shifts the focus from network location to specific users, assets, and resources. This means always authenticating users and applications, whether inside or outside the network perimeter.
Key elements of Zero-trust:
- HTTPS and TLS Encryption: Ensures all data in transit is encrypted.
- JWT Validation: Ensures tokens are valid and haven’t been tampered with.
- Deny Access by Default: Only grant the minimum permissions necessary for a user or application to perform its tasks.
Protect All APIs
All APIs, whether internal or external, need robust security measures. Relying on security by obscurity—hiding APIs in hopes they won’t be found—is not enough.
Protecting all APIs involves:
- Internal APIs: Treat them with the same level of security as public-facing APIs. Internal threats are just as real as external ones.
- External APIs: Ensure they’re secured with strong authentication and encryption methods.
Implementing these strategies can significantly bolster your API security. Next, we’ll explore API Security for Different API Architectures, including SOAP, REST, and GraphQL APIs.
API Security for Different API Architectures
SOAP API Security
SOAP (Simple Object Access Protocol) is a highly structured protocol used in many enterprise environments. It relies on XML for message formatting and supports a range of security features.
Message-Level Security: SOAP APIs offer message-level security through standards like WS-Security. This ensures that each message is encrypted and signed, providing end-to-end security.
WS-ReliableMessaging: SOAP also includes WS-ReliableMessaging, which provides built-in error handling. This means that messages are guaranteed to be delivered, even in the case of network issues.
SOAP’s built-in security features make it a robust choice for applications that handle sensitive data, such as financial transactions or healthcare records.
REST API Security
REST (Representational State Transfer) is a simpler, more flexible approach compared to SOAP. It uses HTTP/S as the transport protocol and typically employs JSON for data transfer.
API Gateway: One of the best practices for securing REST APIs is to deploy them behind an API gateway. This acts as a proxy and handles various security tasks like rate limiting, authentication, and logging.
HTTPS and TLS Encryption: Always use HTTPS to encrypt data in transit. TLS encryption ensures that the data exchanged between the client and server is secure.
While REST APIs don’t have built-in security features like SOAP, they can be made secure through careful implementation and the use of an API gateway.
GraphQL API Security
GraphQL is a query language that allows clients to request specific data structures. This flexibility can lead to complex queries that the server must handle efficiently.
Query Depth and Complexity: To prevent abuse, set a maximum query depth and query complexity. This ensures that clients can’t overload the server with deeply nested or computationally expensive queries.
Query Timeout: Implementing a timeout for queries can help defend against large, resource-intensive requests. If a query takes too long to process, the server can terminate it.
Throttling: Use throttling to limit the number of queries a client can make in a given time period. This helps protect against denial-of-service (DoS) attacks and ensures fair usage.
By adopting these strategies, you can secure your GraphQL APIs against various threats.
Securing your APIs is crucial. As we’ve discussed, APIs are gateways to sensitive data and backend systems. Ensuring their security is not just about protecting data but also maintaining the reliability and integrity of your applications.
It’s critical to invest in a robust solution with API security within the CPaaS environment. Using the APIs, developers can easily integrate voice and SMS functionalities into their applications while ensuring robust security measures are in place.
Why is this important?
- Protecting Sensitive Data: APIs often handle sensitive information like personal data and financial details. A breach can lead to severe consequences, including data theft and financial loss.
- Business Continuity: Secure APIs ensure uninterrupted service. In uncertain times, businesses need resilient systems to maintain operations and customer trust. Secure APIs are a backbone of this resilience.
- Developer Tools: Developers require specific tools that help them identify and address potential vulnerabilities. These tools can help developers ensure compliance with security standards and protect against unauthorized access.
- Use a Central OAuth Server: Centralized token issuance and claims assertion provide a stronger security foundation.
- Implement Zero-Trust Security: Always validate JWTs and deny access by default to ensure only authorized requests are processed.
- Protect All APIs: Treat internal APIs with the same level of security as public-facing ones to prevent internal threats.
By following these best practices and leveraging the right CPaaS, you can effectively safeguard your APIs and ensure your applications remain secure and reliable. Get started today. | <urn:uuid:f99f5fe7-526d-4f7d-904d-10d39f9d43c8> | CC-MAIN-2024-38 | https://flowroute.com/blog/safeguarding-voice-applications-api-security-for-developers/ | 2024-09-20T06:18:11Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652138.47/warc/CC-MAIN-20240920054402-20240920084402-00648.warc.gz | en | 0.891759 | 2,934 | 2.703125 | 3 |
In today’s data-driven world, organizations are increasingly realizing the importance of effectively managing their data assets. Data governance frameworks have emerged as critical tools for ensuring data quality, accuracy, and compliance. This article explores the ways in which it contributes to business success, providing valuable insights into its implementation and best practices.
Before delving deeper into this topic, you might like to read A Brief Guide To What Is Data Governance And Why Is It Important.
The Role of Data Governance in Business Success
In the modern business landscape, data plays a pivotal role in driving success. Organizations rely on data to make informed decisions, identify market trends, and gain a competitive edge. However, without proper governance, data can become unreliable, inconsistent, and fragmented, hindering business growth. A robust data governance framework establishes the necessary structure, policies, and processes to effectively manage data, ensuring its integrity, availability, and usability.
Key benefits of implementing it in organizations include:
Improved Data Quality
A data governance framework enables organizations to establish data standards, data cleansing processes, and data validation mechanisms. By maintaining high-quality data, businesses can make reliable decisions, minimize errors, and build trust with customers and stakeholders.
Enhanced Data-driven Decision Making
Data governance frameworks facilitate access to accurate, timely, and relevant data. With reliable information at their fingertips, decision-makers can base their strategies on insights derived from trusted data sources, enabling better decision-making and driving business success.
Learning about Data Integration Solutions: Benefits And Key Features might also be something that interests you.
Regulatory Compliance and Risk Mitigation
In an era of strict data protection regulations, organizations must comply with various laws and regulations, such as GDPR or CCPA. Data governance frameworks provide the necessary controls and processes to ensure compliance, reducing the risk of legal and reputational repercussions.
Streamlined Business Processes and Efficiency
By defining data ownership, data lifecycle management, and data integration processes, organizations can streamline their operations and improve efficiency. Data governance frameworks enable data to flow seamlessly across departments, eliminating silos and fostering collaboration.
Data Collaboration and Knowledge Sharing
An effective data governance framework promotes data collaboration, enabling cross-functional teams to access and share data securely. This enhances knowledge sharing, encourages innovation, and facilitates the development of data-driven solutions.
One of the best ways to ensure data safety is to have a continuous control monitoring system to protect your data. And if that is not what you are looking f
Establishing a Data Governance Framework
Understanding the Components of a Data Governance Framework
A comprehensive data governance framework comprises policies, procedures, standards, roles, and responsibilities. It defines how data is managed, protected, and used within the organization.
Assessing the Current State of Data Management
Organizations should conduct an assessment to identify existing data management practices, strengths, and weaknesses. This evaluation helps identify gaps and areas for improvement.
Identifying Business Objectives and Aligning Data Governance Goals
Data governance initiatives should align with the organization’s strategic goals and objectives. By understanding business needs, organizations can tailor their data governance framework to support specific outcomes.
Building a Data Governance Team
Establishing a dedicated data governance team is crucial for successful implementation. This team should include representatives from various departments and possess the necessary expertise to drive the data governance initiative forward.
You might also like to read about Data Governance Vs Data Management: The Key Differences.
Driving Business Value
Enhancing Data Quality and Accuracy
By implementing data standards, data cleansing processes, and data validation mechanisms, organizations can improve the quality and accuracy of their data. This ensures reliable insights and informed decision-making.
Facilitating Data-driven Decision Making
A robust data governance framework ensures that decision-makers have access to accurate, reliable, and timely data. This empowers them to make informed decisions based on trustworthy information, resulting in better business outcomes.
Ensuring Regulatory Compliance and Mitigating Risks
Data governance frameworks establish processes and controls to ensure compliance with data protection regulations. By adhering to these regulations, organizations mitigate legal and reputational risks.
Streamlining Business Processes and Improving Efficiency
Data governance frameworks promote data integration, harmonization, and consistency. This streamlines business processes, eliminates redundant efforts, and improves overall operational efficiency.
Enabling Data Collaboration and Knowledge Sharing
By fostering a culture of data collaboration, organizations can unlock the full potential of their data. Data governance frameworks facilitate secure data sharing, enabling cross-functional teams to collaborate, innovate, and drive business success.
You might also be interested in learning How to build a Data Governance Strategy.
Best Practices for Implementation
Establish Clear Data Governance Policies and Guidelines
Clearly define policies, procedures, and guidelines that govern data management practices within the organization. This ensures consistency and clarity, aligning employees with the data governance objectives.
Engage Stakeholders and Foster a Data-driven Culture
Involve key stakeholders in the data governance initiative and create awareness of its importance. Foster a data-driven culture by promoting data literacy, training, and incentivizing data-driven behaviors.
Implement Robust Data Management Practices and Technologies
Leverage suitable data management tools and technologies to support the data governance framework. This includes data cataloging, data lineage, and data quality tools, among others.
Monitor and Measure the Effectiveness
Regularly assess the performance of the data governance framework, monitor compliance, and measure the impact on business outcomes. This enables organizations to refine their strategies and continuously improve.
All that said, it is also important to note that the best way of implementing all the above-mentioned measures successfully is to have a good data management service in place.
Why Choose IntoneSwift?
Data governance frameworks are vital for organizations seeking to leverage the full potential of their data assets. By implementing robust frameworks, businesses can enhance data quality, facilitate data-driven decision-making, ensure regulatory compliance, streamline processes, and enable data collaboration. It is crucial for organizations to prioritize data governance and take proactive steps towards implementing an effective data governance framework. By doing so, they can drive business success in today’s increasingly data-centric world. IntoneSwift enables businesses to attain all of these in a seamless, effective and efficient way. We offer:
- Knowledge graph for all data integrations done
- 600+ Data, and Application and device connectors
- A graphical no-code low-code platform.
- Distributed In-memory operations that give 10X speed in data operations.
- Attribute level lineage capturing at every data integration map
- Data encryption at every stage
- Centralized password and connection management
- Real-time, streaming & batch processing of data
- Supports unlimited heterogeneous data source combinations
- Eye-catching monitoring module that gives real-time updates
Contact us to learn more about how we can help you! | <urn:uuid:f83a7583-cbd0-49b5-bce4-74c792579e1c> | CC-MAIN-2024-38 | https://intone.com/how-data-governance-frameworks-drive-business-success/ | 2024-09-20T08:06:35Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652138.47/warc/CC-MAIN-20240920054402-20240920084402-00648.warc.gz | en | 0.892012 | 1,424 | 2.515625 | 3 |
Table of Contents
In this lesson, we will talk about one of the key lessons in networking, especially in switching. We will explain VLAN definition and we will answer the question what is a VLAN? In the following lessons, we will learn the details of Virtual LANs and we will practice with VLAN Configuration Examples . You can also check the definion on Wiki.
If we do a simple VLAN definition, Virtual Local Area Networks are the Logical Virtual Networks that you can seperate big networks into smaller networks. This can be done for reducing broadcast traffic, network performance improvement, security purpose or to seperate different departments each other and for network flexibility.
In a company, different Virtual LANs can be used for different departments. Think about that these departments are IT, HR and Finance. In a single company LAN, with Virtual LANs, each of these department networks become separate networks.
Virtual LANs are Logical networks. In the first place they are defined on the switches and then the ports are assigned to them. By doing this, VLANs members ports appear.
Generally fistly two terms are learned by new engineers about computer networks. These terms are Collision Domain and Broadcast Domain. It can be good to define these terms again. Because in the VLAN lesson, these terms are ciritically important.
Collision domain : A single physical line that a colision can occur. Example: Hubs have one collision domain and only one connected node can make a transfer at any time. Switches collision domain number is like their port number by default.
Broadcast domain : A logical division of networks that all nodes can reach eachother at data link layer(layer 2). Example: Switches are one broadcast domain. Because without any restriction, if one node sends something from one port, all other ports receive it. Routers’ each port is one broadcast domain.
Let’s return our main lesson again. Virtual Local Area Networks help you to build new child broadcast domains in one switch or in one broadcast domain. After Configuring VLANs, each Virtual LAN become a single broadcast domain and without routing, there is no communication between Virtual LANs.
There are also Collision Domains in the Virtual LANs again. Each VLAN has Collision Domain as the number of their assigned ports.
Here, Virtual LANs can be thinked like small switches in the main switch.
On Cisco switches, all the ports are the member of VLAN 1 by default. So if no VLAN Configuration done, all the ports are in the same Virtual LAN, Virtual LAN 1. And they are in the same Broadcast Domain as mentioned above.
By default Native VLAN is 1. By default, all untagged frames are member of it. This Native VLAN can be changed by a trunk port. For example, think about that, one trunk’s NativeVLAN is 5. Here, all the untagged and 5 tagged frames are belong to that Virtual LAN 5. Here the important point is, each end of the connection must be configured with the same configuration.
ISL trunks does not support the NativeVLAN and untagged frames. But dot1.q trunks supports.
On the other hand, Native VLAN is a security risk. To avoid this risk, NativeVLAN can be assigned to an unused port or disabled port. You can also make the trunk ports to tag the Native Virtual LAN.
In this lesson, we have talked about Virtual LANdefinition, what is a VLAN simply and Native VLAN. Beside, we have remembered Collision and Broadcast Domains. In the next lessons, we will learn more on Virtual LANs and we will learn How to Configure VLANs. | <urn:uuid:129865e0-1d54-43dc-b549-075abde7880c> | CC-MAIN-2024-38 | https://ipcisco.com/lesson/vlans-overview/ | 2024-09-08T04:31:26Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650958.30/warc/CC-MAIN-20240908020844-20240908050844-00848.warc.gz | en | 0.910432 | 770 | 4.1875 | 4 |
We briefly covered voice access ports earlier in the chapter also mentioning voice VLANs. It is time now to dig a bit deeper into voice VLANs and do a little configuration as well.
The voice VLAN is an ingenious feature that enables access ports to carry voice traffic from an IP phone. Cisco IP phones connect to the IP network using Ethernet to send Voice over IP (VoIP) packets. The Voice over IP framework is made up of several components including IP phones, call managers, and voice gateways. A detailed coverage of these components is beyond the scope of this book and your Cisco Certified Network Associate (CCNA) exam. The VoIP communication takes place over the same shared network infrastructure made up of switches and routers which is used for data communication.
Each desk or cubicle in a modern enterprise is likely to have both an IP phone and a PC on it. One way of connecting the IP phone to switch may have been to use a separate Ethernet cable and a separate switch port. But Cisco came up with the idea of including a small LAN switch built inside each Cisco IP phone. This small switch allows one cable to run from the LAN switch to the desk to connect to the switch built into the IP phone. Then the PC can connect to the switch inside the IP phone over a short straight-through Ethernet cable from the PC to the bottom of the IP phone. If you have access to a Cisco IP Phone, turn it upside down and you would find two Ethernet ports at its bottom. One port is to be connected to the LAN switch, the second port is to be connected to the PC and the third port is internal which connects to the IP phone circuitry inside. This is the simple three port switch built into all Cisco IP phones. In this way, a Cisco IP phone provides a data connection for a user’s PC, in addition to its own voice data stream. Please see figure below for a graphical representation of the concept just described.
Figure 7-14 Built-in Switch of the Cisco IP Phone
As you can see in the diagram, the link between the phone and switch should use 802.1Q trunking, and the phone and PC should be in different VLANs and hence in different IP subnets. This design is per Cisco recommended guidelines and has several advantages. First, by placing IP phones in one VLAN, and the PCs connected to phones in a different VLAN, you can more easily manage the IP address space, apply Quality of Service (QoS), and provide better security by isolating the data and voice traffic.
Figure 7-15 How to Connect an IP Phone and PC to LAN Switch
On a relatively quiet, underutilized network, a switch can generally forward frames as soon as they are received. However, if a network is congested, packets cannot always be delivered in a timely manner. Different types of applications have different requirements for how their data should be sent end to end. For example, it might be acceptable to wait a short time for a Web page to be displayed after a user has requested it. Also, an FTP download may continue at a variable rate without issues as user can use the file once it is fully downloaded. But it is probably not tolerable to face the same delays in receiving packets that belong to a streaming video presentation or a telephone call. Video streaming is very popular these days and typically multicast traffic over UDP as the transport protocol is used to transmit the video stream from a server to several clients. Any loss or delay in packet delivery would ruin the purpose of these applications due to their real-time or interactive nature.
Traditionally network congestion has been handled by increasing link bandwidths and enhancing switching hardware performance. This approach is not cost effective or efficient and it does nothing to address how one type of traffic can be preferred over another. Quality of Service (QoS) can be used to protect and prioritize time-critical traffic like voice and video. Keep in mind that the most important aspect of transporting voice traffic across a switched network is maintaining the proper Quality of Service level. Voice packets must be delivered in the most timely manner possible, with minimum jitter, loss, and delay.
As a matter of fact, layer 2 frames have no means to indicate the priority or importance of their contents for the purpose of prioritization or QoS. One frame looks just as important as any other frame. However, when frames are carried from switch to switch, an opportunity for classification occurs. We understand that a trunk is used to carry frames from multiple VLANs between switches. The trunk does this by encapsulating the frames and adding a tag indicating the source VLAN number. The encapsulation also includes a field that can mark the class of service (CoS) of each frame. This marking can be used at switch boundaries to make QoS decision and prioritize traffic according to importance. Cisco switches typically perform QoS implementation or traffic prioritization in hardware and the actual mechanisms may vary from platform to platform.
The LAN used for voice traffic from the IP phone is called the voice VLAN and the VLAN used for data is called the data or access VLAN. For the LAN switch to forward traffic correctly, it needs to know the VLAN ID of the voice VLAN as well as the data VLAN. The data or access VLAN is configured just as a regular access VLAN is configured using the switchport access vlan vlan-id command. The voice VLAN is configured using the switchport voice vlan vlan-id interface configuration mode command. Referring to the diagram, the switch would need both the switchport access vlan 5 and switchport voice vlan 15 commands in interface configuration mode.
This chapter introduced to you a number of enhanced switching technologies and described how you can configure them on Cisco switches. We started with talking about virtual LANs (VLANs) and how they break up broadcast domains in a switched network and provide traffic isolation at layer 2. This fact is very important because layer 2 switches without VLANs only break up collision domains and your switched network is one large broadcast domain. We learned what access links are and also went over how trunked VLANs work across a Fast Ethernet of Gigabit Ethernet link.
Trunking is an important and critical technology to understand as most of the enhanced switching technologies described in this chapter invlove trunking one way or the other. We went into great detail describing VLAN Trunking Protocol (VTP) and learned how it sends VLAN information to all switches in the network over trunked links. We also leaernt how to configure and troubleshoot VTP in case things don’t work as you expect them to work.
Finally we covered Voice VLANs which can be used to allow IP phones to run along with regular desktop or laptop computers over your access switch ports. We finished off the chapter with detailed configuration and troubleshooting examples for almost all technologies covered in the chapter.Questions
Read the questions carefully and try to answer as many questions correctly as you can. Answers to these questions are provided on the next page.
1. Based on the exhibit shown for the local area network of an office comprising two departments, which of the following are correct ? (Choose two)
A. There are six collision domains in the network
B. There are two broadcast domains in the network
C. There are four broadcast domains in the network
D. There are six broadcast domains in the network
E. There are five collision domains in the network
2. An Ethernet switch receives a unicast frame with a destination MAC address that is listed in the MAC address table. What will the switch do with the frame?
A. The switch will forward the frame to a specific port
B. The switch will forward the frame to all ports except the port on which it was received
C. The switch will send a copy of the frame out the same port on which it was received
D. The switch will not forward the frame at all
E. The switch will add the destination MAC address in the frame to the MAC address table
F. None of the above
3. A switch port is configured as a VLAN trunk. Which of the following trunk modes are valid ? (Select all that apply.)
B. Dynamic auto
C. Dynamic desirable
F. All of the above
4. Which of the following frame encapsulation methods can be configured on Cisco switch trunks? (Select two.)
5. You need to configure two switches to exchange VLAN information. Which protocol provides the functionality of sharing VLAN information between these two switches?
F. None of the above
Q6. Which of the following statements are true regarding how VLANs are used to segment a network? (Select three)
A. VLANs increase the size of collision domains.
B. VLANs increase the size of broadcast domain while decreasing the number of collision domains.
C. VLANs increase the number of broadcast domains while decreasing their size.
D. VLANs allow logical grouping of users by function.
E. VLANs can enhance network security.
F. VLANs simplify switch administration.
7. Two switches have been configured with static VLANs as shown in the figure. But VLAN 2 on switch A has no connectivity with VLAN 3 on switch B. How should the network administrator solve the problem?
A. Configure interconnected ports on switch A and switch B in access mode.
B. Connect the two switches using a straight-through cable.
C. Configure VLAN 1 with IP addresses on both switches.
D. Add a layer 3 device to provide connectivity between VLAN 2 and VLAN 3.
D. Ensure that VTP passwords match on both switches.
8. Which of the following steps are basic requirements in order to add a new VLAN to a switched network?
A. Create the VLAN.
B. Name the VLAN.
C. Configure an IP address for the VLAN.
D. Add the desired switch ports to the new VLAN.
E. Add the VLAN to the VTP domain.
9. You connect a new PC to a free port on a switch, but you find that the PC cannot access any of the resources on the LAN. No other PC connected to the switch has connectivity issues. What is the most likely cause of this problem?
A. The MAC address is not configured correctly on the host.
B. An STP instance is not running for the new host.
C. The switch does not have the MAC address of the new host hard coded in the MAC address table.
D. The switch port host is connected to is assigned to the incorrect VLAN.
E. The router has not learned the route to the new host.
10. Please study the exhibit carefully. The switch has twenty four Fast Ethernet ports and two Gigabit Ethernet ports. But why are some ports missing from the list of ports assigned to the default VLAN?
A. The missing ports are administratively shut down.
B. The missing ports are not actively participating in STP
C. The missing ports are assigned to VLAN 100.
D. The missing ports are configured as trunk ports.
E. The missing ports have a speed or duplex mismatch with neighboring ports.
F. None of the above.
1. B, E
3. B, C, D
4. A, F
6. C, D, E
8. A, D | <urn:uuid:bfae711a-2c8c-49e9-acbf-fb4b1bb890f0> | CC-MAIN-2024-38 | https://www.freeccnastudyguide.com/study-guides/ccna/ch7/7-10-voice-vlan-configuration/ | 2024-09-10T13:20:38Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651255.81/warc/CC-MAIN-20240910125411-20240910155411-00648.warc.gz | en | 0.925896 | 2,372 | 3.171875 | 3 |
Digest Access Authentication is a way for service providers to verify a person’s credentials by using a web browser.
Specifically, digest access authentication uses the HTTP protocol, applying MD5 cryptographic hashing and a nonce value to prevent replay attacks. Hash values are affixed to the person’s username and password before they are sent over the network, enabling the provider’s server to authenticate the person.
Digest access authentication is preferred over basic access authentication, which uses unsecure Base64 encoding over HTTP. Basic access authentication is unsecure unless combined with transport-layer security (TLS).
“Digest Access Authentication provides for the hashing of usernames and passwords so online services can verify that the person accessing their service on the web browser is who they say they are.” | <urn:uuid:431ce3e3-e192-4cb2-9956-9ab9d802b252> | CC-MAIN-2024-38 | https://www.hypr.com/security-encyclopedia/digest-access-authentication | 2024-09-10T13:36:37Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651255.81/warc/CC-MAIN-20240910125411-20240910155411-00648.warc.gz | en | 0.840731 | 165 | 2.796875 | 3 |
Web applications often use session tokens to track user sessions and maintain state. With each request, these tokens are passed between the client and server, allowing the server to identify the user session. While session tokens are useful, their management and expiration policies are critical for application security.
Session Expiration Not Enough
Many web applications set session expiration policies based simply on inactivity timeouts. For example, if there is no activity in the user session for 15 minutes, the session is terminated. However, inactivity timeouts alone are not sufficient for secure session management.
The National Institute of Standards and Technology (NIST) provides guidelines that session tokens should expire after an absolute timeout, regardless of activity. This ensures that an attacker cannot indefinitely prolong a hijacked session. The Open Web Application Security Project (OWASP) similarly recommends absolute timeouts no longer than the business-required timeframe, typically 30 minutes for high-security applications.
Relying only on inactivity timeouts means a hijacked but active session could persist indefinitely. Attackers could proactively refresh the session to prevent inactivity timeouts. Additionally, users may walk away from an active session which could then be hijacked. Absolute timeouts mitigate these risks.
Session Hijacking Attacks
Attackers often target session tokens to hijack user sessions and assume their identities. Common attacks and their prevention include:
- Session prediction - Some session tokens are generated using weak algorithms and can be predicted by the attacker. Strong session id generation is critical.
- Man-in-the-middle - The attacker intercepts traffic between client and server to steal the session token. Sensitive traffic should always be encrypted via HTTPS.
- Cross-site scripting (XSS) - An attacker injects malicious scripts into the page to steal the session token. The token can then be used to impersonate the user.
- Session side jacking - On public WiFi networks, the attacker monitors traffic to steal session tokens from the wire. Network traffic should be secured and encrypted.
- Brute force - An attacker performs automated guessing on session tokens to find valid ones. Long complex session tokens can mitigate this.
Securing Session Tokens
Companies should implement security best practices around session management:
- Enforce absolute session expiration timeouts consistent with business needs and no longer than 5 minutes of inactivity for sensitive applications.
- Generate strong session tokens with high entropy at least 128 bits long. Avoid tokens that are guessable or predictable.
- Use HTTPS encryption for all sites handling sensitive data or transactions. Encrypt network traffic end-to-end.
- Implement additional session security controls like binding tokens to client IP addresses and/or browser fingerprints.
- Follow secure coding practices around session management in application development.
Properly managing web session tokens is critical for mitigating session hijacking, maintaining state securely, and protecting user identities and data. Combining short absolute expiration timeouts, strong session ids, encryption, and other controls provides defense-in-depth for this critical component of web security. | <urn:uuid:e7dce576-2599-4555-8ced-9644a3914d8b> | CC-MAIN-2024-38 | https://guptadeepak.com/web-session-tokens-your-insurance-policy-against-cyber-threats/ | 2024-09-15T13:16:30Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651630.14/warc/CC-MAIN-20240915120545-20240915150545-00248.warc.gz | en | 0.848922 | 616 | 2.578125 | 3 |
We know that security is a must in the Digital world . News reports about cyberattacks and data breaches leave no doubt that strong security is a must. But what’s the difference between information security, cybersecurity and network security?
When humans begin to keep secrets, that’s when information security came. In earlier days we used to keep physical files and folders , documents in key lockers. When digital world started using computers, network security started taking its form. It became important to protect the network security of digital systems. As soon as internet started growing in this business world, a new important industry called as cyber security takes a new form to protect data from unwanted threats.
So , as it is said , everything and everyone has its own importance, these three are equally plays a vital role in their areas. While the first two is just foe keeping information, data safe and secure, the third one “Cyber security” is important.
Closely related terms?
how do some of the industrialist define these terms let’s have a look
According to the SANS institute, Information security refers to the process and methods which are there to protect print, media and other form of private and confidential data from unauthorized use.
Cisco defines Cyber security as the practice of protecting networks, programs from digital attacks which destroys sensitive information.
Network security, the SANS Institute explains, is “the process of taking physical and software preventative measures to protect the underlying networking infrastructure from unauthorized access, misuse.
CIA Trio in Cyber security. What it is ?
Whenever we are discussing about the three securities i.e. Information security, Cyber security, and Network security, we need to understand what is this CIA trio. What it comes to mind when hearing first about CIA trio? A secret group of three people? not exactly.
CIA trio refers to those policies and guidelines which the industry experts pay attention to while developing policies for effective information security system.
CIA trio is the most important aspects of Information security.
C- CONFIDENTIALITY : It protects the information from unauthorized access to people with the help of passwords, pin codes, ID’s and encrypted codes.
I-INTEGRITY: It protects the information from unauthorized access to people from being modified by unauthorized people. It safeguards accuracy of data.
A-AVAILABILITY- The information is available to people whenever they need them by keeping them with current updates and backups.
While observing throughout in security industry , The CIA TRIO according to Cybervie is to helps you to detect vulnerabilities of a system, attacks and manage emergency situations. It uses real time scenarios which can help students to understand the market and maintain its integrity. It is all time available to provide best cyber security training program.
- Social engineering
- Brute force
- Phishing. This type of online fraud is designed to steal sensitive information, such as credit card numbers and passwords.
- Computer Viruses.
When cyber threat attackers your organization, they find about your business and employees. They know that employees outside of IT security are not aware of cyber threats, so they implement cyberattacks. Through the process of social engineering, threat attackers manipulate people to give them access to sensitive information.
In this form, cyber threat attackers gather the potential data with the help of email, phone, SMS chats.
- Man-in-the-Middle Phish Kits:
When a threat actor pretends to be an someone or have authority over it , they target people to do something which they would not do. - Baiting:
When threat attackers leave a system -poisoned device, such as a USB or CD at a place where people can find them, then if they use the infected device on their computer and by mistake install the software, threat attackers get their system access. - Quid Pro Quo:
When a threat attacker requests personal information in return for some kind of reward, e.g., money, free gift, or a free service.
How Does Cybersecurity Work?
- Application security: All of the platforms used within an organization provides a protective environment for data like aspects like architecture, code, etc.
- Data storage and transit: While data is at rest, it needs to be kept properly with appropriate storage and encryption.
- Disaster recovery: Both data backups and plans are necessary for keeping systems safe and running smoothly in the event of a hack.
- Mobile security: mobile security involves the steps and policies to protect the systems and the information.
- Identity management: It ensures that only authorized users can access data.
- Training: Users must also know how to use devices safely and identify and report malicious attacks or suspicious events just like Cybervie providing exclusive training programs related to cyber security.
Network, info and Cyber: Can information in these security systems overlap?
When digital data was a relatively new concept, it was easy to distinguish InfoSec, cybersecurity, and network security. As usual, cybersecurity took on the role of data protection. Most professionals understand the technology behind you, but the information security umbrella tends to place more emphasis on data testing, such as prioritization and risk.
For each type of security, many experts use the CIA triangle, which refers to confidentiality, integrity, and access to data. While they may use different methods, InfoSec, cybersecurity, and network security all aim to protect CIA employers from data security. Indeed, because network security is part of cybersecurity, which is part of information security, these three have significant differences.
Meaning of cloud and network security.
what is a hybrid cloud?
Both Cloud and Network security aim to prevent any data and ensure that the information is not changed. The role of both cloud and network security is to protect the organization’s IT infrastructure from all types of cyber threats, including:
- Insider attacks
- Malware like viruses, worms, and Trojans
- Zero-day attacks
- Tradecraft attacks that bypass normal technical controls
- Denial of service attacks
We visualize the world, which owns businesses in cloud storage. This brings us to the need for Cyber Security and Network Security. Cyber Security is a field in which we protect our data from cyber criminals. Cyber-security refers to the use of computer network software, software, or other technologies to protect online threats. Maintains a set of processes used to protect the integrity of networks, programs, and data from unauthorized access. Lock network (Network security). Network security is a subset of Cyber Security aimed at protecting networks.
I hope we have learnt enough about what is the difference between closely related terms Cybersecurity, Information Security and Network Security. | <urn:uuid:e1934916-2fb5-4a4b-a7db-bee1224f4b6c> | CC-MAIN-2024-38 | https://cybervie.com/article/cybersecurity-vs-information-security-vs-network-security/ | 2024-09-08T10:32:08Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650976.41/warc/CC-MAIN-20240908083737-20240908113737-00048.warc.gz | en | 0.939035 | 1,369 | 3.171875 | 3 |
What is Data Aggregation?
Data Aggregation is the process of gathering data and then presenting it in an organized manner for business or statistical analysis.
The data can be gathered from multiple data sources so that we can combine these data sources into a summary for data analysis. This is a pivotal step since the data analysis depends heavily on the quantum and quality of data used. It is important to gather high-quality accurate data to produce conclusive results. Data aggregation is useful for business strategy, pricing, operations, and marketing strategies.
Give some examples of Data Aggregation?
Data aggregation in the financial, stock markets and investment sectors can use data aggregation to gather headlines and article copy and use that data for predictive analytics, to find trends, events, and changing views that could affect the financials of the companies and products. Another example is Web Data Integration which not only extracts and aggregates the data you need, but it also prepares and cleans the data and delivers it in a consumable format for integration, discovery, and analysis. So, if any company needs accurate data from the web, then Web Data Integration is your choice. Other examples are the retail industry, travel industry, etc.
How is Data Aggregation useful?
Data extraction, Modifying or transforming the data in such a way that it corresponds to the specified format for data analysis.
Data visualization and analysis – A visual representation of analysed data and KPIs which can be used for actionable business decisions. You can fluently estimate where your business needs to grow or change with these criteria.
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Or Request for a Free Demo | <urn:uuid:e7b2c5b7-8549-4480-8f60-9cc46bb8a2c6> | CC-MAIN-2024-38 | https://alertops.com/articles/data-aggregation/ | 2024-09-09T11:04:42Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651098.19/warc/CC-MAIN-20240909103148-20240909133148-00848.warc.gz | en | 0.899319 | 336 | 3.5625 | 4 |
spchapi.exe is the file that can cause system issues
spchapi.exe is an executable file whose primary purpose is to start a process or launch the program on the machine. Unfortunately, a parasite can use to spread threats on the machine or launch viruses. Once executed, the possibly malicious file runs a process that is responsible for the parasite's payload. The executable file can be a significant part of a dangerous threat, but it can also work on its own. It can be installed by the trojan, keylogger, or different threats. Stay away from the file.
Name | spchapi.exe |
Type | Executable |
Possible issues | Speed issues, internet issues, crashes, and freezing of the PC |
Removal | You should use an antivirus tool and check if the piece is malicious before deleting it fully |
Repair | Run FortectIntego and repair any possible damage on the machine |
spchapi.exe is one of the many executable files that can be found on the system running in the background. Executables are legitimate file processes developed by Microsoft Corporation generally. But some of them can be misused by malicious actors. You can locate these safe files in C:\Program Files, so if you notice the piece in a different file – be concerned.
The virus can be using the DLL or EXE file to hide malicious processes. If it is created by malware authors, it can still be named after the spchapi.exe file to mask the purpose. If so happens you can notice symptoms:
- Unstable internet connection
- Browser redirects to unwanted websites
- Poor PC performance
- System slows downs.
You are highly advised to scan the system before you choose to delete executable spchapi.exe and terminate all the processes it started. It can be a file installed by harmless legitimate software and therefore may not pose any threat to your privacy and the system. Run an anti-malware tool to make sure it is possible to remove the piece. | <urn:uuid:b09e1b58-5b28-431f-a0b3-31d8c7366e6c> | CC-MAIN-2024-38 | https://www.2-spyware.com/file-spchapi-exe.html | 2024-09-09T11:27:43Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651098.19/warc/CC-MAIN-20240909103148-20240909133148-00848.warc.gz | en | 0.918867 | 417 | 2.59375 | 3 |
- By using AI-powered chatbots, companies can provide customers with 24/7 support without human intervention.
- Artificial Intelligence (AI) is a critical tool for enterprises to stay competitive in the modern world.
AI has brought a revolution, quite literally! Currently, many companies are still trying to understand AI from a business perspective. Many understand its importance, but very few are sure about investing in AI-enabled tools. Most of them are struggling to hire teams that thoroughly understand AI for direct implementation.
So, it’s the need of the hour for people to see AI in action. It’s that time of year again when business leaders, consultants, and vendors in AI look at enterprise trends and make predictions. After the crazy year of 2022, it might get challenging in 2023.
2023 will be the beginning of a true AI reckoning from companies spanning various industries. Let’s see how.
What is the Importance of AI in Enterprises?
Artificial Intelligence (AI) is now an essential tool for enterprises in the digital age. With the ability to study large amounts of data quickly and accurately, AI can help organizations improve efficiency, productivity, and decision-making.
One of the most significant ways AI is used in enterprises is by automating repetitive tasks. This includes tasks such as data entry, invoice processing, and customer service.
By using AI-powered chatbots, for example, companies can provide customers with 24/7 support without human intervention. This not only reduces costs but also improves customer satisfaction.
Another area where AI is making a significant impact is in the field of predictive analytics. AI algorithms can identify patterns and predict future outcomes by analyzing large amounts of data. This can be especially valuable in marketing and sales, where companies can use predictive analytics to understand customer behavior and preferences better.
Also, AI is used to improve the efficiency of supply chain management. AI can help companies optimize their supply chains and reduce costs by analyzing supplier performance, inventory levels, and customer demand.
AI is also playing a key role in cybersecurity. With the rise of cyber threats, companies need to be able to detect and respond to attacks quickly.
AI-powered security tools can analyze network traffic and identify potential threats in real time, allowing companies to take action before any damage is done.
Finally, AI is being used to enhance the customer experience. AI can provide personalized recommendations and offer customized products and services by analyzing customer data. This improves customer satisfaction and helps companies build stronger customer relationships.
Benefits of AI in Enterprises
Artificial Intelligence (AI) is essential for enterprises to stay competitive in the modern world. The technology allows machines to learn from data and make decisions that mimic human thinking.
The benefits of AI in enterprises are vast and can be seen in many areas, including productivity, cost reduction, customer service, and innovation. Here are some of the significant benefits of AI in enterprises:
Enhanced efficiency and productivity: AI-powered tools and software can automate many time-consuming and repetitive tasks, allowing employees to focus on more complex and strategic work. AI can also analyze large amounts of data to identify patterns and insights humans may have missed, helping companies make more informed decisions.
Cost reduction: By automating tasks, AI can help reduce costs associated with human labor. Additionally, AI can help optimize supply chains, reduce waste, and minimize downtime, leading to significant cost savings for businesses.
Improved customer service: AI-powered chatbots and virtual assistants can provide 24/7 support to customers, answer their queries, and even handle transactions. This can lead to faster response times, improved customer satisfaction, and reduced support costs.
Personalization: AI can help businesses provide personalized experiences to customers by analyzing their behavior and preferences. This leads to an increase in customer loyalty and higher sales.
Innovation: AI helps companies develop new products and services by identifying unmet customer needs and predicting future trends. This can give businesses a competitive edge and help them stay ahead of the curve.
Risk management: AI can help companies identify potential risks and opportunities by analyzing large amounts of data. This can help businesses make more informed decisions and mitigate threats before they become problems.
Predictive maintenance: AI can help companies predict when machines and equipment need maintenance or repairs, reducing downtime and increasing efficiency.
Cybersecurity: AI can help companies detect and prevent cyber threats by analyzing network traffic, identifying anomalies, and flagging suspicious activity.
AI Predictions for Enterprises in 2023
In 2023, enterprises will continue to adopt AI technologies to improve business operations and decision-making processes. Here are some predictions for how AI will impact enterprises in the next two years:
Expansion of AI Applications
Enterprises will continue to explore new applications for AI. From healthcare to finance, AI is poised to revolutionize many industries. With the release of tools like ChatGPT, today’s large language models are larger than they ever were. There are high chances that it will be multimodal in the future – meaning it could work with data, videos, images, and text.
2023 Might be the Year for AI Governance
Companies will build from the principles-based discussions around Responsible AI and AI Governance to implementing practical solutions. It is predicted that the businesses that adopt a unified strategy to ensure that defined procedures and frameworks are made operational over the full AI lifecycle—one that incorporates an AI Governance framework, a strong Responsible AI program, and the successful use of MLOps—will win.
More Focus on Explainable AI
Explainable AI will become a primary focus for enterprises, enabling them to understand better how AI systems work and make decisions. Enterprises will focus more on combining AI or ML activities with traditional analytics and automation.
2023 will be Significant for Federated Learning
The machine learning process, known as federated learning, uses the unmodified original data in a collaborative setting. Federated learning, in contrast to traditional machine learning systems, which require the training data to be centralized into a single machine or data center, distributes the training of algorithms across a number of decentralized edge devices or servers.
AI will Enable More Productive DevOps
AI-driven DevOps will be the way of the future. It’s fair to say that human intelligence struggles to make sense of vast amounts of extremely complex data. As a result, data integration and analysis will be made easier with the help of AI-powered solutions, which will also revolutionize the way teams create, deliver, and manage applications.
A few other predictions are –
- The concept of ‘Search’ will change forever. It is no longer a long list of links but is more of a conversational search that includes a dynamic conversation with an AI agent.
- Efforts and funding will rise for developing humanoid robots. Also, giants like Google Brain, OpenAI, and DeepMind will make efforts to build a “foundational model” for robotics.
- The AI/ML space will practice more Machine Learning Operations (MLOps). The ability to accurately monitor models post-deployment and make the needed changes will become an important component of MLOps strategies.
- Real-time speech translation will see a lot of advances due to its rising importance. Manual translation can be a huge pain when the world is working remotely. The advances will help in improving efficiency and offer an opportunity for businesses to operate globally.
Enterprises have always relied on AI to improve their operations, develop new products and services, and better understand their customers. But now, enterprises will focus on doing more with less, whether it’s resources or cost.
As these technologies become more advanced, many are sure that enterprises will dedicate serious time and money to the development of AI! | <urn:uuid:f8dd8a30-7120-46b3-8026-4ece516f166d> | CC-MAIN-2024-38 | https://www.ai-demand.com/insights/tech/artificial-intelligence/predictions-for-ai-in-enterprises-in-2023/ | 2024-09-09T12:21:39Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651098.19/warc/CC-MAIN-20240909103148-20240909133148-00848.warc.gz | en | 0.943866 | 1,591 | 2.59375 | 3 |
Ready to learn Artificial Intelligence? Browse courses like Uncertain Knowledge and Reasoning in Artificial Intelligence developed by industry thought leaders and Experfy in Harvard Innovation Lab.
I’m pretty sure that at this point you simply were too afraid to ask.
Regularly receiving queries about Artificial Intelligence is of course flattering, but can also be bothersome, as some of the most regularly asked questions could easily be answered via a quick Google search. A number of people are however wary of doing so, partly because of movies’ unrealistic image of A.I (among other unrealistic expectations), and the current startup culture which venerates coders and techies, putting them and their knowledge on a pedestal.
With that in mind, below is a simple, quick and no-nonsense look at A.I through the lens of the questions I most frequently get asked.
“What is your own definition of Artificial Intelligence?”
A.I is not a mere constellation of processes and technologies, but also a business topic and an academic matter, while also being an ethics concern (among other things). I’d argue that to keep things very easy you could define A.I in three ways :
- Symbolic A.I : a simple algorithm which is able to make decisions based on predefined parameters and expected actions. These are mere “if-statement” and far from what academics would call artificial intelligence. Nevertheless, it is, in a way, intelligence: if I see a snake, I run. If I see cake, I salivate. The main difference is that I know why I’m running (experience, fear…), and why I’m salivating (hunger, potential sugar-high which would hit the reward center of the brain…). A symbolic A.I has no idea of the why and how, it’s just automated to follow procedure.
- Machine Learning : this refers to an algorithm which also follows procedure but on a deeper level. When “fed” enough data (and we’re talking very, very large amounts), it can potentially draw inferences which a human might not be able to draw in his/her lifetime (a.k.a unsupervised machine learning, a.k.a clustering). Beyond this, we’re able to create tools which learn and adapt from this data through rewards (a.k.a reinforcement learning), and even tools able to identify and categorise unstructured data such as images or speech (a.k.a deep learning). Though incredible, these technological advances only apply to very specific, easily automated tasks. For now, that is.
- General Artificial Intelligence : This is what you see in movies (i, Robot, Ex Machina, 2001 A Space Odyssey…). It’s an algorithm which could not only learn from experience but could also transfer that knowledge from one very specific task to another (you can read this on a computer and could potentially read my handwriting, but at the moment an A.I could only do one of the two). Alternatively, you could look at it this way : a modern A.I could make a very accurate prediction based on data, but would need a (comparatively statistically challenged) human to infer meaning (the good old causation vs correlation debate). A general artificial intelligence could do both, but is oh so far away from ever being developed.
“Do we already use it in our daily lives?”
I mean, yes, of course. We shop on Amazon, we take Ubers, we use Google, we send Gmails, we fly in planes… we all use A.I everyday, and it would be very hard to find someone not using such algorithms in their daily lives. Search results, newsfeeds, digital advertisement, platform moderation, friends/products recommendations… It all is impacted by companies leveraging data to inform softwares.
Individuals, however, are unlikely to leverage such a tool themselves though, due to the massive amount of data necessary to create a convincing A.I.
“When will we get the happy-fun-times robots?”
That’s a robotics questions. Not an A.I question. Get your head out of the gutters.
“Should we trust A.I?”
A.I is not something to be trusted or not trusted. It is merely a man-made tool which is “fed” data in order to automate certain tasks, at scale.
Do you trust your washing-machine?
Yeah, me neither.
Math is black magic.
The only thing we should be wary of (for now) is the quality of the software’s design and the quality of the data “fed”. Ensuring both of these elements’ quality is however easier said than done. As such, this question should be rephrased as “do we trust (insert company’s name here)’s managers have our best interest at heart?” and, if yes, “do we trust the company’s programmers to implement that vision flawlessly while taking into account potential data flaws?”.
That’s trickier, isn’t it? But more realistic.
“More generally, should I be frightened of this new technology?”
First of all, forget the LONG think-pieces about General Artificial Intelligence (go home Kissinger, you’re drunk). We’re not there yet and the chances we ever will be are incredibly small (I’m a realist, sue me). Nevertheless, though the technology itself is more or less value-neutral, as explained above, the way it’s implemented may have terrifying ramifications.
- Right to self-determination : Through a basic understanding of Nudge Theory, a potentially hostile actor could manipulate content displays on platforms and personalisation enough to influence a statistically significant amount of people towards a pre-determined nefarious goal (hey, remember when Russia used social media to get Trump elected?).
- Right to freedom of opinion : Put simply, A.I could (and can) identify and target specific opinions on the internet. For advertising purpose? Yes, for advertising purpose said Erdogan and Putin. This could become a nightmare if the mechanisms of this identification and targeting are not well understood. Hey remember when Facebook labeled 65,000 Russian users as ‘interested in treason’?
- Right to privacy : yeah, no, we can forget about that. Oh, the Americans already have? cool, cool. Hey, remember when a facial recognition software could tell your sexual orientation? In Russia? Speaking of…
- Obligation of non-discrimination : Hey, remember when a facial recognition software could tell your sexual orientation? In Russia? Oh I already… Soz, seemed important.
Of course, all the above does not take into account the whole automation issue. See more below.
“Is A.I an opportunity for businesses or a threat to the traditional channels and employees?”
Why can’t it be both? This technology would not be under development if there was no benefit to reap from it: it is an opportunity for corporate teams to increase margins and use their customers’ data to better serve them (how we go from there depends on your view of capitalism as a system). However, this will absolutely mean that many people WILL lose their jobs in the process.
“But who, who will lose their jobs?” I hear you chant.
Well, it’s complicated. Many thousands of people have already lost their jobs, or were simply not replaced when they left, as technology is not a sudden surge and happens in waves. In a recent article for Harvard Business Review, one of the most influential AI researchers Andrew Ng offers this rule of thumb: “if a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.”
I however believe that in the long run A.I will assist us more than replace us, and ultimately free more time for grander endeavors : washing-machines and Hoovers didn’t replace women, they made it so that they could enter the workforce, ushering nearly 30 years of economic growth.
“Should my business follow or lead?”
I’ve got good news and I’ve got bad news.
The good news is that the decision has already been made : there are already A.I leaders (Google, Uber, Facebook, Amazon, JD, Alibaba…), and most brands are now just trying to follow. The bad news is that the decision has already been made : there are already A.I leaders and you’re now just playing catch-up. And sadly, in this instance, the world belongs to early adopter.
In many ways, A.I is a zero-sum-game : the first to adapt a sustainable A.I strategy is able to create a moat deep enough to protect itself from future competitors.
That however doesn’t mean that an A.I strategy shouldn’t be implemented. On the contrary…
“I want to use machine learning for my business: how do I start?”
First you’d need to assess what data you have, how much of it you have, and what tasks needs to be done : machine learning works best with very large data-sets and highly specialised tasks. Then you’d need to hire data scientists (and a consulting firm, hello there) in order to put new processes in place. Then, as a non-technical manager your role is to know the answer to three questions about your new algorithm:
“What data does it use? What is it good at? What should it never do?”
That’s it. The rest is for subordinates to take care of.
Then comes the boring part: you probably should be thinking about how to manage the ethical, legal, and business risks involved if something goes wrong. But there simply isn’t an industry standard framework for thinking about these kinds of issues. Nevertheless, one very common step involves checks and balances within the data scientist teams. Others are more thorough:
- Document the A.I model’s intended use, data requirements, specific feature requirements, and where personal data is used and how it’s protected.
- Take steps to understand and minimize unwanted biases
- Continuous monitoring by external actors such as consultants (hi!)
- Knowing how and when to pull the plug and what that would mean for the business
“What’s next for the technology?”
Are we on the path to Artificial General Intelligence? No, not even a little bit. Machine learning, in fact, is a rather dull affair. The technology has been around since the 1990s, and the academic premises for it since the 1970s. What’s new, however, is the advancement and combination of big data, storage power and computing power.
In fact, A.I breakthroughs have become sparse, and seem to require ever-larger amounts of capital, data and computing power. The latest progress in A.I has been less science than engineering, even tinkering; indeed, correlation and association can only go so far, compared to organic causal learning, highlighting a potential need for the field to start over. Researchers have largely abandoned forward-thinking research and are instead concentrating on the practical applications of what is known so far, which could advance humanity in major ways, though it would provide few leaps for A.I science. | <urn:uuid:4d57a053-bd8e-4381-aa1f-ac5a26918af3> | CC-MAIN-2024-38 | https://resources.experfy.com/ai-ml/simple-answers-to-artificial-intelligences-faqs/ | 2024-09-10T18:01:05Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651303.70/warc/CC-MAIN-20240910161250-20240910191250-00748.warc.gz | en | 0.948304 | 2,428 | 3.015625 | 3 |
As the business world adopts online digital tools, data stored on premise, in the cloud or using a hybrid configuration is increasingly at risk and requires sustained protective efforts. If left unchecked, cybercriminals can exploit weaknesses in security measures and infiltrate, siphon, distort or lock away data, causing setbacks that can cost businesses a fortune.
On Friday the 12th of May 2017, a worldwide ransomware attack, known as WannaCry, hit Windows users in 150 countries, though Australia seems to have been spared of the worst. The attack proceeded to lock user files behind a ransomware crypto worm. Though this was stopped by a 22 year old researcher, it shows how simple it is to find weaknesses in common operating systems and wreak havoc worldwide.
WannaCry is but one of the most recent examples of a major cyberattack. Locally, about a quarter of Australian organisations deal with security breaches every month. The problem with cyber threats is that any attack can rapidly spread to suppliers and customers, causing a lot of collateral damage. That’s why IT managers must ensure their security measures are up to snuff and ready to deal with threats—both external and internal.
Fortunately, IT security is a serious business. In Australia, key players are working together closely to reduce the threat of cyber theft. Government and IT security vendors are adapting to better protect digital customers.
Malcolm Turnbull’s government is taking steps to strengthen the legal framework pertaining to IT security. They introduced a mandatory data breach notification scheme, which requires organisations to report cybercrime to the Privacy Commissioner, as well as alert their customer base. Not complying can lead to fines of up to $1.8 million. This ties into the other data and privacy protection measures put in place, such as the Australian Internet Security Initiative (AISI).
Vendors have started to collaborate to further strengthen data protection efforts. Where before they would compete, they now share information. For instance, Sophos is harnessing the power of collaboration through partnership schemes that make it easier for IT security service suppliers to tailor IT security solutions to their customers’ needs.
By leveraging the collaborative efforts of government and vendors, customers are doing their part to help improve data security procedures by creating the demand for better solutions. This teamwork gives them greater security agility and flexibility, as they can rely upon customised multi-vendor security suites for their data protection needs.
The team mentality shown by government, vendors and customers against the common threat of cyberattacks drives innovation and increases data security. Customers benefit from a wider range of security options, regardless of their IT architecture, through vendor collaboration. They can also fall back on a more adequate legal framework to mitigate losses in the event of a security breach.
With PowerCONTROL, Powernet offers management solutions catered towards all aspects of your IT architecture. From maintenance and failure management, to email management and IT security, we offer a wide array of industry leading security products to take away the hassle and cost of having to maintain internal security solutions. Our managed team’s quick response time ensures that any problem will be dealt with before it escalates and causes irreparable damage. | <urn:uuid:420503e8-b90e-43b8-9875-65195ed4f193> | CC-MAIN-2024-38 | https://power-net.com.au/blog/how-team-mentality-helps-combat-it-security-threats/ | 2024-09-11T22:10:11Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651405.61/warc/CC-MAIN-20240911215612-20240912005612-00648.warc.gz | en | 0.945109 | 642 | 2.53125 | 3 |
DKIM, SPF and DMARC – Implement All Three For The Best Email Protection
How SPF, DKIM & DMARC enhance the credibility and deliverability of their emails.
Email spoofing is a cyberattack that can lead to losses not just for the victim but also the organization whose domains have been spoofed or compromised. Around 3.1 billion such domain spoofing messages are sent every day. The three pillars of email authentication, namely – SPF, DKIM, DMARC – prevent spoofing and improve email credibility and deliverability.
Spoofing tarnishes brand reputation and can get a domain blacklisted.
DMARC, DKIM, and SPF authenticate whether the server (IP address) sending an email is authorized to send that email on behalf of the domain. These thus protect brand reputation and ensure emails reach their intended destination. Read further to know how implementing SPF, DKIM, and DMARC is the gold standard in email authentication.
Table of Contents
What Is SPF?
Sender Policy Framework (SPF) is a DNS TXT record that specifies which IP addresses and servers are authorized to send an email on a domain’s behalf. If unauthorized servers send an email, the record can instruct receiving servers to send such emails to spam. SPF increases email deliverability by preventing spoofing and blacklisting.
What Is DKIM?
DKIM stands for DomainKeys Identified Mail. It is a TXT record added to the domain’s DNS and uses a pair of encryption keys: public and private, where emails are signed with the private keys. Receiving servers authenticate emails by seeing if a public-facing key matches a private key that only domain owners have. DKIM ensures that the integrity of an email has not been tampered with by any external party.
What Is DMARC?
DMARC also referred to as Domain-Based Message Authentication, Reporting, and Conformance is an email authentication policy and reporting protocol that relies on either SPF or DKIM. And hence, DMARC:
- It verifies that SPF and DKIM protect the emails.
- If both these authentication methods don’t pass, DMARC tells the receiving mail server what to do.
- It has a reporting element where domain owners can get reports about all emails sent with the domain in the “FROM” address. This feature helps identify falsified and spoofed emails.
DMARC ensures that the information in both SPF and DKIM records matches the ‘friendly from’ (firstname.lastname@example.org) domain that the user sees and the address (‘Mail From’) in the message header.
SPF Or DKIM
Organizations are recommended to use both SPF and DKIM for complete protection. SPF has a simple verification process that lets senders inform ISPs about what IP can send emails on their behalf. DKIM, meanwhile, allows ISPs to verify that the content of an email has not suffered tampering. Both are necessary.
DMARC Vs. DKIM
All three standards are necessary, with SPF and DKIM being more popular than DMARC. Domain administrators should ensure all three techniques are set up for the domains they manage. Having all three standards in place ensures that the best email protection is implemented. The three authentication methods work in tandem with each other. DMARC can be considered to be synergetic and enhances the security provided by DKIM and SPF. The reports provided by DMARC also help make actionable decisions to prevent further spoofing.
With emails being the primary means of corporate communication today, email-based spoofing and attacks are rising. Protection standards like SPF, DKIM, DMARC are necessary to ensure that genuine emails reach their destinations safely. Deploying these three email authentication methods goes a long way in preventing spoofing, spam, phishing, and other email security issues. | <urn:uuid:7894e075-6b4e-42a5-b418-2fa84294fa6c> | CC-MAIN-2024-38 | https://www.duocircle.com/resources/dkim-spf-and-dmarc | 2024-09-13T06:08:18Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651507.67/warc/CC-MAIN-20240913034233-20240913064233-00548.warc.gz | en | 0.917386 | 807 | 2.96875 | 3 |
AI TriSM: The Future of AI
In the fast-paced world of technology, the need for efficient service management is paramount. Enter AI TriSM, the cutting-edge approach poised to revolutionize how organizations handle their services. But what exactly is AI TriSM, why is it important, and how should businesses adapt to this innovative framework? Let’s delve into the details.
What is AI TriSM?
AI TriSM, short for Artificial Intelligence-enabled Service Management, combines the power of AI with traditional service management practices. It aims to enhance service delivery, improve efficiency, and optimize resource utilization through intelligent automation and data-driven insights.
Why is AI TriSM Important?
The significance of AI TriSM lies in its ability to streamline service management processes across various industries. By leveraging AI algorithms, organizations can automate repetitive tasks, predict potential issues before they arise, and provide proactive solutions to customers. This not only improves operational efficiency but also enhances customer satisfaction and loyalty.
According to a study by Gartner, organizations that deploy AI in their service management processes can reduce operational costs by up to 30% while increasing productivity by 40%.
AI TriSM Challenges and Updates
Despite its promising benefits, AI TriSM also faces challenges, including data privacy concerns, ethical considerations, and the risk of algorithmic bias. Organizations need to address these challenges by implementing robust data governance frameworks, ensuring transparency in AI decision-making processes, and regularly auditing AI models for fairness and accuracy.
In terms of new updates, AI TriSM is constantly evolving with advancements in AI technologies. From natural language processing for improved customer interactions to predictive analytics for better resource allocation, organizations are continuously integrating new AI capabilities into their service management practices.
AI Security & Privacy Risks
Like any transformative technology, AI TriSM comes with its own set of risks and challenges. Some of the key risks associated with AI TriSM include:
Data Privacy and Security
AI TriSM relies heavily on data to train algorithms and make informed decisions. However, this reliance on data raises concerns about data privacy and security. Organizations must ensure compliance with data protection regulations such as GDPR (General Data Protection Regulation) and implement robust security measures to safeguard sensitive information from unauthorized access or breaches.
AI TriSM algorithms may inadvertently perpetuate biases present in the data used for training, leading to unfair or discriminatory outcomes. Organizations must be vigilant in detecting and mitigating bias in AI models to ensure fair and equitable treatment for all stakeholders.
Algorithmic Transparency and Accountability
The complexity of AI algorithms used in TriSM may result in a lack of transparency and understanding of how decisions are made. This opacity can undermine trust and raise questions about accountability. Organizations must strive for transparency in their AI TriSM implementations, providing explanations for AI-generated recommendations and decisions to users and stakeholders.
Dependency and Overreliance
Overreliance on AI TriSM systems without human oversight can lead to complacency and diminished human decision-making capabilities. Organizations should maintain a balance between AI automation and human judgment, ensuring that humans remain in control and can intervene when necessary.
AI TriSM implementations may encounter technical challenges such as algorithmic complexity, scalability issues, and integration with existing systems. Organizations must invest in skilled personnel and robust infrastructure to overcome these challenges and ensure the smooth functioning of AI TriSM initiatives.
The deployment of AI TriSM may be subject to regulatory scrutiny and compliance requirements in various jurisdictions. Organizations must stay abreast of evolving regulatory landscape surrounding AI technologies and ensure adherence to relevant laws and regulations to mitigate regulatory risks.
Addressing these risks requires a proactive and holistic approach, encompassing robust governance frameworks, ethical guidelines, ongoing monitoring and evaluation, and stakeholder engagement. By recognizing and mitigating these risks, organizations can maximize the benefits of AI TriSM while minimizing potential pitfalls.
AI TriSM Security Controls
Implementing robust controls is essential to mitigate risks associated with AI TriSM and ensure responsible and effective deployment. Here’s a detailed explanation of the key controls needed or those already in place with AI TriSM:
Effective data governance is fundamental to AI TriSM. This includes establishing clear policies and procedures for data collection, storage, usage, and disposal. Organizations need to ensure data quality, integrity, and privacy throughout the AI TriSM lifecycle. Controls such as data encryption, access controls, and data anonymization techniques help safeguard sensitive information and comply with regulatory requirements.
Algorithm Transparency and Explainability
To enhance trust and accountability, AI TriSM systems must provide transparency and explainability regarding their decision-making processes. Controls such as model documentation, audit trails, and interpretability techniques enable stakeholders to understand how AI models reach conclusions and assess their reliability and fairness. Explainable AI methods, such as feature importance analysis and model-agnostic interpretability techniques, help demystify AI TriSM outputs and facilitate human oversight.
Bias Detection and Mitigation
AI TriSM algorithms may inadvertently perpetuate biases present in training data, leading to unfair or discriminatory outcomes. To address this risk, organizations need to implement controls for bias detection and mitigation. This includes conducting bias assessments, diversity audits, and fairness evaluations to identify and rectify bias in AI models. Techniques such as fairness-aware training, bias mitigation algorithms, and diverse dataset sampling help mitigate bias and promote equity in AI TriSM decision-making.
Human Oversight and Intervention
Despite the automation capabilities of AI TriSM, human oversight and intervention are crucial to ensure ethical and responsible deployment. Organizations should establish controls for human-in-the-loop processes, enabling human experts to review and override AI-generated recommendations when necessary. Human oversight mechanisms, such as escalation procedures, exception handling protocols, and decision support tools, help maintain control and accountability in AI TriSM operations.
Compliance with relevant laws, regulations, and industry standards is imperative for AI TriSM implementations. Organizations need to establish controls for regulatory compliance, including legal reviews, risk assessments, and compliance monitoring. Controls such as impact assessments, regulatory gap analysis, and documentation of legal obligations help ensure alignment with data protection, privacy, and ethical guidelines governing AI TriSM activities.
Continuous Monitoring and Evaluation
Ongoing monitoring and evaluation are essential to assess the performance, effectiveness, and impact of AI TriSM systems. Organizations should implement controls for continuous monitoring, including performance metrics tracking, anomaly detection, and feedback mechanisms. Regular audits, reviews, and assessments enable organizations to identify potential issues, measure compliance with controls, and drive continuous improvement in AI TriSM initiatives.
Ethical Guidelines and Governance Frameworks
Establishing clear ethical guidelines and governance frameworks is critical to guide responsible AI TriSM practices. Organizations should develop controls for ethical decision-making, including ethical principles, codes of conduct, and ethical review boards. Ethical impact assessments, stakeholder engagement, and ethical training programs help foster a culture of ethics and accountability within organizations.
By implementing these controls, organizations can effectively manage risks associated with AI TriSM and ensure its responsible and ethical deployment to realize its full potential in transforming service management practices.
Frameworks for AI TriSM Implementation
To successfully adopt AI TriSM, organizations should follow a structured approach:
- Assessment: Evaluate existing service management processes and identify areas where AI can add value.
- Data Preparation: Ensure data quality and accessibility for AI algorithms to generate meaningful insights.
- Model Development: Develop AI models tailored to specific service management tasks, such as incident resolution, demand forecasting, and resource allocation.
- Integration: Integrate AI capabilities into existing service management systems, ensuring seamless interoperability and user adoption.
- Monitoring and Optimization: Continuously monitor AI performance, gather feedback, and optimize models to adapt to changing business needs and customer requirements.
How Organizations Should Approach AI TriSM
Organizations embarking on the AI TriSM journey should prioritize collaboration between IT and business stakeholders, foster a culture of innovation and experimentation, and invest in employee training to ensure a smooth transition to AI-enabled service management.
Moreover, it’s essential to engage with AI TriSM vendors and partners who have domain expertise and a track record of successful implementations. By leveraging external expertise and resources, organizations can accelerate their AI TriSM initiatives and achieve tangible business outcomes more effectively.
The Future of AI TriSM
The future of AI TriSM holds exciting possibilities for revolutionizing service management practices across industries. Here’s a simplified overview of what we can expect:
AI TriSM will continue to advance automation capabilities, enabling organizations to streamline repetitive tasks, improve efficiency, and deliver faster and more responsive services. Through sophisticated AI algorithms, processes such as incident resolution, ticket routing, and resource allocation will become increasingly automated, freeing up human resources for more strategic and complex tasks.
AI TriSM will leverage predictive analytics to anticipate and preempt service disruptions, enabling organizations to adopt a proactive approach to service management. By analyzing historical data and patterns, AI TriSM systems will forecast potential issues before they occur, allowing organizations to take preventive measures and minimize downtime, thereby enhancing service reliability and customer satisfaction.
Personalized Service Delivery
AI TriSM will enable organizations to personalize service delivery based on individual customer preferences, behaviors, and needs. Through advanced data analytics and machine learning, AI TriSM systems will tailor service offerings, recommendations, and support channels to match the unique requirements of each customer, enhancing customer engagement and loyalty.
AI TriSM will augment human decision-making processes by providing real-time insights, recommendations, and contextual information. Through natural language processing and conversational AI interfaces, AI TriSM systems will empower service agents and business users to make informed decisions, resolve complex issues, and collaborate more effectively, ultimately driving better outcomes for both organizations and customers.
Ethical and Responsible AI
As AI TriSM becomes more pervasive, there will be a growing emphasis on ethical and responsible AI practices. Organizations will prioritize transparency, fairness, and accountability in AI TriSM deployments, implementing robust governance frameworks, ethical guidelines, and oversight mechanisms to ensure that AI systems operate ethically and align with societal values and expectations.
The future of AI TriSM will be characterized by collaborative ecosystems, where organizations collaborate with AI vendors, partners, and industry consortia to co-create innovative solutions and share best practices. By leveraging collective expertise and resources, organizations will accelerate AI TriSM adoption, drive interoperability, and unlock new opportunities for value creation and differentiation.
BigID’s Approach to AI TriSM
The future of AI TriSM holds immense potential for transforming service management practices, driving operational excellence, and delivering superior customer experiences. As organizations begin to embrace AI TriSM technologies and methodologies, they need flexible solutions tailored to their individual needs. BigID is the industry leading platform for data privacy, security, compliance, and AI data management that utilizes advanced machine learning and deep data discovery.
With BigID you can:
- Discover Data: Discover and catalog your sensitive data, including structured, semi-structured, and unstructured – in on-prem environments and across the cloud.
- Gain Complete Visibility: Automatically classify, categorize, tag, and label sensitive data with unmatched accuracy, granularity, and scale to build a cohesive data inventory to prepare for regulatory audits.
- Mitigate Data Access Risk: Proactively monitor, detect, and respond to unauthorized internal exposure, use, and suspicious activity around sensitive data.
- Streamline Remediation: BigID helps to define the remediation actions to provide audit records with integration to ticketing systems like Jira for seamless remediation workflows.
- Achieve Compliance: Automatically meet security, privacy, and AI compliance and frameworks globally, wherever data resides.
Book a 1:1 demo with our data and AI experts to see how BigID can help accelerate your organization’s initiative today. | <urn:uuid:f815ba81-2481-43bc-a077-14bbd5830adc> | CC-MAIN-2024-38 | https://bigid.com/blog/ai-trism-guide/ | 2024-09-16T21:35:04Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651714.51/warc/CC-MAIN-20240916212424-20240917002424-00248.warc.gz | en | 0.90419 | 2,410 | 2.703125 | 3 |
Email Security Intelligence - The Impact of Artificial and Human Intelligence on Email Security
- by Justice Levine
Artificial Intelligence (AI) has found its way out of science fiction and into reality, becoming highly prevalent in today's industries. AI aims to build and create intelligent systems capable of doing jobs people have been expected to take care of.
There is a lot of discourse regarding whether or not AI can adequately perform all of the functions it is programmed to do as expected. This article will discuss the potential impact of AI on the future of email security, how AI differs from Human Intelligence (HI), and how people’s roles change in the face of AI.
How Do Artificial Intelligence & Human Intelligence Differ?
Artificial Intelligence is a type of science that focuses on building intelligent machines capable of performing various tasks that typically require human Intelligence. These intelligent machines are comprised of knowledge from experience and historical data, analyzing their surrounding environments and performing befitting actions. AI combines several branches of science to leverage concepts and tools from multiple fields, such as computer science, cognitive science,
linguistics, psychology, neuroscience, and mathematics.
In contrast, human Intelligence refers to the intellectual capability that allows us to think, learn from different experiences, understand complex concepts, apply logic and reason, and effectively communicate. Human Intelligence is unique in that abstract emotion supports it. Human Intelligence is not limited to patterns and can be adjusted depending on the problems that arise, substantially changing with the nature of the situation.
The goal of human Intelligence is to adapt to new environments by utilizing a combination of different cognitive processes. Artificial Intelligence aims to build machines that imitate human behavior and perform human-like actions. Artificial Intelligence is built to solve problems quickly and efficiently, whereas Human Intelligence takes time to condition the mechanisms. The key difference between natural and Artificial Intelligence is the process of functionality and the time taken by both.
How Is AI Used in Cybercrime?
Threat actors are already taking advantage of AI in several ways. Non-native English speakers can rely on AI services to integrate ransomware and other email threats into victims’ systems. Al is also powered to use IoT devices in attacks, employ botnets in breaches, and identify computer system weaknesses in email security software. Since email threats can more easily be detected using AI, attackers are constantly crafting new mechanisms to utilize in phishing email attacks. They even prepare malicious spear phishing emails that bypass spam filters.
Researchers discovered a system that used “generative grammar” to create a large data set of email messages. Other AI servers can integrate antivirus services, find weaknesses in email security software and malware protection algorithms, and use hacking techniques like guessing passwords and analyzing data sets following a leak.
The spread of misinformation is growing as a trend due to AI technology, which is being used to fake information with malicious intent, which can then be exploited by cybercriminals globally. In 2019, cybercriminals used AI voice-generating software to impersonate the Chief Executive of a UK-based energy company to obtain $243,000 and distribute the transfers of the funds to bank accounts located in Mexico and other countries.
Further, cyberattacks based on AI systems are a growing trend identified by the European Cybercrime Centre (EC3) in a 2020 report. The EC3 stated, "Through AI, criminals may facilitate and improve their attacks by maximizing their opportunities for profit in a shorter period of time and create more innovative criminal business models while reducing the possibility of being traced and identified by criminal justice authorities."
Which Is The Better Solution?
AI can outperform humans in specific areas but still has a long way to go before it can match the human brain's capacity. AI requires more time to adjust to new situations, which can be problematic when AI is used as a cyber security tool in a fast-moving industry. Because new cyber and email threats emerge daily, AI must still learn to make logical judgments like humans in unexpected events. However, machine research is not always enough since new strains and attack types evolve daily.
When performed correctly, solutions allow AI and HI to work in tandem to mitigate email security issues. AI's speed and computing capabilities, alongside HI’s ability to verify that the correct data is being transferred, permit the two forms of intelligence to provide the best outcome possible. You can consider HI as a car driver, where AI keeps the driver at the right speed. If something goes wrong, AI relies on HI to care for it and then takes in data based on the outcome.
Impact of AI on Businesses
Artificial Intelligence provides several benefits for a business, including:
Automation of Tasks
The most obvious impact of AI is the automation of tasks across an extensive range of businesses, changing from manual to digital. Tasks or jobs that incorporate a level of reiteration or the utilization and translation of data are currently conveyed and handled by a computer, sometimes not requiring that a human intervene. This is why companies are now hiring AI prompt engineers to help improve productivity.
Welcome New Chances
As Artificial Intelligence and machine learning execute the manual assignments that no longer require a human to perform, they create opportunities and open doors for the labor force. Digital engineering is an example of an arising calling that transpired because of quick innovation and continued development.
Economic Growth Model
The development of AI should increase productivity growth, inherently increasing economic growth and providing new opportunities for international trade. Current rates of productivity growth globally are low, and various suggested causes exist. With international trade implications, AI will also affect the type and quality of economic growth. For instance, AI is likely to accelerate the transition toward services economies.
Role of Work
Rather than wiping out jobs, AI in the workplace is increasing workers' skill sets. Including Artificial Intelligence in the workforce can improve conditions. According to research, AI will help remove both conscious and unconscious biases in hiring staff. AI will also benefit employees by ensuring the appropriate safety gear is being worn using intelligent scanning technology.
More Opportunity for Creativity
AI-generated content can be of greater quality than that created by humans because AI models can learn from a large amount of data and identify patterns that humans may not be able to see.
African University Stops Cyberattack Using AI
In April 2022, a technology university in Africa stopped a cyberattack using Artificial Intelligence. Attackers attempted to distribute PrivateLoader malware, a pay-per-install service commonly associated with crypto mining and Intellectual Property (IP) theft. The public university receives government-funded research into AI, robotics, and sustainable energy solutions, prime targets for financially motivated cybercriminals and state-sponsored attackers.
The university was targeted during a trial of Darktrace AI in mid-April. The AI technology had formed an understanding of the university's normal operations across its digital estate, which allowed it to spot the odd activity that signified an attack. The AI detected a desktop connecting to a rare external endpoint using a mechanism inconsistent with their technology stack.
The IP address was tracked and found to be related to the service PrivateLoader. The compromised account and device were observed performing activity indicative of “RedLineStealer” and “MarsStealer,” information-stealing malware that exfiltrates data to monetize it through direct use or distribution on darknet sites. Luckily, the AI was able to detect the attack in its early stages, interrupting the threat before any critical research or student data could be compromised. After the attack was quarantined, an investigation into the incident was conducted to ensure future cyber resilience.
Keep Learning About Using AI as a Cybersecurity Tool in Protection Strategies
AI is a valuable cyber security tool shaping the industry and automation, which can become the norm across all sectors when coupled with intelligent workflow. While AI has almost mastered intelligent behavior, it still cannot simulate human thought processes, so AI's future must be governed mainly by people’s capabilities.
- Learn more about a comprehensive cloud email security software solution that uses Artificial Intelligence (AI), Open-Source Intelligence (OSINT), and Machine Learning (ML) to detect and block email threats in real-time.
- Prepare your business for cyberattacks to make sure employees stay safe online.
- Improve your company’s ability to protect against all threat types, attacks, and breaches by engaging in best practices for email security.
- Keeping the integrity of your email safe requires securing the cloud with spam filtering and enterprise-grade anti-spam services.
- Get the latest updates on how to stay safe online.
Must Read Blog Posts
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- Must Read - Microsoft 365 Email Security Limitations You Should Know in 2024
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- Practical Advice for Strengthening Cloud Email Security | <urn:uuid:a3511bda-bb8e-45a9-a1c9-ad3dc54374b6> | CC-MAIN-2024-38 | https://guardiandigital.com/resources/blog/artificial-vs-human-intelligence-for-email-security | 2024-09-18T04:25:48Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651836.76/warc/CC-MAIN-20240918032902-20240918062902-00148.warc.gz | en | 0.928774 | 2,004 | 2.71875 | 3 |
What are Deepfakes and How To Protect Against Them?
Deepfakes are high-tech social engineering attacks used by hackers to gain access to sensitive information. But what makes this tactic so efficient and difficult to detect? And more importantly, how can you protect your business against deepfakes?
What is a Deepfake?
A deepfake is an incredibly realistic piece of media created by altering existing video or audio material. Deepfakes use artificial intelligence to replicate a person’s face and voice. These tools are typically used to spread misinformation and create chaos in the targeted audience’s security system.
A quick search on YouTube will reveal hundreds of deepfakes of influential personalities like Barack Obama, Elon Musk, and Tom Cruise. But social engineering attacks like deepfakes are not only limited to celebrities—they also target businesses. Even though a trained observer may be able to spot a deepfake, several security breaches have been successfully supported using this technology.
How do Deepfakes work?
Deepfakes are created by feeding multiple images to deep-learning computer networks known as VAEs or Variational Autoencoders. VAE will try to capture the different lighting, position, and facial expressions of the provided photos to reconstruct a person’s facial expressions, resulting in a very realistic outcome.
Scammers follow these steps to be successful:
1. The hacker gets 2 groups of photos: photos of themselves (input images), and photos of the target that he/she is looking to impersonate.
2. The AI compares both images and decides which expressions are unique and essential to delivering a “trustworthy” impersonation, also known as “output images.”
3. Once the AI determines which facial features are essential, it combines the input and the output images using the VAE.
4. The AI then reconstructs each facial movement and emotional expression frame by frame.
Deepfakes and Cybersecurity
Cybercriminals are using deep fake technology to create havoc inside organizations. Bad actors usually use deepfakes for the following reasons:
3. Social Engineering
4. Identity Theft
5. Financial Fraud
6. Spreading Misinformation to Damage Business Reputation
How Can I Protect Against Deepfakes?
Unfortunately, there is no reliable software to detect deepfakes as the technology is evolving quickly. However, you may take the following steps during an attack to protect your sensitive information:
1. Have a Communication Response Plan
If you find yourself a victim of a deepfake attack, you must respond quickly. Having a response plan that instructs your company on how to communicate in case of a deepfake attack allows you to completely mitigate or decrease the damage done to your business reputation.
Your communications teams must be trained to deal with deepfake attacks and have a risk management protocol to deal with them.
One of the easiest ways to identify a deepfake is through shadows and skin tones. If you notice the person’s skin tone or shadows don’t match the scene, chances are you are witnessing a deepfake.
Weird eyes and soft and blurry areas are another giveaway when you are dealing with more professional deepfakes.
In this Tom Cruise deepfake, you will notice a weird line on his cheekbone. These flaws are more noticeable when the subject is moving or makes different facial expressions. When looking for audio hints, take a close look at the mouth. Most of the time the mouth does not match the audio. If the audio sounds suspicious, start doubting!
BTI: The Cybersecurity Partner Near You!
At BTI, we have more than 35 years of experience, in IT, security, and communications. We have the right expertise, qualifications, and security awareness training resources to help your team protect your business against deepfakes and all kinds of security threats. Would you like to focus on business profitable tasks without worrying about security? Contact us now to get the best security measures for a low price! | <urn:uuid:791eebbb-f58f-4304-b48f-539b0856ffc1> | CC-MAIN-2024-38 | https://www.btigroup.com/post/deepfakes | 2024-09-18T05:46:25Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651836.76/warc/CC-MAIN-20240918032902-20240918062902-00148.warc.gz | en | 0.926933 | 821 | 2.90625 | 3 |
So I've been doing a lot of wireless related stuff lately. Mainly audits of wireless environments. Lots of passive sniffing and packet analysis, so it's necessary to have a solid understanding of 802.11 Framing and the various packet types. By simply looking at the packets you can determine a great deal about the network in question.
A typical packet is made up of the following:
Frame Control [2 bytes] – This defines the options in the header fields and specifies the type of frame (management, data or control) in use. The frames format changes depending on the options specified in this Frame Control field.
Duration/ID [2 bytes] – This defines the amount time that the transmission medium is expected to be busy for the duration of the data transmission.
Address 1 [6 bytes] – This is the destination/receiving address.
Address 2 [6 bytes] - This is the source address. The address of the device that sent the frame.
Address 3 [6 bytes] – This is a filtering address. It is used to filter traffic on the same frequency as other BSS networks.
Sequence Control [2 bytes] – This is used for fragmentation in management and data frames and contains the sequence number and fragment number fields. Frames with payloads larger than 2312 bytes will be fragmented. Fragmentation is seldom used, as the maximum size of an Ethernet frame is 1500 bytes.
Address 4 [6 bytes] – This address is only used in WDS (Wireless Distribution Systems) to specify the source address. This is the station that sent the packet over the WDS.
Data Frame [variable] – This contains the payload. In management frames the structure is strictly ordered and contains fixed length parameters followed by variable length parameters in any order.
Frame Check Sequence [4 bytes] – This is a CRC32 checksum and is used to provide message integrity against accidental corruption of the frame in transit.
Obviously this is a very simple breakdown of an 802.11 frame.
In the Frame Control header field, which defines the options for the remainder of the header fields, there are two bits called the ‘To DS’ and ‘From DS’ bits. These are the 8th and 9th bits respectively. The To Distribution System and From Distribution bits are important for analysis as, depending on the combination of these flags, they identify the type of network the packet originated from.
The distribution system can have various definitions but it’s easiest to define the distribution system as that which connects the wireless network to other networks. In most cases this will be the wired network. By looking at which bit is set we can determine the source and destination MAC addresses in use.
To DS bit is set – The packet is coming from a wireless station to the wired network
From DS bit is set – The packet is coming from the wired network, or possibly the AP itself and is destined for a wireless station.
From DS and To DS are cleared – The packet is from an Ad-hoc network.
From DS and To DS are set – The packet is from a WDS network. Most often a WDS network is used to connect networks together. An example would be a bridge between buildings.
WDS networks are the only ones that will have a value set for all four address fields. When analyzing a packet from a WDS network it is important that you don’t mix up the Receiver Address (address 1), the Transmitter Address (Address 2), the Destination Address (Address 3) and the Source Address (Address 4).
The Receiver Address is the MAC address of the device at one end of a WDS network (I.e.: a bridge) that bridges the wireless connection to the wired network.
The Transmitter Address is the MAC address of the device at the other end of the WDS network that bridges the traffic from the wired network to the wireless network.
Node ←→Wired Network ←→ AP/bridge ←→ AP/bridge ←→ Wireless Network ←→ Node
The Transmitter and Receiver neither create the frame or are the intended recipient of the frame, they merely receive and forward the frame on. The frame is created by the device identified by the MAC address in the source address field. The destination address field identifies the final recipient of the frame.
Hopefully this has clarified how addressing works in a 802.11 frame. | <urn:uuid:1f5c089d-049e-49d7-bdee-a3bea953dc07> | CC-MAIN-2024-38 | https://blog.carnal0wnage.com/2007/05/addressing-in-80211-frames.html | 2024-09-19T10:33:54Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652028.28/warc/CC-MAIN-20240919093719-20240919123719-00048.warc.gz | en | 0.924432 | 906 | 2.953125 | 3 |
The FETCH statement retrieves the results of the SELECT statement that is executed when a cursor is opened. When a cursor is opened, the cursor is positioned immediately before the first result row. The FETCH statement advances the cursor to the first (or next) row and loads the values in that row into the specified variables. Each FETCH statement advances the cursor one row.
There must be a one-to-one correspondence between variables specified in the INTO or USING clause of FETCH and expressions in the SELECT clause of the DECLARE CURSOR statement. If the number of variables does not match the number of expressions, the preprocessor generates a warning and, at runtime, the SQLCA variable sqlwarn3 is set to W.
The variables listed in the INTO clause can include structures that substitute for some or all of the variables. The structure is expanded by the preprocessor into the names of its individual variables; therefore, placing a structure name in the INTO clause is equivalent to enumerating all members of the structure in the order in which they were declared.
The variables listed in the INTO clause or within the descriptor must be type-compatible with the values being retrieved. If a result expression is nullable, the host language variable that receives that value must have an associated null indicator.
If the statement does not fetch a row—a condition that occurs after all rows in the set have been processed—the sqlcode of the SQLCA is set to 100 (condition not found) and no values are assigned to the variables.
The statement must be terminated according to the rules of the host language. | <urn:uuid:50b64b79-9c20-4448-8458-c615630067ff> | CC-MAIN-2024-38 | https://docs.actian.com/ingres/10S/OpenSQL/Description_22.htm | 2024-09-19T10:47:32Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652028.28/warc/CC-MAIN-20240919093719-20240919123719-00048.warc.gz | en | 0.907856 | 334 | 2.71875 | 3 |
In today’s rapidly evolving educational landscape, digital teaching resources have become integral to creating dynamic and effective learning environments. At Document Solutions Inc. (DSI), we provide cutting-edge office technology IT services in New Mexico, including the OneScreen interactive whiteboards, to support schools and educators. OneScreen offers comprehensive training from engineers to ensure that teachers can maximize the potential of these innovative tools. Let’s explore how digital teaching resources like OneScreen can transform your classroom.
Classroom Tech Tools for Effective Learning
Integrating classroom tech tools into your teaching strategy can significantly enhance the learning experience. These tools provide interactive, engaging, and flexible ways to present and absorb information. OneScreen’s interactive whiteboards are a prime example of how technology can be seamlessly incorporated into the classroom.
Key Classroom Tech Tools:
- Interactive Whiteboards: Serve as dynamic teaching platforms that allow for interactive lessons, multimedia presentations, and collaborative activities.
- Document Cameras: Enable the projection of physical documents and objects onto a large screen, making it easier to share materials with the whole class.
- Student Response Systems: Facilitate real-time feedback and engagement through devices that allow students to participate in polls, quizzes, and discussions.
- Educational Software: Includes a range of applications and programs designed to support teaching and learning across various subjects and grade levels.
These classroom tech tools are essential for creating an interactive and responsive learning environment that caters to the needs of all students.
Benefits of Smart Boards in the Classroom
Smart boards, or interactive whiteboards, offer numerous benefits that enhance both teaching and learning experiences. Here are some of the key benefits of smart boards in the classroom:
- Interactive Lessons: Smart boards allow teachers to create engaging lessons that incorporate touch, movement, and multimedia, keeping students actively involved.
- Visual Learning: High-definition displays make visual learning more impactful, helping students to better understand and retain complex information.
- Group Work: Multiple students can interact with the board simultaneously, facilitating group activities and collaborative problem-solving.
- Real-Time Feedback: Teachers can provide immediate feedback, helping students to quickly understand and correct mistakes.
Flexibility and Adaptability:
- Versatile Teaching: Smart boards support a wide range of teaching styles and methods, from traditional lectures to flipped classrooms and blended learning.
- Integration with Other Technologies: They can easily connect with other devices and platforms, enhancing the overall functionality and scope of classroom technology.
The benefits of smart boards in the classroom make them invaluable tools for modern education. They can help promote engagement, collaboration, and flexible learning.
How to Work With Interactive Panels in Classrooms
Working with interactive panels in classrooms can seem daunting at first, but with the right approach and training, teachers can quickly become proficient in using these powerful tools. Here’s a guide on how to work with interactive panels effectively:
- Set Up and Calibration: Begin by setting up the panel according to the manufacturer’s instructions and calibrating it for accurate touch response.
- Familiarize Yourself with the Software: Spend time exploring the interactive software that comes with the panel, learning how to use its features for lesson planning and delivery.
- Create Interactive Lessons: Use the panel to develop lessons that incorporate various media, interactive activities, and real-time feedback.
- Encourage Student Interaction: Allow students to engage with the panel during lessons, using it for activities such as solving problems, drawing diagrams, or participating in quizzes.
- Integrate Other Tools: Combine the panel with other classroom technologies, such as document cameras or student response systems, to enhance the learning experience.
- Leverage Online Resources: Access a wealth of online resources and applications that can be used directly on the panel to support and enrich your lessons.
Learning how to work with interactive panels in classrooms involves both mastering the technology and integrating it into your teaching practices to create engaging and effective learning experiences.
Receive Training From a OneScreen Engineer
To fully realize the potential of digital teaching resources like OneScreen interactive whiteboards, it’s crucial to receive proper training. OneScreen offers comprehensive training sessions so that you can get unlimited on-demand FREE support and training from the actual engineers of the device.
Benefits of OneScreen Engineer Training:
- Hands-On Experience: Gain practical, hands-on experience with the interactive whiteboard and its software.
- Customized Learning: Training sessions can be tailored to meet the specific needs and goals of your classroom or school.
- Expert Guidance: Learn from experts who can provide tips, best practices, and troubleshooting advice.
- Ongoing Support: Access continuous support and resources to help you integrate the technology smoothly into your teaching routine.
Receiving training from a OneScreen engineer ensures that you and your team are confident and proficient in using digital teaching resources to enhance the educational experience.
For more information on digital teaching resources and how to maximize their potential with professional training, contact Document Solutions Inc. (DSI). Our team is dedicated to providing top-quality technology solutions and support to schools in New Mexico and El Paso, TX. Contact DSI for a free immersive A/V demo today.
Jocelyn Gorman, the Executive Vice President of DSI, possesses a deep understanding of the unique requirements of growing businesses. With over a decade of experience collaborating with clients across various industries, she closely collaborates with her Sales Team to develop and implement tailored technology solutions. These solutions aim to enhance office productivity and minimize operational costs. Her remarkable ability to effectively address business challenges has garnered recognition from prestigious publications such as the Cannata Report and Family Business Magazine. | <urn:uuid:1cd82ef2-c161-4f7e-93a7-76572c5e482c> | CC-MAIN-2024-38 | https://www.dsinm.com/digital-teaching-resources-training-from-onescreen-engineer/ | 2024-09-19T09:52:45Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652028.28/warc/CC-MAIN-20240919093719-20240919123719-00048.warc.gz | en | 0.923177 | 1,166 | 2.625 | 3 |
In recent years, cyberattacks targeting hospitals and healthcare systems have been increasing at an alarming rate, highlighting major vulnerabilities in the cyber defenses of the sector. These attacks have wide-ranging impacts on patient treatment, safety, and sensitive medical data. Two recent incidents at hospitals in New York underscore the disruptions and risks caused by the rise in cyber threats.
Just this month, Margaretville Hospital and HealthAlliance Hospital in New York suffered a cyberattack that forced them to completely shut down their IT systems. With systems locked down, the hospitals had to divert ambulances and discharge current patients to other facilities. This mirrors an incident in August where a cyberattack affected hospitals in five states, also prompting systemwide computer shutdowns.
These attacks contribute to an overall trend of cybercriminals aggressively taking aim at healthcare organizations. According to FBI data, the agency was investigating around 100 cyber incidents targeting the healthcare sector in 2021 alone. Many of these involve ransomware, where attackers encrypt systems and demand payment to decrypt them. Across the industry, 45 million patient records were breached in 2021, up 55% from the previous year.
Hospitals and clinics make attractive targets due to the sensitive medical data they house and the critical nature of their services. Patient treatment frequently ends up affected. In two high-profile cases, hospitals had to close their emergency rooms and divert patients due to cyberattacks. In one incident, a diverted patient died as the increased distance to the alternate hospital delayed treatment.
Beyond immediate risks from diversions and shutdowns, cyberattacks cause appointment cancellations, treatment delays, administrative disruptions, and lost access to patient data. The average healthcare organization now spends over $3.5 million annually on cybersecurity. However, antiquated systems containing gaps in security remain common. Tighter regulations have been proposed to push healthcare systems to modernize defenses.
Cybercriminals are growing more sophisticated as security measures lag behind. Until cybersecurity is elevated to match current threats, patients remain at risk from attacks exploiting vulnerable healthcare institutions. Hospitals and clinics still have widespread work to do beefing up their protections, assessing risks, updating systems, and training staff. Otherwise these attacks will persist, jeopardizing patient health through treatment disruptions, data loss, and safety risks.
In a hybrid work world, an effective balance between flexibility, productivity, and robust cybersecurity measures is crucial. Without it, businesses face a ticking time bomb of security threats. As businesses continue to navigate the challenges of the hybrid work model, partnership with a skilled MSP is no longer a luxury but a necessity to stay secure and in business. Protecting yourself is getting tougher but must be done to keep your business or government agency, school, state, city, etc. running. Ask the Hybrid Work Experts at Apex Technology Services about how they can help your organization stay secure. | <urn:uuid:4bade380-9de0-4c51-86ee-3c92bfe7c83a> | CC-MAIN-2024-38 | https://www.apextechservices.com/topics/articles/457506-cyberattacks-healthcare-systems-surge-exposing-dangerous-gaps-cybersecurity.htm | 2024-09-20T13:25:05Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652278.82/warc/CC-MAIN-20240920122604-20240920152604-00848.warc.gz | en | 0.955415 | 567 | 2.859375 | 3 |
Last month, we looked at some of the changes coming in the CompTIA A+ exams as they are being updated. The new exams (to be named 220-901 and 220-902) are expected by the end of the year and one of the topics being added is that of Basic Linux commands. Due to space constraints, approximately half of the commands were covered and this month we look at the rest of the basic Linux commands CompTIA wants you to be familiar with for the upcoming A+ certification exams.
Changing Permissions and Ownership
You may need to change a file's permission settings to protect it from others. Use the chmod command to change the permission settings of a file or a directory. To use chmod effectively, you have to specify the permission settings. A good way is to concatenate letters from the columns of the following table in the order shown (Who/Action/Permission). You use only the single character from each column "��the text in parentheses is for explanation only.
Letter Codes for File Permissions
WhoActionPermissionu (user)+ (add)r (read)g (group)- (remove)w (write)o (others)= (assign)x (execute)a (all)s (set user ID)
For example, to give everyone read access to all files in a directory, pick a (for all) from the first column, + (for add) from the second column, and r (for read) from the third column to come up with the permission setting a+r. Then use the set of options with chmod, like this:
chmod a+r *.
On the other hand, to permit everyone to execute one specific file, enter:
chmod a+x filename
Then type ls -l to verify that the change took place.
Another way to specify a permission setting with chmod is to use a three-digit sequence of numbers. In a detailed listing, the read, write, and execute permission settings for the user, group, and others appear as the sequence ...
... and dashes will appear in place of letters for disallowed operations. Given that, you should think of "rwxrwxrwx" as three occurrences of the string "rwx." Now assign the values r=4, w=2, and x=1.
To get the value of the sequence rwx, simply add the values of r, w, and x (4+2+1=7). With this formula, you can assign a three-digit value to any permission setting. For example, if the user can read and write the file but everyone else can only read the file, then the permission setting is rw-r--r-- (that's how it appears in the listing), and the value is 644. Thus, if you want all files in a directory to be readable by everyone but writable only by the user, use the following command:
chmod 644 *
The following table shows some common permissions and values.
Common File Permissions
Sometimes you have to change a file's user or group ownership for everything to work correctly. For example, suppose you're instructed� to create a directory named "cups" and give it the ownership of user ID lp and group ID sys. You can log in as root and create the "cups" directory with the command mkdir:
If you check the file's details with the ls -l command, you see that the user and group ownership is root root. To change the owner, use the chown command. For example, to change the ownership of the "cups" directory to user ID lp and group ID sys, type
chown lp.sys cups
Working with Files
To copy files from one directory to another, use the cp command. If you want to copy a file to the current directory, but retain the original name, use a period (.) as the second argument of the cp command. Thus, the following command copies the Xresources file from the /etc/X11 directory to the current directory (denoted by a single period):
cp /etc/X11/Xresources .
The cp command makes a new copy of a file and leaves the original intact.
If you want to copy the entire contents of a directory "��including all subdirectories and their contents "��to another directory, use the command cp -ar sourcedir destdir. This command copies everything in the sourcedir directory to destdir. For example, to copy all files from the "/etc/X11" directory to the current directory, type the following command:
cp -ar /etc/X11 .
To move a file to a new location, use the mv command. The original copy is gone, and a new copy appears at the destination. You can use mv to rename a file. If you want to change the name of today.list to old.list, use the mv command, as follows:
mv today.list old.list
On the other hand, if you want to move the today.list file to a subdirectory named "saved," use this command:
mv today.list saved
An interesting feature of mv is that you can use it to move entire directories (with all their subdirectories and files) to a new location. If you have a directory named data that contains many files and subdirectories, then you can move that entire directory structure to "old_data" by using the following command:
mv data old_data
To delete files, use the rm command. For example, to delete a file named old.list, type the following command:
Be careful with the rm command "��especially when you log in as root. You can inadvertently delete important files with rm.
Working with Directories
To organize files in your home directory, you have to create new directories. Use the mkdir command to create a directory. For example, to create a directory named "images" in the current directory, type the following:
After you create the directory, you can use the cd images command to change to that directory.
You can create an entire directory tree by using the "-p" option with the mkdir command. For example, suppose your system has a "/usr/src" directory and you want to create the directory tree "/usr/src/book/java/examples/applets." To create this directory hierarchy, type the following command:
mkdir -p /usr/src/book/java/examples/applets
When you no longer need a directory, use the rmdir command to delete it. You can delete a directory only when the directory is empty. To remove an empty directory tree, you can use the "-p" option, like this:
rmdir -p /usr/src/book/java/examples/applets
This command removes the empty parent directories of applets. The command stops when it encounters a directory that's not empty.
Just as you can use the ipconfig command to see the status of IP configuration with Windows, the ifconfig command can be used in Linux. You can get information about the usage of the ifconfig command by using "ifconfig -help." The following output provides an example of the basic ifconfig command run on a Linux system:
eth0����� Link encap:Ethernet� HWaddr 00:60:08:17:63:A0
inet addr:192.168.1.101� Bcast:192.168.1.255� Mask:255.255.255.0
UP BROADCAST RUNNING� MTU:1500� Metric:1
RX packets:911 errors:0 dropped:0 overruns:0 frame:0
TX packets:804 errors:0 dropped:0 overruns:0 carrier:0
Interrupt:5 Base address:0xe400
lo������� Link encap:Local Loopback
inet addr:127.0.0.1� Mask:255.0.0.0
UP LOOPBACK RUNNING� MTU:3924� Metric:1
RX packets:18 errors:0 dropped:0 overruns:0 frame:0
TX packets:18 errors:0 dropped:0 overruns:0 carrier:0
In addition to ifconfig, Linux users can use the iwconfig command to view the state of a�wireless network. Using iwconfig, you can view such important information as the link quality, AP MAC address, data rate, and encryption keys, which can be helpful in ensuring that the parameters in the network are consistent.
Having concluded looking at the basic Linux commands CompTIA wants you to be familiar with for the upcoming A+ certification exams, we will next turn our�focus to Windows 8/8.1. | <urn:uuid:9975f4b2-e467-4fd5-8f6b-d5a0ae3df86d> | CC-MAIN-2024-38 | https://www.certmag.com/articles/basic-linux-commands-need-know-comptias-new-2 | 2024-09-20T13:43:41Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652278.82/warc/CC-MAIN-20240920122604-20240920152604-00848.warc.gz | en | 0.855632 | 1,857 | 3.203125 | 3 |
Shining a Light: Combating Darknet Risks to Brands
In today's digital age, the internet is a vital part of our lives, offering access to endless information and opportunities. Yet, beneath its surface lies a hidden, more sinister space: the dark web. This obscure network presents significant risks to brands, making it essential for companies to recognize and shield themselves from the dangers that lurk within.
Cybercriminals exploit the anonymity and encryption of the dark web to trade stolen data, such as login credentials, credit card information, and intellectual property. The volume of compromised data circulating in this shadowy realm is vast, with billions of credentials believed to be available.
Despite its complexities and obscurity, dismissing the dark web's threats can be perilous. Operating beyond regular web browsing and search engines, the dark web is not well understood by many, contributing to a dangerous complacency. This lack of awareness can allow dark web-originated threats to go unnoticed and unaddressed, posing a continuous risk to individuals and organizations alike.
What is the Dark Web exactly?
The internet is broadly divided into three main layers: the clearnet, the deep web, and the dark web. The clearnet is the part of the internet most familiar to us, comprising all the searchable sites indexed by search engines like Google, Bing, or Yahoo. These are the publicly accessible websites we all visit every day.
Beyond the clearnet lies the deep web, which includes all the content that search engines cannot index. This includes private databases, intranets, and password-protected areas not accessible to the general public - but are not necessarily illegal or nefarious.
A smaller, more concealed part of the deep web is known as the dark web. This segment is intentionally hidden and requires specific software and encryption techniques to access. The dark web is often associated with illegal activities, including but not limited to cybercrime
Here's a simple diagram to illustrate these parts of the internet:
The dark web utilizes a technique called onion routing: the layering of encryption to secure internet traffic through multiple nodes, obscuring the origin and destination of data. While this technology offers privacy protection, it also facilitates the growth of illicit activities by shielding users from detection.
To access the dark web, users must employ specialized software like Tor (The Onion Router), which conceals their identity and encrypts their internet traffic. Many users also combine Tor with VPNs and virtual machines for added layers of anonymity and security.
Threats to Brands on the Dark Web
The dark web presents diverse threats, categorized into three main types of attacks that target both individuals and companies:
Data Leaks and Sales:
Cyber threats can impact both individuals and organizations in devastating ways. For individuals, threat actors often access and trade Personal Identifiable Information (PII), leaving people vulnerable to identity theft, privacy breaches, and significant financial losses. Such incidents can drastically undermine the trust and reputation of the brands involved.
For organizations, the consequences of leaked corporate credentials and sensitive documents are profound. Unauthorized access to accounts and the exposure of critical intellectual property and business strategies can lead to major security breaches. Not only does this compromise the security of the organization, but it also gives competitors potentially unfair advantages.
Moreover, cybercriminals are increasingly using ransomware to encrypt a brand's data, adding another layer of threat. This method locks companies out of their own data and demands payment, further amplifying the risks and potential damages associated with cyber attacks.
Phishing kits: are pre-packaged tools crafted by threat actors to impersonate legitimate brands and deceive customers into providing personal information, resulting in identity theft and financial losses. This not only tarnishes a brand's trustworthiness but is akin to selling guns to terrorists, as it equips malicious entities with the tools they need to inflict damage and chaos.
DDoS Attacks: Apart from being used for extortion, DDoS attacks are also deployed directly to sabotage a company's online services, resulting in operational disruptions and financial detriment.
By comprehending these threats and their implications, brands can better strategize their cybersecurity measures to protect both their and their customers' interests effectively.
AT&T Fell Victim to Dark Web Attacks
Telecommunications giant AT&T suffered a significant data breach affecting over 70 million customers, where personal information such as social security numbers, names, addresses, and account details was leaked on the dark web. The breach is especially significant given AT&T's status as a global telco giant that invests tremendous resources in cybersecurity. This underscores ongoing vulnerabilities in cybersecurity and in particular the utility of the dark web for such threat actors. Consequently, considering this domain is necessary as part of a well-rounded and dynamic cybersecurity strategy.
Protecting Your Brand with BrandShield
BrandShield's Dark Web Monitoring solution dives into the internet's hidden corners to identify and neutralize threats to your brand’s reputation. By using a comprehensive approach that combines advanced scraping techniques, APIs, and human intelligence, BrandShield explores various dark web sources, including specialized forums and websites, to analyze and distill vast data into actionable insights for your security team.
BrandShield’s Darkweb monitoring covers a wide range of risks, from leaked credentials and sensitive personal data to intellectual property and ransomware-damaged documents, tracking secretive communication threads and infiltrating deep web communities to offer early warnings of credential theft, data breaches, and other malicious actions, enabling swift and effective responses.
BrandShield provides critical visibility into the dark web's covert networks, enhancing defenses and protecting your organizations' most valuable assets, confidently navigating dark web complexities and combating digital threats.
Protect your brand from dark web threats and contact us today. | <urn:uuid:78598801-98a8-43c8-990a-d05e5868d2c9> | CC-MAIN-2024-38 | https://blog.brandshield.com/combatting-darknet-risks-to-brands | 2024-09-10T20:50:51Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651318.34/warc/CC-MAIN-20240910192923-20240910222923-00848.warc.gz | en | 0.916113 | 1,160 | 2.859375 | 3 |
Computer theft can happen to anyone, any place, and any time. There are people who deem their data more valuable than their computer. This data can be corporate secrets, client information, personal information, etc. There is a one way everyone can protect their data if their computer was ever stolen. This process is called “encryption”. Encryption is not a new thing, it’s been used for a long time. Encryption works of algorithms, mathematics calculations. Each encryption method works differently, one is weaker, another is stronger, one performs faster, and the other one could be slower but more efficient.
Encryption is the process of scrambling the data. A key is assigned to the data, which is the password to access the data. With the encryption process, you could give your data to someone, or someone could potentially steal it, but they wouldn’t be able to read any part of it without your key. Once the key is entered, the data is decrypted and it could be read in plain text. For example, you can password protect a word document; no one will be able to read it without the password.
There are a few ways one can start working in an encrypted environment. Most operating systems now support encryption. With Mac OS you can encrypt the entire hard drive using the builtin FileVault application that comes with Mac OS. Some argue its not as secure or fast as other tools, but it’s a start. Windows 7 does feature an encryption service called BitLocker. However BitLocker is only available on the Enterprise and Ultimate editions, which are generally more expensive. Windows 8 also features BitLocker, available to the Pro and Enterprise editions. The issue with BitLocker is the backdoor. Microsoft has built in a backdoor, which Microsoft and government agencies can use to decrypt an encrypted computer if one was ever seized. BitLocker can work in a few different fashions. The most secure fashion is having a TPM (Trusted Protection Module) installed on the computer, when it was purchased. A TPM is a special chip that is installed on the computers main board. The second part alongside a TPM is to require the user to insert a special flash drive to the computer upon each startup. If the computer were stolen, but not the flash drive, the thief would have no access to the data at all. The user has the ability to encrypt some of his data or all of it. Encrypting the entire hard drive is the best method.
TrueCrypt is one great application, which has no backdoors and is completely free, this way you won’t have to worry about which edition of Windows you have. The best part is that it also works with Macs. TrueCrypt can create various encryption solutions. One can make a container which is encrypted, and will look like another hard drive, when mounted. Although it’s just one simple file which needs a password to be accessed? Same as BitLocker, TrueCrypt can also encrypt the entire hard drive, requiring the user to enter a password upon each startup.
It all comes down to how much protection you want and if you need it. If you work with sensitive data and cannot afford that data to be leaked out in any way, shape or form, you may want to think about some sort of encryption plans in the future.
For more info contact us at Group 4 Networks | <urn:uuid:aad10eee-39d7-4674-9d81-ce60779dfc4a> | CC-MAIN-2024-38 | https://g4ns.com/computer-encryption/ | 2024-09-10T21:44:35Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651318.34/warc/CC-MAIN-20240910192923-20240910222923-00848.warc.gz | en | 0.962361 | 701 | 3.390625 | 3 |
Databases have been used by various organizations to solve business problems for a very long time. In the early days, databases used to be flat files, which meant that data was stored in flat files. However, this approach made it difficult to search for information or generate specific reports from a set of fields.
To resolve these concerns, a relational model of databases was proposed by a researcher from IBM, E.F Codd. Slowly this model of database gained momentum due to the various advantages it offered to organizations. Over the years, various relational database management systems, aka RDBMSs, have been made by open source communities and enterprises to store and manage them to solve business problems.
In this article, we will explore relational databases by going through their history, use cases, discussing SQL and look into various relational databases available these days.
What Is a Relational Database?
A relational database is a form of database in which a collection of data is stored as rows and columns inside tables. Each row defines a new record, and a field is a column that represents a specific property. A row or record can be uniquely identified in a table with the help of primary keys. Records in multiple tables can be correlated in a relational database with the help of foreign keys. We use SQL (structured query language ) to work with relational databases.
History of Relational Database
In 1970, the term relational databases was first coined by E.F.Codd in his research paper titled “A Relational Model of Data for Large Shared Data Banks”. Subsequently, Codd is considered the inventor of relational databases. By 1974, IBM came up with a prototype of an RDBMS called System R, and with time and advancement of technology, various other RDBMSs started coming up in the market. Oracle database became the first commercial version launched in the year 1979 by Oracle Corporation.
What Is SQL?
As discussed earlier, SQL is a query language that lets us work with our databases. We can perform operations like creating a database, deleting a database, creating a table, inserting records in the table, updating existing records, deleting records, or executing queries to fetch a specific result set from the database. SQL became ANSI standard in 1986 and ISO in 1987. Although some of the popular relational databases have their own versions of SQL, they support all the major commands.
Benefits of Using Relational Databases
- Scalability – Irrespective of the number of rows or fields, a relational database can enlarge to enhance its usability.
- Querying Capability – We can perform complex queries to get desired results with the help of SQL.
- Data Integrity – With the help of relational constraints and strong data types, we can enforce the integrity of our data in a relational database.
- Security – We can restrict access to our data to specific users as per our requirements.
Popular Relational Databases
- SQL Server
SQL Server is the first relational database we will be encountering today. You might have heard of this one.
It is a popular database management system developed by Microsoft. It was first launched in 1989 and has been growing throughout the years by adding new features. It is mostly used for large-scale enterprise applications. It comes with different variants like Enterprise and Express editions.
If you are still learning about relational databases, you might be wondering: What is PostgreSQL? I have never heard of it!
It is an open source RDBMS. It started as the POSTGRES project at the University of California in 1986. It is being developed and maintained by the PostgreSQL Global Development Group. It runs on all major operating systems and contains 170 of the 179 mandatory features for SQL:2016 Core Conformance.
MySQL is another very popular relational database and a must-know for people who are in the field.
It is an open source RDBMS that uses SQL standard. It is supported by Oracle and is ideal for both small and large applications. It is an easy-to-use, fast, and scalable relational database. It is widely used as a database for web applications built with PHP but has other use cases too.
Relational databases have been at the center of application development for the last few decades for storing, managing, and processing data. It provides an efficient mechanism to maintain the integrity of the RDBMS by enforcing constraints and reducing data redundancy with the help of data normalizations. Furthermore, we can perform complex queries on our data in relational databases by using SQL.
There are many relational databases, some proprietary and others open source. It is an integral part of modern application development. | <urn:uuid:3f4818fb-c74e-4e65-9464-aa85bc8d9e51> | CC-MAIN-2024-38 | https://kalilinuxtutorials.com/guide-to-relational-databases/ | 2024-09-14T14:17:40Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651579.38/warc/CC-MAIN-20240914125424-20240914155424-00548.warc.gz | en | 0.946715 | 946 | 3.375 | 3 |
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Deep Learning enjoys a massive hype at the moment. People want to use Neural Networks everywhere, but are they always the right choice? That will be discussed in the following sections, along with why Deep Learning is so popular right now. After reading it, you will know the main disadvantages of Neural Networks and you will have a rough guideline when it comes to choosing the right type of algorithm for your current Machine Learning problem. You will also learn about what I think is one of the major problems in Machine Learning we are facing right now.
Table of Contents:
- Why Deep Learning is so hyped
- Computational Power
- Neural Networks vs. traditional Algorithms
- Black Box
- Duration of Development
- Amount of Data
- Computationally Expensive
Why Deep Learning is so hyped
Deep Learning enjoys its current hype for four main reasons. These are data, computational power, the algorithms itself and marketing. We will discuss each of them in the following sections.
One of the things that increased the popularity of Deep Learning is the massive amount of data that is available in 2018, which has been gathered over the last years and decades. This enables Neural Networks to really show their potential since they get better the more data you fed into them.
In comparison, traditional Machine Learning algorithms will certainly reach a level, where more data doesn’t improve their performance. The chart below illustrates that perfectly:
2. Computational Power
Another very important reason is the computational power that is available nowadays, which enables us to process more data. According to Ray Kurzweil, a leading figure in Artificial Intelligence, computational power is multiplied by a constant factor for each unit of time (e.g., doubling every year) rather than just being added to incrementally. This means that computational power is increasing exponentially.
The third factor that increased the popularity of Deep Learning is the advances that have been made in the algorithms itself. These recent breakthroughs in the development of algorithms are mostly due to making them run much faster than before, which makes it possible to use more and more data.
Also important was marketing. Neural Networks are around for decades (proposed in 1944 for the first time) and already faced some hypes but also times where no one wanted to believe and invest in it. The phrase „Deep Learning“ gave it a new fancy name, which made a new hype possible, which is also the reason why many people wrongly think that Deep Learning is a newly created field.
Also, other things contributed to the marketing of deep learning, like for example the controversial „humanoid“ robot Sophia from Hanson robotics and several breakthroughs in major fields of Machine Learning that made it into mass-media and much more.
Neural Networks vs. traditional Algorithms
When you should use Neural Networks or traditional Machine Learning algorithms is a hard question to answer because it depends heavily on the problem you are trying to solve. This is also due to the „no free lunch theorem“, which roughly states that there is no „perfect“ Machine Learning algorithm that will perform well at any problem. For every problem, a certain method is suited and achieves good results while another method fails heavily. But I personally see this as one of the most interesting parts of Machine Learning. It is also the reason why you need to be proficient with several algorithms and why getting your hands dirty through practice is the only way to get a good Machine Learning Engineer or Data Scientist. Nevertheless, I will provide you some guidelines in this post that should help you to better understand when you should use which type of algorithm.
The main advantage of Neural Network lies in their ability to outperform nearly every other Machine Learning algorithms, but this goes along with some disadvantages that we will discuss and lay our focus on during this post. Like I already mentioned, to decide whether or not you should use Deep Learning depends mostly on the problem you are trying to solve with it. For example, in cancer detection, a high performance is crucial because the better the performance is the more people can be treated. But there are also Machine Learning problems where a traditional algorithm delivers a more than satisfying result.
1. Black Box
The probably best-known disadvantage of Neural Networks is their “black box” nature, meaning that you don’t know how and why your NN came up with a certain output. For example, when you put in an image of a cat into a neural network and it predicts it to be a car, it is very hard to understand what caused it to came up with this prediction. When you have features that are human interpretable, it is much easier to understand the cause of its mistake. In Comparison, algorithms like Decision trees are very interpretable. This is important because in some domains, interpretability is quite important.
This is why a lot of banks don’t use Neural Network to predict whether a person is creditworthy because they need to explain to their customers why they don’t get a loan. Otherwise, the person may feel wrongly threatened by the Bank, because he can not understand why he doesn’t get a loan, which could lead him to change his bank. The same thing is true for sites like Quora. If they would decide to delete a users account because of a Machine Learning algorithm, they would need to explain to their user why they have done it. I doubt that they will be satisfied with an answer such as “that’s what the computer said”.
Other scenarios would be important business decisions, driven by Machine Learning. Can you imagine that a CEO of a big company will make a decision about millions of dollars without understanding why it should be done, just because the „computer“ says he needs to do so?
2. Duration of Development
(Image Source: http://slideplayer.com/slide/6816119/)
Although there are libraries like Keras out there, which make the development of Neural Networks fairly simple, you sometimes need more control over the details of the Algorithm, when for example you trying to solve a difficult problem with Machine Learning that no one has ever done before.
Then you probably use Tensorflow, which provides you with much more opportunities but because of that it is also more complicated and the development takes much longer (depending on what you want to build). Then the question arises for a companies management if it is really worth it that their expensive engineers spend weeks to develop something, which may be solved much faster with a simpler algorithm.
3. Amount of Data
Neural Networks usually require much more data than traditional Machine Learning algorithms, as in at least thousands if not millions of labeled samples. This isn’t an easy problem to deal with and many Machine Learning problems can be solved well with less data if you use other algorithms.
Although there are some cases where NN’s deal well with little data, most of the time they don’t. In this case, a simple algorithm like Naive Bayes, which deals much better with little data, would be the appropriate choice.
4. Computationally Expensive
Usually, Neural Networks are also more computationally expensive than traditional algorithms. State of the art deep learning algorithms, which realize successful training of really deep Neural Network, can take several weeks to train completely from scratch. Most traditional Machine Learning Algorithms take much less time to train, ranging from a few minutes to a few hours or days.
The amount of computational power needed for a Neural Network depends heavily on the size of your data but also on how deep and complex your Network is. For example, a Neural Network with one layer and 50 neurons will be much faster than a Random Forest with 1,000 trees. In comparison, a Neural Network with 50 layers will be much slower than a Random Forest with only 10 trees.
Great! Now you know that Neural networks are great for some tasks but not as great for others. You learned that huge amounts of data, more computational power, better algorithms and intelligent marketing increased the popularity of Deep Learning and made it into one of the hottest fields right now. On top of that, you have learned that Neural Networks can beat nearly every other Machine Learning algorithms and the disadvantages that go along with it. The biggest disadvantages are their „black box“ nature, increased duration of development (depending on your problem), the required amount of data and that they are mostly computational expensive.
In my opinion, Deep Learning is a little bit over-hyped at the moment and the expectations exceed what can be really done with it right now. But that doesn’t mean it is not useful. I think we live in a Machine Learning renaissance because it gets more and more democratized which enables more and more people to build useful products with it. Out there are a lot of problems that can be solved with Machine Learning and I am sure this will happen in the next few years.
One of the major problems is that only a few people understand what can be really done with it and know how to build successful Data Science teams that bring real value to a company. On one hand, we have PhD-level engineers that are geniuses in regards to the theory behind Machine Learning but lack an understanding of the business side. And on the other hand, we have CEO’s and people in management positions that have no idea what can be really done with Deep Learning and think that it will solve all of the world’s problems in the next years to come. In my opinion, we need more people that bridge this gap, which will result in more products that are useful for our society. | <urn:uuid:89e6dfdc-47f7-47b5-a3b3-f68bb7e4b58d> | CC-MAIN-2024-38 | https://resources.experfy.com/ai-ml/pros-and-cons-of-neural-networks/ | 2024-09-17T01:14:34Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651722.42/warc/CC-MAIN-20240917004428-20240917034428-00348.warc.gz | en | 0.962561 | 2,000 | 2.625 | 3 |
Electronic data is information recorded in a way that requires electronic devices such as computers to interpret, process, and display. On the other hand, electronic data processing is a series of operations on a computer that interprets, manipulate, classify, summarize, and record data. Electronic data processing aims at managing and protecting the integrity of documents.
As the years unroll, data is turning into an invaluable asset for most businesses and other organizations. Consequently, hackers are targeting data held by various institutions, reaping vast sums of money from ransoms paid by companies whose data is compromised. To shield against attackers, businesses now prefer to entrust IT companies such as Fusion Computing Limited with the roles of safely processing their electronic data.
There are four essential components of electronic data processing. They include hardware, software, procedure, and personnel. The hardware consists of the physical and tangible parts of a computer. Hardware is used to record and store data. Computer software is a set of instructions that guide how machines perform given tasks. In the case of data processing, computer software consist of custom applications, databases, spreadsheets, among many other pieces of code. A procedure is an organized set of coded instructions that capture and manipulate electronic data. Procedures are designed to eliminate redundancy and corruption of data. Personnel is the staff trained to operate electronic data processing procedures.
There are four stages of electronic data processing. They include collection, preparation, input, and storage. Sometimes, these stages can be compressed into three, including input, processing, and output.
The collection stage entails gathering data and is the most crucial step of all. If accurate data is not collected, then all the other phases of data processing will be futile. Customer data is an example of data gathered during the collection stage.
Once raw data is collected, it is taken through the preparation stage. Preparation entails cleaning and transforming raw data before inputting it in the right format into a computing system.
The input step entails sending data into a computer using an input device such as a keyboard, digitizer, or scanner.
After data is collected, prepared, and keyed into a system, it is taken through processing. Processing entails various data manipulation techniques. These operations involve comparing, classifying, sorting, among many other procedures that transform data into information.
Once data is converted into information via processing, it is ready for transmission to relevant parties who need to use it. The output data is stored in the right format for retrieval or future use by relevant authorities.
There are eight methods of electronic data processing utilized by most reputable IT companies. They include:
All of the above are expounded in the subsequent paragraphs.
In time-sharing, many terminals are connected to a central processing unit at the same time. However, in actual sense, each terminal is allocated a given time slice in the CPU’s sequence. This means that a user of a given terminal can complete a given task within the time slice assigned to the terminal. If the allocated time elapses before the task is completed, the user has to wait for the next time slice allocated to the terminal.
Reservation of airline and train tickets are examples of online data processing scenarios. Suppose you are booking a plane or train, a computer processes your incoming data upon submission. Consequently, it updates the transaction file and makes a reservation. You are then given an immediate response to the events to follow. This type of data processing maximizes on delivering data output for efficient service delivery. For online data processing to occur, the CPU must be directly connected to a data input unit. This is achieved through a communication network.
Automated Heating Ventilation and Cooling Systems (HVAC) serve excellent examples of real-time data processing. Accurate information is collected and manipulated. After which an immediate response that influences the next tract of events is provided. Just like online processing, real-time data processing achieves prompt, efficient service delivery. For example, when the temperature set for a given room is surpassed, an automated HVAC system automatically turns on to restore comfortable temperatures.
Multiprocessing entails processing more than one task at the same time on one computer. Multiprocessing computers contain more than one independent CPU, which operate together in a coordinated manner. Servers are examples of multiprocessing units.
In interactive processing, one action leads to the next. A user inputs data which is manipulated and output displayed. The response presented requests the following input to execute the next out until the desired information is achieved.
Multitasking involves working with different processors at the same time. Take an example of the banking industry where banks have different branches. These branches have different customer accounts, all of which can be centrally administered from the central server. Hence, the various tasks in different offices share the same processing resource.
Batch processing accumulates data over some time. The data is then processed at once when the data collection period elapses. A good example is payroll systems. Employee data is collected in terms of hours worked and their rate per hour for a given time, for instance, one month. The information is consequently used to process payment for the given period.
ATMs serve perfect examples of distributed processing. This type of processing leverages the use of remote workstations for efficient service delivery. All the remote work stations are synchronized with the mega workstation.
In summa, electronic data processing runs on different modes, all of which target speed and efficiency at which information can be delivered. Additionally, EDP reduces the costs of managing data as well as eliminate duplication of efforts. | <urn:uuid:5b25b136-8265-4a30-a231-3755d4be6817> | CC-MAIN-2024-38 | https://drawntoscalehq.com/how-it-companies-safely-process-electronic-data/ | 2024-09-19T15:25:32Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652031.71/warc/CC-MAIN-20240919125821-20240919155821-00148.warc.gz | en | 0.921185 | 1,139 | 3.71875 | 4 |
Hybrid Cloud vs. Multi-Cloud: What is the difference?
In cloud computing, the cloud is a collection of servers that cloud customers access over the Internet. Cloud computing has different cloud deployments and is mainly divided into 4 types: private cloud, public cloud, hybrid cloud, and multi-cloud. In this post, hybrid cloud and multi-cloud will be mainly introduced.
Hybrid Cloud and Multi-Cloud Comparison
Both multi-cloud and hybrid cloud refer to cloud deployments that integrate two or more clouds. Their main difference is the kinds of cloud infrastructure they include. To find out the difference between hybrid and multi-cloud, we should first figure out what hybrid and multi-cloud are and what the applications of these cloud strategies are.
What Is Hybrid Cloud?
Hybrid cloud deployments combine public and private clouds, additionally, they may also include on-premises legacy infrastructure. Almost all hybrid clouds contain at least one public cloud.
Public and private clouds are completely different cloud environments, which functions in completely different way. Hybrid clouds effectively combine the two environments. The result is more powerful cloud infrastructure. To learn more about public cloud vs. private cloud, you can read Comparison of Private Cloud and Public Cloud.
Hybrid cloud organizations can use its private cloud for some services and its public cloud for others. Or they can use the public cloud as a backup to its private cloud. They can also use the public cloud to handle periods of high demand while keeping most operations in their private cloud.
What Is Multi-Cloud?
Multi-cloud is a cloud architecture composed of multiple cloud services provided by multiple cloud providers (either public or private). "Multi-cloud" can be multiple public clouds, multiple private clouds, or a combination of public clouds and private clouds. Additionally, a multi-cloud deployment that includes private clouds or on-premises infrastructures is considered a hybrid multi-cloud.
Multicloud deployments can leverage multiple IaaS (Infrastructure as a Service) vendors, or different vendors for IaaS, PaaS (Platform as a Service), and SaaS (Software as a Service) services.
Multi-cloud can be purely for redundancy and system backup, or it can incorporate different cloud providers offering different services. For example, a business could use one public cloud for the database and another public cloud for scale computing. In this way, you can get the most out of each service.
Characteristics and Differences Between Them
To understand the specific differences between hybrid clouds and multi-cloud, we must first understand the characteristics of the two clouds. The following table outlines the characteristics of hybrid clouds and multiple clouds in several ways.
Hybrid Cloud | Multi-cloud | |
Architecture | Public and private clouds or on-premises data centers (or both) | Multiple public clouds (but can also have private, community, and on-premises data centers) |
Cross-cloud workloads | Components work together to run a single IT solution, so data and processes intersect | Different clouds handle different tasks, so data and processes often run in silos |
Sensitive data storage | Resides on private cloud or on-premises servers | Valuable data resides on-premises or in the cloud, depending on the design |
Security Responsibilities | Internal teams are responsible for protecting data in private clouds and data centers; provider handles public cloud security | Public cloud providers are responsible for cloud computing security |
Benefits of storing regulated data | Teams keep sensitive data in a highly secure private cloud or data center | Companies can ensure that every piece of data is located in a geographic location as required by law |
Vendor lock-in | High integration between environments makes changing suppliers difficult | Multiple cloud providers and independent workloads provide the flexibility to switch vendors easily and quickly |
Cloud Migration | Most workloads continue to run locally, so the migration process is shorter and less challenging | Migrating to multiple clouds can be time-consuming and challenging |
Availability | Users may experience problems if public cloud encounters problems preventing cloud bursting | If one provider fails, workloads can be shifted to another; companies can also set up separate public clouds based on user location to avoid delays |
Cost | Less risk of overruns, but companies have to incur more staffing and maintenance costs | Public clouds are cheaper than private clouds or data centers, but companies must be careful not to overspend on each platform |
The first key difference is that a hybrid cloud always includes both private and public clouds. Multi-cloud includes multiple public clouds or private clouds.
Another key difference is that a hybrid cloud provides a direct connection between public and private clouds. While in the multi-cloud model, the two or more cloud providers are usually completely independent.
Which Cloud to Choose?
For most businesses, the ideal cloud solution is not to deploy a single cloud, but to deploy a hybrid or multi-cloud solution. So which cloud is chosen by most enterprises, multi-cloud or hybrid cloud?
According to market research, the application scope of the hybrid cloud is becoming more and more extensive. Globally, the hybrid cloud has become the main form of enterprise cloud. According to RightScale's 2019 State of the Cloud Report, 84% of enterprises have adopted multiple cloud strategies or hybrid cloud strategies. Among them, the proportion of enterprises using hybrid cloud continued to increase — from 51% in 2018 to 58% in 2019. Another 26% of enterprises choose multiple private clouds and multiple public clouds.
Both cloud setups provide efficiencies through cloud computing, but the final goal is to get the best results. According to the above comparison of different aspects of the two clouds, enterprises can choose the appropriate cloud deployment according to their own needs. | <urn:uuid:7983f726-c686-447c-a9d2-39ca55ca56bc> | CC-MAIN-2024-38 | https://community.fs.com/article/hybrid-cloud-vs-multi-cloud-what-is-the-difference.html | 2024-09-20T19:49:48Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725701423570.98/warc/CC-MAIN-20240920190822-20240920220822-00048.warc.gz | en | 0.926777 | 1,173 | 2.59375 | 3 |
Identity and access management (IAM) is the set of practices and technologies used to manage digital identities and control access to computer systems and networks.
Identity and access management (IAM) is a critical component of IoT security that involves the management of digital identities and control of access to IoT devices and networks. It includes the use of specialized technologies and practices for user authentication, authorization, and permissions management, as well as secure device provisioning and deprovisioning. IAM helps prevent unauthorized access and data breaches by ensuring only authorized users and devices are granted access to IoT networks and devices. Effective IAM for IoT requires the use of specialized security controls and technologies to ensure the confidentiality, integrity, and availability of information. | <urn:uuid:a5cee92a-7966-49af-ae60-ec62acb19e77> | CC-MAIN-2024-38 | https://www.kudelski-iot.com/glossary/identity-and-access-management | 2024-09-07T12:26:19Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650826.4/warc/CC-MAIN-20240907095856-20240907125856-00412.warc.gz | en | 0.922437 | 147 | 2.5625 | 3 |
The biotechnology & pharmaceutical industry faces an increased risk of cyberattacks
The coronavirus outbreak has led to the rapid digital evolution of the healthcare industry. This has resulted in an incredible increase in hacking attacks and disinformation. Digital espionage against the healthcare sector, pharmaceutical agencies, and vaccine manufacturers has stepped up in recent months. With more data than ever collected and managed online, pharmaceutical organizations became very appealing to cybercriminals, and for good reason. Hardly any other industry has access to data with that level of critical sensitivity. A breach would mean stolen intellectual property and clinical trial data, reputational damage, revenue loss, etc.
Phishing campaigns and COVID-19 scams are more prevalent than ever.
The DynaRisk intelligence team has detected hackers offering fake applications associated with Coronavirus - trackers, maps, etc.
Prescription drugs, vaccines, even saliva and blood samples infected with COVID-19 also can be found available for purchase through the Dark web forums.
Cybercriminals exploit the pandemic to perpetrate phishing attacks, often posing as government and official health organizations. Online scammers will try to take advantage of the pandemic situation by sending fraudulent emails encouraging you to click on malicious links or open attachments. Any funding appeal that appears to be sent by the World Health Organization (WHO) is most likely a scam. WHO will never ask for your login information, send email attachments, charge a fee to apply for a conference, employment, etc.
Lotteries or prize giveaways also indicate a scam. Hackers will try anything that looks catchy enough for people to click on it. One click and voilà - you've got yourself a nice malware.
The WHO, the Gates Foundation, and the Wuhan Laboratories were subjected to a hacking attack that led to leaks of the user passwords.
The pandemic affected everyone financially and even cybercriminals have had to adapt to the situation. The screenshot above shows hackers offering a discount to entice more buyers.
Free Download: Ransomware Guide for SMEs
The Healthcare industry has been overwhelmed with implementing technical solutions to navigate the Covid-19 crisis and maximize efficiency. Relying on third-party vendors, automation tools and outsourcing moved cybersecurity issues to a whole new level. Many pharmaceutical companies still fail to set even the basic steps in terms of employee behavior online. It is a common error for employees to browse the Internet using corporate computers and domains. There are concerns many of them have even used company provided email addresses corporate domain to register on different forums or unknowingly access hacked websites, leaving the access to the company's database out in the open.
The DynaRisk intelligence team was able to locate, access, and download a large number of different leaked databases, but the hackers did as well.
DynaRisk detected numerous examples of information leakage following cyberattacks against the European Medicines Agency (EMA) in December 2020. In mid-January 2021, the EMA confirmed that some of the data associated with the Pfizer/BioNTech COVID-19 vaccine and the Moderna vaccine had been stolen. Hackers altered some of the email correspondence related to the vaccine evaluation process before its release. This type of data tampering undermines public confidence in COVID-19 vaccines. Fear sells.
Our early warning Hacker Chatter monitoring has tracked down a Pfizer FTP server in Spain with stolen credentials shared between hackers in a data cache with many other businesses. We detected messages posted on Russian forums with lists of thousands of other FTP servers, easily accessible by hackers since employees were using private identifiers, as well as the Pfizer domain.
Over the years, Pfizer has suffered several security breaches and data leaks. The released information remains available on forums to this day.
The DynaRisk intelligence team has noticed the leaked data concerning two other leading vaccine makers – Moderna and AstraZeneca. Stolen user’s credentials are shared on the Dark web forums and sold on a black market. Weak passwords always play a big role in corporate cybersecurity. One of Moderna’s employees has even used the company’s name as his password.
A great percentage of breaches can be attributed to human error. Healthcare employees lack training when it comes to cyber awareness. Using safe cloud services is more important than ever with the increasing number of devices connected. The Internet of Things (IoT) enabled the use of personal IoT devices in the workplace causing a number of security challenges.
The healthcare sector has been hit hard by cybercrime, and because it is such a vulnerable industry, the impact will go far beyond financial loss and invasion of privacy. Ransomware can make files and systems in-accessible until a ransom is paid. This leaves hospitals and health centers cut off from essential systems and unable to fully operate on a day-to-day basis. But there's still paper and pen. Not good enough for 2021.
DynaRisk offers strategies for fighting against cybercrime and ransomware attacks. We have created a range of tools to help companies improve their online safety and give you a heads up when you need to improve your protection.
· Types of ransomware attacks
· Ransomware examples
· The costs of a ransomware attack
· The ways your business may be vulnerable
· Preventing a ransomware attack
· Common mistakes when planning ransomware prevention
· Recovering from a ransomware attack | <urn:uuid:7a0f58b8-7557-4103-8b55-c0ce442da294> | CC-MAIN-2024-38 | https://dynarisk.com/resources/blog/cyber-threats-affecting-the-healthcare-industry | 2024-09-08T16:20:58Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651013.49/warc/CC-MAIN-20240908150334-20240908180334-00312.warc.gz | en | 0.93837 | 1,101 | 2.5625 | 3 |
The recent trend of providing access to free public WiFi is helpful for working professionals. With the onset of remote and hybrid working, many professionals use the free WiFi provided in public spaces. However, this comes at a cost. The features that make free WiFi hotspots appealing (no requirement of authentication) to use a network connection also appeal to cybercriminals. It allows hackers to get unrestricted access on the same network to unsecured devices, making it a threat to data security.
With public WiFi getting widespread, there are certain security issues that one can be privy to while accessing it. However, measures can be taken to mitigate such risks.
SSL stands for Secure Sockets Layer, a safety protocol that establishes an encrypted link between the user and the website. Using SSL connections helps to reduce the likelihood of a cyber attacker extracting sensitive information from the public WiFi or network that the user uses.
A VPN or Virtual Private Network provides strong encryption that helps conceal a user’s information and device while accessing public and unsecured networks. Business professionals must ensure the data security of their company’s confidential information when working from a public space.
When connected to a public network that is likely unsecured, a user should turn off sharing or receiving shared information over a public network. This is so that a hacker cannot imprint their bugs into the user’s device.
With remote and hybrid working being the new way of working, professionals using public WiFi should find ways to limit their exposure to cyber threats. Their devices must be equipped with optimum cybersecurity solutions to enhance their data security.
GajShield’s robust cybersecurity solutions, such as advanced Firewalls, Virtual Private Networks, Pro Active Security, and much more, help provide the user with a well-rounded cybersecurity solution and ensure high-level data security. Contact us for more information on our cybersecurity solutions. | <urn:uuid:bd6100dc-0cfd-443a-9d8f-3995d02fc96f> | CC-MAIN-2024-38 | https://gajshield.com/index.php/resources/gajshield-blogs/351-remote-work-avoid-public-wifi-security-risks | 2024-09-08T16:11:25Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651013.49/warc/CC-MAIN-20240908150334-20240908180334-00312.warc.gz | en | 0.930061 | 381 | 2.75 | 3 |
Tunnel and Transport Modes
IPSec can be run in either tunnel mode or transport mode. Each of these modes has its own particular uses and care should be taken to ensure that the correct one is selected for the solution:
Tunnel mode is most commonly used between gateways, or at an end-station to a gateway, the gateway acting as a proxy for the hosts behind it.
Transport mode is used between end-stations or between an end-station and a gateway, if the gateway is being treated as a hostfor example, an encrypted Telnet session from a workstation to a router, in which the router is the actual destination.
As Figure 1 shows, basically transport mode should be used for end-to-end sessions and tunnel mode should be used for everything else. (Refer to the figure for the following discussion.)
Figure 1 Tunnel and transport modes in IPSec.
Figure 1 displays some examples of when to use tunnel versus transport mode:
Tunnel mode is most commonly used to encrypt traffic between secure IPSec gateways, such as between the Cisco router and PIX Firewall (as shown in example A in Figure 1). The IPSec gateways proxy IPSec for the devices behind them, such as Alice's PC and the HR servers in Figure 1. In example A, Alice connects to the HR servers securely through the IPSec tunnel set up between the gateways.
Tunnel mode is also used to connect an end-station running IPSec software, such as the Cisco Secure VPN Client, to an IPSec gateway, as shown in example B.
In example C, tunnel mode is used to set up an IPSec tunnel between the Cisco router and a server running IPSec software. Note that Cisco IOS software and the PIX Firewall sets tunnel mode as the default IPSec mode.
Transport mode is used between end-stations supporting IPSec, or between an end-station and a gateway, if the gateway is being treated as a host. In example D, transport mode is used to set up an encrypted Telnet session from Alice's PC running Cisco Secure VPN Client software to terminate at the PIX Firewall, enabling Alice to remotely configure the PIX Firewall securely.
AH Tunnel Versus Transport Mode
Figure 2 shows the differences that the IPSec mode makes to AH. In transport mode, AH services protect the external IP header along with the data payload. AH services protect all the fields in the header that don't change in transport. The header goes after the IP header and before the ESP header, if present, and other higher-layer protocols.
In tunnel mode, the entire original header is authenticated, a new IP header is built, and the new IP header is protected in the same way as the IP header in transport mode.
Figure 2 AH tunnel versus transport mode.
AH is incompatible with Network Address Translation (NAT) because NAT changes the source IP address, which breaks the AH header and causes the packets to be rejected by the IPSec peer.
ESP Tunnel Versus Transport Mode
Figure 3 shows the differences that the IPSec mode makes to ESP. In transport mode, the IP payload is encrypted and the original headers are left intact. The ESP header is inserted after the IP header and before the upper-layer protocol header. The upper-layer protocols are encrypted and authenticated along with the ESP header. ESP doesn't authenticate the IP header itself.
Higher-layer information is not available because it's part of the encrypted payload.
When ESP is used in tunnel mode, the original IP header is well protected because the entire original IP datagram is encrypted. With an ESP authentication mechanism, the original IP datagram and the ESP header are included; however, the new IP header is not included in the authentication.
When both authentication and encryption are selected, encryption is performed first, before authentication. One reason for this order of processing is that it facilitates rapid detection and rejection of replayed or bogus packets by the receiving node. Prior to decrypting the packet, the receiver can detect the problem and potentially reduce the impact of denial-of-service attacks.
Figure 3 ESP tunnel versus transport mode.
ESP can also provide packet authentication with an optional field for authentication. Cisco IOS software and the PIX Firewall refer to this service as ESP hashed message authentication code (HMAC). Authentication is calculated after the encryption is done. The current IPSec standard specifies SHA-1 and MD5 as the mandatory HMAC algorithms.
The main difference between the authentication provided by ESP and AH is the extent of the coverage. Specifically, ESP doesn't protect any IP header fields unless those fields are encapsulated by ESP (tunnel mode). Figure 4 illustrates the fields protected by ESP HMAC.
Figure 4 ESP encryption with a keyed HMAC. | <urn:uuid:b2aff549-07f7-4ce7-a70d-2ae53e2baabd> | CC-MAIN-2024-38 | https://www.ciscopress.com/articles/article.asp?p=25477 | 2024-09-08T17:28:04Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651013.49/warc/CC-MAIN-20240908150334-20240908180334-00312.warc.gz | en | 0.91685 | 990 | 2.96875 | 3 |
A few days ago, a critical bug was found in the common OpenSSL library. OpenSSL is the library that implements the common SSL and TLS security protocols. These protocols facilitate the encrypted tunnel feature that secure services – over the web and otherwise – utilize to encrypt the traffic between the client (user) and the server.
The discovery of such a security bug is a big deal. Not only that OpenSSL is very common, but the bug that was found is one that can be readily exploited remotely without any privilege on the attacker’s side. Also, the outcome of the attack that is made possible is devastating. Exploiting the bug allows an attacker to obtain internal information, in the form of memory contents, from the attacked server or client. This memory space that the attacker can obtain a copy of can contain just about everything. Almost.
There are many essays and posts about the “everything” that could be lost, so I will take the optimistic side and dedicate this post to the “almost". As opposed to with other serious attacks, at least the leak is not complete and can be quantified, and the attack is not persistent.
I will focus on the server as the target of the attack.
Say an attacker exploits the newly discovered bug, and starts dumping out contents of memory addresses from your server. The bug allows to exfiltrate 64K at a time, but multiple iterations are possible to exfiltrate as much data as needed. This dump can contain anything that is stored in memory. The memory involved is the process space of the application or web server that happened to call OpenSSL.
What is there as loot for the attacker? In essence, there is all the state information of the application, including that of the web server process, if the application is web-based. The actual state information depends on what the application or web server is doing, but at a minimum it contains:
All data (including keys) pertaining to the secure connection itself, such as the permanent private key of the server.
All communicated data: the data that is being exchanged between the client and the server.
Potentially any other data that the attacked application processes in the current session, including inputs, outputs, and passwords.
This is not to be taken lightly. This is a lot. Notwithstanding, let us see what was not put at risk. There are three resources that are clearly left out of scope for the attacker:
The contents of disks and storage, which were not loaded into memory during the session of the attack. The bug allows to map memory contents, but not to access the file-system, and not to introduce commands that can load parts of the file-system into memory from where they can be exfiltrated.
Memory contents of other applications and processes on the system, including that of processes that happen to run at the same time as the attacked application. The bug fools the OpenSSL implementation to leak data that it has access to, but it does not fool Linux into allowing OpenSSL to reach beyond its process memory space.
The integrity of the system. This is probably the most important point. The attack is passive in the sense that it gets data out, but cannot change anything in the system. An obvious exception would be if a password that was captured happens to open the door to other attack venues. However, as long as the stolen credentials do not allow their holder to cause persistent damage, no persistent damage could have been made. This implies that by following a few instructions (below), you return to the presumably secure state you were in before the attack was brought to your attention.
What to do next
First and foremost, install the necessary updates so to close the tap.
Second, comprehend the scope of the leakage that might have occurred. Unfortunately, there is no way to tell if your server was hacked and to what extent, so assume it was and enumerate the data that might have been compromised. This data, which we refer to as “session data", consists of all data that is served, processed or obtained by the web (or other application) process that calls OpenSSL. This includes all its inputs that come over the web (or other bearer), all data that goes out, and all data that may be processed in between by the same process that calls OpenSSL (e.g., the web server).
What is not in the scope of leaked data is all data that may be processed but is not served, or otherwise made available to the process that uses OpenSSL. For example, if the application is a web-application, then data that is neither sent nor received over the web, and which is not processed by the web server, would never find itself in the process memory space of the web server, and is thus safe. Also, other data on the server, such as files in home directories, is safe.
The private key of the web server is also at immediate risk, but in most cases it accounts for a change in quantity, not in quality, of the leaked data. In other words, this key will allow an attacker to decipher more sessions, so the attacker can leak not only session data during the attack, but other session data as well, yet it is still session data by the definition above, which we already considered to be entirely lost.
Passwords may be another issue. In most cases, however, stolen passwords only account for yet more session data that can be accessed by impersonating the user, so it is still in the sense of “more of the same". Obviously, if the passwords that your application uses are also used for granting access to other assets – those may be at risk as well.
Private keys of users, if used by the application, are not at risk, because they are never made available to the server in the first place.
To summarize, in the usual case, the maximum leakage that could have occurred consists of all data served or processed by the process calling OpenSSL. Data of other applications and back-end data are safe.
Third, return to secure state. We got lucky with the “heartbleed bug” in that it is passive and cannot cause your system to be “owned", or to be contaminated in a way that calls for a complete re-install or serious scrubbing. After installing the patch to OpenSSL, you need to generate a new key-pair for the OpenSSL deployment, get it certified if your previous key was, revoke the previous key, and change application passwords that might have been leaked. Once this is done, aside of the data that might have been leaked forever, you can consider the incident to be behind you.
If you run an application server utilizing OpenSSL which was subject to attack, a lot of data might have been stolen, both in terms of application data and in terms of credentials. However, the only bright side is that, as opposed to with other serious attacks:
it is relatively easy to quantify the data that could have been stolen, and
(unless credentials that allow further access were leaked) compromise is not persistent: once you patch OpenSSL and replace keys and credentials, you are safe hereafter. | <urn:uuid:b050a59c-bbd2-4681-8f1f-50fde89ec9a8> | CC-MAIN-2024-38 | https://www.hbarel.com/posts/OpenSSL-Heartbleed-bug-whats-at-risk-on-the-server-and-what-is-not.html | 2024-09-11T04:23:28Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651343.80/warc/CC-MAIN-20240911020451-20240911050451-00112.warc.gz | en | 0.966208 | 1,467 | 2.828125 | 3 |
In the ever-evolving landscape of cybersecurity, the emergence of data breaches has become an unfortunate reality. However, this latest breach, is so large some cybersecurity experts are calling it a “mega-breach”. This unprecedented event involves more than 26 billion passwords and credentials leaked, exposing individuals and organizations to severe cybersecurity risks. In this article, we delve into the details of this mega-breach, explore its implications and emphasize the urgent need for enhanced cybersecurity countermeasures.
Scope of the Breach:
The Mother of All Breaches was first reported by CyberNews, a reputable cybersecurity news source known for its in-depth analysis and coverage of emerging threats. According to their report, a staggering number of passwords and credentials have been compromised. The scale and severity of this breach have sent alarm bells sounding within the cybersecurity community.
The breach encompasses a wide array of personal and sensitive information, including email addresses, passwords, and usernames. CyberNews estimates that billions of records are newly circulating on the dark web, posing a significant threat to individuals and businesses alike. The data appears to be aggregated from various sources, some public while others previously unseen. This indicates a sophisticated and well-organized hacker or group of hackers, that compiled lists of breach data over many years into a single compendium of exposed account data. This will have severe consequences for years to come.
Implications for Individuals:
For individuals, the Mother of All Breaches brings forth immediate concerns regarding online security and privacy. With login credentials exposed, individuals are at risk of unauthorized access to their accounts, leading to potential identity theft, financial fraud, and other malicious activities. The breach serves as a stark reminder of the importance of robust password practices like utilizing a password manager to protect and store your passwords, and the necessity of implementing multi-factor authentication to enhance account security. To these technical measures, you must also train your users on how to spot and avoid phishing attacks. Recent Session-Stealing attacks delivered by phishing emails, by-pass your unique password and MFA to get hackers into your account quickly!
Business and Organizational Impact:
Businesses and organizations are not immune to the repercussions of this breach. Compromised employee credentials could provide cybercriminals with a gateway to sensitive corporate information, intellectual property, and confidential data. The potential fallout from such unauthorized access could result in financial losses, damage to reputation, and legal consequences. This breach underscores the critical need for organizations to prioritize cybersecurity program development measures and outlined below.
In the wake of this mega-breach, cybersecurity experts and organizations are intensifying efforts to mitigate the damage and prevent further unauthorized access. Individuals are urged to change their passwords promptly, adopt secure password practices, and enable multi-factor authentication wherever possible. Companies are advised to conduct thorough security audits, implement advanced threat detection systems, and educate employees on cybersecurity best practices to safeguard against future breaches.
This mega-breach serves as a wake-up call for individuals, businesses, and organizations worldwide. It highlights the evolving and sophisticated nature of cyber threats and emphasizes the need for constant vigilance in the face of an ever-changing digital landscape. As we collectively grapple with the aftermath of this unprecedented breach, it is crucial to prioritize cybersecurity, implement robust protective measures, and stay informed about emerging threats to ensure a safer online environment for everyone.
Video Overview of the Largest Data Leak to Date via CyberNews
– CyberNews: Mother of all breaches reveals 26 billion records: what we know so far
– 1Password: One breach. One leak. | <urn:uuid:a3dd1e24-77fa-4352-b739-e199c9cf01ba> | CC-MAIN-2024-38 | https://cyberhoot.com/blog/unveiling-the-megabreach-understanding-the-impact-of-billions-of-leaked-passwords-and-credentials/ | 2024-09-17T05:51:31Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651739.72/warc/CC-MAIN-20240917040428-20240917070428-00512.warc.gz | en | 0.920027 | 726 | 2.75 | 3 |
Artificial intelligence is seen as future technology, yet in fact AI is already having an enormous effect on our lives. An in-depth look at AI, automation and robotics.
It’s a beautifully sunny day on the campus of UC-Berkeley, students rushing between classes, backpacks and smartphones everywhere. Here in the Robot Learning Lab it’s pure geek heaven. Students code software at desktops, while others assemble odd machines with wires and multi-colored boxes. Earning a spot at this elite university isn’t easy; UC-Berkeley accepted a mere 14.8 percent of applicants for the class of 2020. So this young crew will likely be tomorrow’s tech leaders and pioneers.
Despite all the promise, it appears that BRETT is struggling. Actually, even failing. BRETT is a robot, and he – or she, or it – is attempting to place a small wooden block into a small hole. Again and again, BRETT swings his arm over the opening, attempts to place the block, but fumbles. Just can’t make it fit.
However, as robots go, BRETT has a huge advantage: he can learn. (BRETT’s name is a playful acronym: Berkeley Robot for the Elimination of Tedious Tasks.) Every time BRETT swings his arm and fails, he calculates what went wrong. In essence he’s doing what we humans do: he’s failing, and in response he’s deciding how to improve the next effort.
I stand watching for about 15 minutes, and finally BRETT succeeds – a lengthy period given the simple task. But the astounding point is that the robot really did learn. He’s not merely a machine repeating a single task. He’s evolving, he’s improving himself.
If you’re a pessimist, BRETT’s slow success on this sunny day casts a shadow over those of us who aren’t robots: Will BRETT, or his next generation peers, eventually learn far better than the humans who program him?
That is, will there come a day when BRETT no longer needs us?
UC-Berkeley’s robot BRETT is capable of learning, if slowly.
Artificial Intelligence and Frankenstein
It’s the defining question of Artificial Intelligence: can a computer attain the human mind’s ability to conceptualize?
Can a computer not just power the system, but conceive of the system? Most significantly, can a computer look at itself critically, self assess, and devise a novel new solution?
As of 2017, the answer is very much no. AI is in its infancy, despite high profile wins like Google DeepMind’s victory against a world-class player in Go, and Watson’s $1 million prize for winning Jeopardy. Compared with the human mind, computers are powerful but limited workhorses.
Computers, to be sure, have a vast advantage in raw processing power. IBM’s Watson can digest upwards of 500 gigabytes – or more than a million books – in a single second. Google’s DeepMind was “trained” to compete at Go by being fed 30 million examples. This massive compute power will only grow ever greater.
Still, Watson’s Jeopardy win was, at its core, simply data retrieval. And while DeepMind’s Go victory required considerably more cognitive agility, it wasn’t creative. It was advanced logistical reasoning powered by brute force compute power.
At the risk of flattering we humans, we not only have intelligence, we have meta-intelligence. We create new and unforeseen leaps in thinking; we turn the framework on its side, squeeze it, shatter it, invent something surprising. Developing artificial intelligence is so difficult because (among many reasons) we don’t know exactly how the human mind works. We are a mystery to ourselves, so how can we replicate ourselves?
And yet we see AI replicate aspects of ourselves every year. Humans are an eccentric lot, but the tasks we do are mostly reducible to routine. Assistive robotics like the iRobot Roomba 650 helps us clean the house. Self-driving cars are being developed by automakers from BMW to Hyundai. Autonomous drones will be delivering our online purchases. AI computers can now recognize images (in limited settings) and respond to natural language (awkwardly).
Indeed, the foundational tools of AI all perform some function akin to human thought. Machine learning uses an algorithm that “learns” to respond to changing inputs; it often outputs a prediction or some next level summary.
A neural net is software that’s analogous to the network in the human central nervous system, including the brain. A neural net employs an adaptive software architecture; it uses a toolset of rule-programming that enables both multi-variable inputs and outputs. The neural net “learns” and can generate output from diverse, non-linear inputs – which is exactly what the human mind does.
Deep learning combines neural nets into a sophisticated responsive structure that can produce an abstract data model. Deep learning – powered by today’s ultrafast GPU computer processors – is AI’s furthest frontier. In a famous example of deep learning, AI pioneer Andy Ng fed 10 million photos from YouTube videos into a neural network, enabling a computer to recognize cat images.
The AI advances enabled by these tools suggest that the fear, once the domain of pulp sci-fi, is now oddly plausible: an AI-equipped robot could at some point surpass a human. Filling the robot’s mind would be all the knowledge of the Library of Congress, Wikipedia, and billions of example patterns. Enabling its mind to “think” would be deep learning neural networks. This mind (if you can call it that) could synthesize learning based on past experience to create novel, unique outputs.
This self-learning robot could then spark the singularity, the turning point – inspired by a physics concept in which the known physical laws no longer apply – when AI transcends human intelligence. At that point super-intelligent machines could direct their own future, striding forward in ways we can no longer predict or control. In this scenario, robots could indeed “rebel.” Or, more accurately, be fully independent actors. To follow the scenario to its dystopian end, we humans would be mere Help Desk support for our technological overlords.
This fear is longstanding. We humans have a deep apprehension of being overtaken by some science we ourselves create. In Mary Shelley’s Frankenstein, published in 1818, the young scientist finds a way to give human awareness to his oversized lab experiment, and the monstrous creature escapes from the lab, wreaking havoc in his creator’s life.
This theme of the rebelling humanoid invention would repeat itself in countless sci-fi novels, movies and TV show. George Jetson’s co-worker robot Uniblab turns out to be a duplicitous rival, tricking him into trash-talking his boss. In 2001: A Space Odyssey, HAL 9000 refuses to let the spaceman back in the ship, famously intoning “I’m sorry Dave, I’m afraid can’t do that.” More recently, the robot Ava in Ex Machina liberates herself, and on TV’s Westworld, the robots – abused by humans – turn the tables on their supposed masters.
Will artificial intelligence actually surpass its human creators? Noted futurist Ray Kurzweil forecasts the singularity for 2045, or about one human generation from now. Kurzweil’s film The Singularity is Near explores the possibilities. Many leading technologists dismiss the singularity as overheated sci-fi fantasy – or so distant as to be hardly worth discussing. The human mind, in their view, is so multi-faceted that no computer system will ever encompass it. Yet the history of science and technology suggests that the exponential leap is the norm. In 1927 it was global news that Lindbergh crossed the Atlantic in an airplane; his flight took 33 hours. In 1969 man walked on the Moon; Apollo 11 reached the Moon in just under 76 hours.
And even if the singularity is distant, or an impossibility, the surging progress in artificial intelligence will create myriad possibilities. What about genetic engineering with AI, in an effort to create super humans? What about some Frankensteinian combination of AI with the human brain? A USB port to our brains? AI combined with virtual reality to form an entirely new reality?
So while we can’t know exactly how artificial intelligence will affect human life, it’s certain that AI will affect us profoundly, and unpredictably.
In short, when in doubt, it’s best to be kind to your robot.
The trailer for Ray Kurzweil’s film The Singularity is Near.
Artificial Intelligence and Your Personal Life
Although AI is often viewed as otherworldly whiz-bang technology, it’s already pervasive in our everyday lives, even commonplace. Every time you Google something, use Map software, shop on Amazon or speak to your smartphone’s voice recognition software, you’re using artificial intelligence. Every time you log on to Facebook and enjoy those lovable baby photos, AI shapes your experience.
All these applications leverage an algorithm, which at its most basic is a set of rules that form an analytic process, capable of responding to variable input. Today’s algorithms – especially those from giants like Amazon and Facebook – are responsive and constantly learning. They are programmed to harvest better response from users; that is, results that serve the vendors who control the algorithm.
When you shop on Amazon, behind the scenes the algorithm is making fantastically advanced calculations – based on a huge database of buying patterns – about what to show you. It’s responding in real time to your trail of clicks. You might think that having a human personal shopping assistant is the deluxe choice; she knows trends, she knows you personally. But she can’t compete with Amazon, says Daniel Druker, CMO at Ayasdi, an AI vendor. Amazon is “using AI to figure out, from a million items, what’s going to be most interesting to you right now, from everything you’ve ever done. No human could ever do that.”
On Facebook, very few of your friends show up in your feed; the Facebook AI algorithm knows you’d be overwhelmed if your feed was too long. So Facebook uses AI to sensitively respond to your signals about your circle of personal relationships, shaping your feed to promote a more effective emotional connection. In case you thought AI was cold and scientific, Facebook uses it to peer into your heart (and the hearts of Facebook’s other 1.23 billion daily users). And it’s powerful: It’s no exaggeration to say that Facebook AI influenced the recent election.
Despite AI’s enormous current impact, it continues to be seen as a magical technology that looms over a distant horizon. “It doesn’t matter how fascinating and cool and powerful the algorithm or the app,” says Babak Hodjat, founder and chief scientist at Sentient Technologies, an AI vendor. “Often when I go out and describe these systems, always people say, ‘Yeah, that’s smart and that’s cool, but it’s not AI.’”
The reason for this skepticism, he says, is that “AI is often, by the general public, not by the practitioners, confused as being human level general intelligence that includes emotional intelligence, creativity, autonomy, a whole slew of things. Consequently, AI is “always lurking as the next big thing that we will invent,” Hodjat says. “I think that is going to continue being the case even 10-15 years from now.”
In truth, in many current applications, “AI is more powerful than humans,” he says. “You name that facet and I will tell you how that particular facet is implemented and is more powerful than humans.” At the very least, “AI is faster, and so the decision and action cycle for AI in today’s world is much faster than how humans react to the world.”
Still, he runs into the attitude: “It’s really cool but it’s not AI – it can’t tell me a funny joke.”
Artificial Intelligence: Behind the Curtain
The last few years have seen big leaps forward for AI. Adam Coates, Director, Baidu Silicon Valley AI Lab, points to many examples, including IBM’s Watson. The AI supercomputer can answer a complex question based on a natural language query. “That’s something that would have been very hard to do ten years ago,” he says. However, he notes, echoing Hodjat, “I also think there’s a lot of hype out there about what AI is and what it’s going to do.”
To be sure, “over the next few years a lot of problems that we’ve thought of as the core AI problems, that humans have been very good at and historically computers have been very bad at,” will see major advances, Coates says. “For example, recognizing objects in images or understanding speech and responding to spoken language, those are problems where deep learning and AI technology are going to keep getting better over the next few years.”
What functionality fuels these advances, and what functionality must AI attain to move forward?
First, an AI system – robot or computer – “needs to be able to learn by itself without human input,” says Pieter Abbeel, a professor at UC-Berkeley’s computer science department, and co-founder of Gradescope, an AI-based education startup.
Furthermore, “it also should be able to communicate and understand when it’s told things like, ‘maybe when you stack your block coming from this angle it will work more easily.’ If it can’t incorporate things like that we wouldn’t think of it as a real intelligence.”
Humans (in theory at least) can use past experiences to extrapolate and deal with new environments. Robots, much less so. It’s far easier to program a robot to assist in a limited environment; factory robots repetitively perform the same task.
What AI scientists want is to program robots to deal with related variations. “They will need to use experience they’ve had in the past and generalize to new situations that are not the same but similar, and understand the connection,” Abbeel says. “What I’m very interested in is how a robot can really learn to do things from scratch.” Learning from scratch is a particularly human ability; if a robot could truly fill its own blank slate, it could be an independent actor.
But AI robot “learning” can be defined many different ways, some of which are the mundane “trial and reward” style, akin to teaching a dog new tricks. AI reinforcement learning, for instance, is coding the robot’s software to learn from trial and error. UC-Berkeley’s BRETT robot uses reinforcement learning, based on receiving high or low reward after an action. “The variation in reward allows it to distinguish what’s desired and not desired and zone in on strategies that achieve high reward,” Abbeel says.
Similarly, AI scientists employ supervised learning, which feeds the computer many examples of a labeled input (these are cats, these are dogs), with a clear target output (is this a cat or a dog?). Unsupervised learning feeds the computer unlabeled data, (say, photos of many animals) and the computer categorizes or otherwise defines a structural model for this data (these animals are much furrier than these other animals). Unsupervised learning, Coates says, is “an active area of research that is really important, because we know what humans do to a large degree is unsupervised learning.”
At the core of AI “learning” is the neural net, which, as noted earlier, is roughly analogous to the human mind. Like the mind, the neural net alters itself in response to more input. “You show enough of those [examples] then the neural net will adapt itself and say, Well, I guess for that input I needed that output, so the only way to do that is, I need to adjust some strengths of connections so that I get that mapping right,” Abbeel says. “So, in some sense, when you’re training a neural net, you have the computer learn its computer program rather than you having programmed it into it.”
Yet creating a neural net isn’t easy, Coates explains. “The big challenge is that we don’t have very good ideas for how to train a neural network from just a bunch of unlabeled and unstructured data. We don’t know how to quantify what is a good neural net versus what is a bad neural net in these kinds of tasks,” he says. “And when we discover that, that will be a big improvement. But we’re not there yet. And again, this is a far cry from human intelligence.”
Though AI isn’t human intelligence, AI leaders like Google’s DeepMind show how responsive AI learning can be. For a computer to perform well at, for instance, Tic-Tac-Toe, requires no special intelligence; the game is so simple that a computer wins with brute force. In contrast, when DeepMind plays the vintage Atari video game Breakout, it “actually has to learn concept,” Abeel says. As DeepMind learns to play “it needs to learn a visual system. It needs to learn motor control,” in the form of joystick actions, he says. In real time, its neural network rivals human responsive to multiple variables.
DeepMind’s performance at Breakout demonstrates responsive and agile AI learning. Here’s a tool to help you build your own AI bot to play Atari games.
As neural net technology improves, AI learning becomes more lifelike. Still, Abbeel, as an AI futurist who dreams of what might be, imagines some day teaching a robot with all the nuance and personal insight of a human expert teaching a human student. Like, for instance, a professional basketball player coaching a novice: “You’d say, well, it’s good to keep your eyes on the rim while you shoot…using the backboard is going to be beneficial.” That is, with the countless variations of human responsiveness. He notes: “That is well beyond what is possible right now, but that’s the kind of things you would want in the future.”
But Does AI Lead to the Singularity?
The recent leaps in AI performance have produced countless cases of “human level” performance. But in most cases, only in single, isolated tasks.
Even passing the Turing Test, proposed by Alan Turing in 1950, remains elusive. A computer would pass the Turing Test if it can fool humans into thinking that it’s human; if it can imitate true human intelligence. In the test, human evaluators have a conversation, text only, with a computer. If the computer convinces a given number of listeners that they’re speaking with a human, it has successfully played “the imitation game.” (The Imitation Game is also the title of film about Turing’s code breaking work in WW II.)
In 2014 an eloquent chatbot dubbed Eugene Goostman fooled one third of the judges at the University of Reading into thinking it was a 13-year-old Ukrainian boy. Yet AI professionals largely dismissed the event as pointless, a publicity stunt that runs counter to true accomplishment in AI. Over the years the Turing Test itself has lost some of its credibility; fooling a human via text wouldn’t necessarily demonstrate true intelligence.
The core AI challenge remains: while computers excel at specific tasks in limited settings, they remain unable to achieve the larger awareness of the human mind.
“What’s still fundamentally missing is putting it together into a larger, cognitive, architecture where [the AI system] does lots of things that humans are still really good at and computers are not,” says Zsolt Kira, a research scientist at Georgia Tech Research Institute.
A key limit of AI involves memory, he says. The human mind makes countless decisions involving what to focus on enough to remember and what to discard, “meta level things that are not really conscious decisions that we make, but certainly our brain does,” that an AI system cannot replicate, Kira says. Overcoming this difficulty would require solving problems in both long and short term memory. “A lot of these notions, right now, are really not being tackled – or, definitely not solved.”
In sum, it’s the mysterious synthesis that the human mind excels at that eludes artificial intelligence. Human intelligence, Hodjat notes, “is a very particular configuration that has been brought about through millennia of evolution. You might actually end up with a robot that talks and understands and can sense your feelings and be funny, but it will still disappoint.”
Coates speaking glowingly of the many leading edge advances in AI, but as for the rise of truly sentient AI – the singularity? “I think that’s much further out,” he says. “Right now, there’s no realistic plan for how we build technology like that. A lot of the active areas of research are problems that point in that direction, but I still think it’s quite a distance away.”
For Abbeel, the singularity is an interesting question to ponder. The human brain, he notes, is essentially a combination of storage and compute power, with sensory inputs and outputs. If scientists were to assemble a digital system with equivalent compute, storage and sensory inputs/outputs, at that point “it’s really a matter of having a program that’s comparable to something intelligent that lives inside our brains. So, when that exists then it could be quite comparable to human intelligence.”
He conjures the futuristic notion of humans downloading skills directly to their brains, as in The Matrix. If humans could ever do this, he notes, then certainly AI systems could freely download skills and databases from other AI systems.
This scenario of linked super-systems may suggest a future AI breakthrough: while one single AI system has limits, what if several AI systems were linked together? If, say, a system like IBM’s Watson interfaced with a system like Google’s DeepMind? In theory, each unit in the AI super-network would add its learning tools – its array of neural networks – creating a merged entity that transcended human cognition.
Notes Abbeel: “I think there are some very interesting things that could happen that are kind of hard to wrap our heads around.”
I spoke with UC-Berkeley’s Pieter Abbeel about the future of artificial intelligence.
AI Produces Helpful Robots – Too Helpful
Artificial intelligence offers benefits in virtually any field, from medicine to education to finance. It’s likely that human life needs AI to reach its highest potential in achievement and well being. The list of upsides is long: Self-driving cars never get distracted. Robots could allow the elderly to live healthier independent lives. AI-assisted data analytics will enable smarter, faster decisions.
Among the near term improvements, “AI is learning to understand people and how to interact with us on our terms,” Coates says. Deep learning algorithms will enable remarkable use of natural language in interacting with computers and robots. We’ll run our world with simple voice commands.
In fact, Coates is concerned that some areas of AI aren’t progressing fast enough.
“You have a problem that growth is very low in the world right now. You have countries with large retiring populations and shrinking labor forces,” he says. “To grow and be wealthier in the future, we actually need a huge boost in productivity. If AI comes sooner it will be a benefit to a lot of those places.”
Yet if AI’s promise is rosy, the potential threat of AI is a gaping maw of disruption. In 2016, American manufacturing produced more output than ever, yet US factories employ one third less workers. If you hear someone say “we don’t build anything anymore,” you might correct them – we build more than we ever did. We just do it with automation.
“If Watson can answer Jeopardy questions, why can’t Watson answer every question that somebody calling into a call center might ask?” says Druker. “Those are knowledge worker jobs. It’s not a $200,000 a year job, but that’s fairly repetitive, level one support. There’s millions of people doing that.”
As AI proceeds, “you’re talking about the [highly paid] quant who’s used to running the show who now has a computer doing much of what they’ve done,” Druker says. “A large bank can have 10,000 people trying to track down money laundering or terrorist-related financial transactions. Computers can easily do 90% of that.”
A McKinsey report entitled Where Machines Could Replace Humans (And Where They Cant, Yet), notes that “currently demonstrated technologies could automate 45 percent of the activities people are paid to perform, and that about 60 percent of all occupations could see 30 percent or more of their constituent activities automated, again with technologies available today.”
A McKinsey report identifies which types of occupations are most vulnerable to job losses from AI.
At first glance, an AI report from research firm Forrester is less worrying, forecasting that AI and Robots will replace 7% of American jobs by 2025. Yet that number doesn’t reflect the churn involved. The report predicts that “16% of US jobs will be replaced, while the equivalent of 9% jobs will be created,” hence the 7% overall replacement number.
AI advocates point out that AI will create jobs, not merely eliminate them, and this is certainly true. Yet the new jobs will be skilled jobs – the Forrester report lists robot monitoring professionals, data scientists, automation specialists, and content curators.
So lower-skilled displaced workers will need to retrain, which in most cases will require advanced education. That creates a dire problem for the larger percentage of the workforce that can’t afford this education.
This conclusion is detailed in a report from the University of Oxford entitled The Future of Employment: How Susceptible are Jobs to Computerization. The report describes “the current trend towards labour market polarization, with growing employment in high-income cognitive jobs and low-income manual occupations, accompanied by a hollowing-out of middle-income routine jobs.”
Included is a shocking prediction that has prompted great debate: it forecasts that 47% of US jobs are “highly automatable.” Other experts downplay the potential losses, noting that automation replaces certain tasks of jobs, but not always the entire job itself.
Perhaps that rosy thought bears credence, yet note that spending on AI by business is expected to climb steadily. Surely this level of spending indicates that businesses are expecting to lower labor costs.
An IDC report forecasts heavy spending on AI in the years ahead.
Peruse the headlines and it seems there are few jobs a robot can’t take. MIT’s Technology Review reports that a robot bricklayer – or SAM, semi-automated mason – lays three times as many bricks as human bricklayer, without those pesky overtime regulations. “The robot is able to do all of this using a set of algorithms, a handful of sensors that measure incline angles, velocity, and orientation, and a laser,” the article notes.
Farm workers will see fewer openings due to agriculture robots that, for now, are cost effective only for certain tasks, but those tasks will expand. The graph from Lux Research looks at weeding lettuce, yet a similar graph could be drawn for many similar lower-skilled jobs:
While robots pick the fruit, their colleague robots will milk the cows. A Swedish company, DeLaval International, is debuting an automated milking machine that enables the bovine herd to saunter up when ready (lured by feed) and fill a computerized system – no humans are needed. The rise of self-driving vehicles threatens legions of transport workers, from long-distance truckers to Uber drivers; self-driving cars are currently cruising on streets near you.
White collar jobs aren’t immune: the Deloitte Insight Report forecasts that 39% of jobs in the legal field could be displaced by automation within ten years. In what might be the biggest blow to the human ego, a handful of companies are developing AI systems to compose music. Efforts range from startup Jukedeck to Sony’s Flow Machines. To my ears, the results prove robots don’t have much soul. Then again, the technology is still new.
In January 2017 I attended the Virtual Assistant Summit, in San Francisco, which focused on how AI systems would support or replace humans.
There I spoke with Bart Selman, a professor at Cornell University’s computer science department.
Having studied AI for twenty some years, Selman is not optimistic about the future of human employment. He once thought that AI would erode low-skilled employment yet leave most white-collar jobs alone. His view on that has changed, he tells me. “You start analyzing a mid-level job that seems to require quite a bit of knowledge and skills, now it looks like [AI] might be able to do that job successfully,” he says.
Even as wages have fallen, partially due to automation, company valuations have risen to record highs. If this formula continues it may lead to social unrest, he opines.
Furthermore, he disagrees with the widely held opinion that society can save itself from AI-related job losses by stressing STEM education. “I’m not a big fan of STEM in education,” he says, explaining that too small a sliver of the workforce could ever find employment in science and technology. Data from the U.S. Department of Labor reports that only 5.9 percent of the U.S. workforce is employed in STEM occupations. “So society needs to step back and say, Are these [STEM jobs] real solutions, or are they solutions that sound good?”
The Future of Frankenstein
In a critical turning point in Frankenstein, the oversized monster-man, having attained human consciousness, discovers loneliness. He demands that his creator, the scientist Victor, create a female counterpart for him. This seizes Victor with a horrible worry: if he creates a female companion, she and the man-creature may create spawn, which would then imperil all of mankind. Victor, like today’s artificial intelligence developers, faces the unpredictable consequences of his creation.
Victor refuses the monster’s request but, alas, learns that reversing course is impossible once you’ve created independent, sentient life. The monster, enraged, comes after Victor, murdering his new wife and fleeing. Toward the end, Victor attempts retribution – going all the way to the Arctic – but dies in the pursuit. The creature is then grief stricken over Victor’s death; the scientist was the only one who understood him. The monster decides he must kill himself and is last seen drifting off on an ice floe.
As today’s AI developers create systems with ever increasing independence, we have to wonder if the outcome will be happier than Victor’s. Of course Victor’s experiment plagued only his own life, while current AI advances will affect the entirety of culture and society. And so humanity peers forward, perhaps optimistically but with a definite unease. At this point we can only hope for the best. | <urn:uuid:6df996d6-6054-4e76-8235-28f7e5b74084> | CC-MAIN-2024-38 | https://www.datamation.com/data-center/artificial-intelligence-when-will-the-robots-rebel/ | 2024-09-07T14:28:54Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650883.10/warc/CC-MAIN-20240907131200-20240907161200-00512.warc.gz | en | 0.947599 | 6,838 | 3.390625 | 3 |
Google Finally Unlocks Its Data Center Doors
October 17, 2012The Importance of SSAE 16 Approved Data Centers
October 19, 2012When the general population imagines a server, some might think of a giant computer standing taller than themselves with fans whirring and lights blinking all over it
Micro-servers have been around for a while, with Intel announcing the idea back in 09. According to Intel, Micro-servers currently make up approximately 1 to 2% of total server sales around the world, hardly jaw dropping. There is hope though, with projected sales closer to 10% by 2015.
What Is A Micro-Server?
So what is a Micro-server then? Pretty much they are what their name suggests. Small servers designed to compute less intensive tasks, such as web hosting. Web hosting benefits the most from this type of server, as micros servers consume less energy. Micro servers are compact, with each Micro-server not much larger than 27 x 20 x 26cm (10.6 x 7.8 x 10.2 inches).
Intel aims to make a clear distinction between Micro-servers and general cheap dedicated servers. Jason Fedder, Intel Asia Pacific’s data center General Manager, defines cheap servers as those being a PC mounted on a blade. Micro-servers on the other hand are used specifically in data centers around the world for low intensive tasks. Due to the fact they are used in data centers, they are required to meet quality control and redundancy requirements.
This not only reduces the space taken up, but also reduces the amount of cabling, power supplies and racks needed. Generally a Micro-server will have a small quad core CPU, four memory slots allowing up to 32GB of RAM and a dual-port Gigabit Ethernet controller. All this on a small motherboard, with a line of 2.5 HDD underneath the chassis connected to each Micro-server providing the storage. Computing powers like this are perfect for data centers on a budget.
Micro-Servers Ideal for Conserving Energy
These small servers are ideal for data centers looking to increase their energy efficiency and decrease their carbon footprint. Will they take over the market? Not just yet. However, in a world continually focused on efficiency and streamlining resources, Micro-Servers might just show up in more data centers around the globe.
About the author: This is a blog post written by Alex Burgess. He is the main blog writer for Servers Australia. | <urn:uuid:7dd89c08-2a0d-47e0-b5e7-dadebc4ad466> | CC-MAIN-2024-38 | https://www.colocationamerica.com/blog/small-mighty-micro-servers-corner-the-market | 2024-09-08T20:39:26Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651017.43/warc/CC-MAIN-20240908181815-20240908211815-00412.warc.gz | en | 0.941811 | 507 | 2.6875 | 3 |
A primary focus of the video tutorial is on harnessing Power BI for data analysis using a dataset from Netflix. This tutorial is not just about loading and viewing data; it is an extensive educational resource on how to handle, process, and analyze data effectively using various tools and functions within Power BI.
Power BI, developed by Microsoft, stands as a leader in the realm of business analytics services. It provides interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. In the world of data analysis, Power BI facilitates the transformation, integration, and consolidation of vast amounts of data into actionable insights, presenting them through compelling visualizations.
In practical scenarios, such as the Netflix dataset illustrated in the tutorial, Power BI enables users to conduct holistic data examinations—from basic data cleaning to complex manipulation like sentiment analysis. Each step in the data analysis process is critical, as it helps in uncovering hidden patterns and trends that can significantly influence decision-making in a business context.
For beginners, understanding how to navigate Power BI and utilize its tools effectively can dramatically increase productivity and the ability to derive insights. For intermediate users, refining these skills can lead to more complex applications, including predictive analytics and machine learning integration.
Through tutorials like the one discussed, users not only learn technical skills but also develop a strategic approach to data analysis, making it an essential learning tool for anyone aiming to advance in data-driven fields.
In a recent educational video presented by Chandoo, viewers are taught how to initiate their journey into data analysis using Power BI, with a specific focus on a dataset from Netflix. The video serves as a practical guide for performing extensive Exploratory Data Analysis (EDA) through a series of structured steps. Each step is designed to enhance the learner's understanding of handling real-world data effectively.
The content kicks off with a brief introduction to the basics of data analysis and EDA utilizing Power BI. The initial segments of the video cover the crucial steps of loading data into Power BI and setting up the dataset by fixing common data issues such as improper headers or formatting discrepancies, thereby preparing the data for deeper analysis.
Subsequently, Chandoo explores a variety of analytical techniques. Key methods demonstrated include column profiling, managing missing data values, and advanced data cleaning particularly with date values. These techniques are practical for viewers aiming to refine their analytical skills and enhance data accuracy and usability.
The final sections of the video involve a recap of all the covered techniques and provide guidance on the next steps in data analysis with Power BI. It becomes apparent through the video that each step is interconnected, creating a comprehensive data analysis flow in Power BI that transforms raw data into insightful, actionable information.
For those seeking to enhance their data analysis skills, particularly using Power BI, Chandoo’s video provides a solid, easy-to-understand foundation. The video effectively uses a real-world dataset from Netflix to demonstrate applications of Power BI various data analysis techniques, making it both educational and directly applicable for viewers working with similar types of data.
Data analysis is a vital skill in many industries today, and learning tools such as Microsoft Power BI can significantly enhance one's ability to understand and manipulate large datasets. Tools like this enable users to perform a wide range of functions from basic data cleaning to sophisticated analytic techniques such as sentiment analysis and predictive modeling.
Power BI's capabilities allow users to seamlessly integrate various data sources, automate data refresh, and collaborate with team members on interactive visual reports. This functionality fosters a more data-driven decision-making process in businesses and organizations.
For professionals and students alike, understanding data through EDA is crucial. It helps uncover patterns, detect anomalies, and test hypotheses, which all contribute to better strategic decisions. EDA in Power BI can span from simple data inspections to complex data transformations and visualizations.
The Netflix dataset used by Chandoo in the tutorial is an excellent example of real-world data that analysts might encounter in the entertainment industry. It demonstrates how tools like Power BI are instrumental in transforming raw data into actionable insights that can influence content strategies and customer engagement metrics.
In essence, learning data analysis through practical examples such as this Netflix dataset not only enhances technical proficiency but also improves one's ability to apply these skills in real-world scenarios. Power BI remains one of the leading tools in the industry, providing robust support for a variety of data analysis needs.
As a Power BI data analyst, one's role involves collaborating closely with business stakeholders to comprehend their needs and requirements. This position requires working alongside enterprise data analysts and data engineers to source and manage the necessary data. Utilizing Power BI, the responsibilities extend to transforming this data and constructing comprehensive data models.
Power BI Desktop is designed to facilitate the generation of insights from data through a series of straightforward actions. However, there may be instances when the available data does not fully cover all the questions that need addressing. In such cases, using measures becomes essential. Measures are crucial tools in many typical data analysis scenarios within Power BI.
Power BI data analysis, Netflix data visualization, real-life Power BI example, Power BI tutorial, beginner Power BI guide, learn data analysis with Power BI, Netflix data Power BI, Power BI Netflix project | <urn:uuid:fecea08b-e345-4cd4-b2a6-211cc97f3340> | CC-MAIN-2024-38 | https://www.hubsite365.com/en-ww/crm-pages/your-first-real-life-data-analysis-with-power-bi-netflix-example.htm | 2024-09-08T18:24:18Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651017.43/warc/CC-MAIN-20240908181815-20240908211815-00412.warc.gz | en | 0.897862 | 1,072 | 2.703125 | 3 |
Here’s what to look Forward to, and to Fear, in the next Evolution of the Global Internet.
In reality the internet was in many respects a lucky accident.
It originated through a collection of US Government technology projects, that somehow grew into a global network.
Early enthusiasts envisioned the internet as a free and open space for exchanging information and innovation was perhaps just a dream.
However, as the internet (and the world wide web built on top of it) started to gather momentum, that optimistic viewpoint was pushed to the side, by more powerful forces, mostly do to money and power.
Areport from the influential Council on Foreign Relations warns, “The era of the global internet is over.“
Washington has worked closely over the last three decades with the private sector and allies to promote a vision of a global, open, secure, and interoperable internet, but the reality of cyberspace is now starkly different.”
“The internet is more fragmented, less free, and more dangerous.”
The rise of big technology companies over the last two decades has made the internet more usable for most people.
However, this has resulted in a small number of very large companies controlling what you search for online, where you share information with your friends, or even do your shopping.
Even worse, these companies have done much to develop what is effectively ‘surveillance capitalism’ taking the information we have shared with them (about what we do, where we go and who we know) to sell to advertisers and others.
As smartphones have become one of the key ways we access the web, that surveillance capitalism now follows us wherever we go.
The Rise Of Social Media (so-called ‘Web 2.0’ era)
A platform that was once about openness seems to now be dominated by big tech.
While the rise of social media (the so-called ‘Web 2.0’ era) promised to make it possible for individuals to produce and share their own content, it was still mostly the big tech companies that remained the gatekeepers.
Governments have realised the power of the internet and have become keen to harness it. While the internet has largely been a US invention, and tacitly controlled by the US since, that’s changing now.
Some governments enact laws and regulations which are understandable and benign, aiming to protect the rights and privacy of their citizens.
Meanwhile, other states try to protect their power by preventing people from accessing information and services.
The ‘Splinternet’ Effect
Internet shutdowns, where states decide to simply switch off the internet in times of crisis, are increasingly common.
As a result, the internet is increasingly fragmenting into zones of influence, the so-called ‘splinternet’ effect.
The Internet Society warned earlier this year, “Politicizing decisions about the Internet’s inner workings sets a dangerous precedent that puts us on the fast track to a ‘splinternet,’ an Internet artificially carved up along political, economic, and technological boundaries.”
“The effects may be irreversible, opening the door for further restrictions across the globe.”
“A world in which digital protectionism creates a ‘splinternet’ will be a world in which people in different countries lose the ability to learn from each other and interact with each other, a world in which people will be poorer in every sense of the word.”
“For economic, political and cultural reasons, it is vital that data can continue to flow freely across borders, and that governments work together to make this possible,” said financial services industry body TheCityUK in a recent report.
Projects such as the Great Firewall of China, which blocks access to many services and data sources hosted in the West, are the most obvious manifestations of this.
Russia, too has made efforts to distance itself from the broader internet, cutting off Russians from services like Facebook.
The Council on Foreign Relations points to moves by Beijing and Moscow, in particular, which are trying to create a vision of cyber sovereignty based on state control over the internet warns, “The international competition for power is accelerating the fragmentation of technology spheres.”
Big Tech Trends & Innovations
Despite these efforts to manage, commercialise and limit the reach of the internet, tech innovation continues, some of which claims to hold the key to reducing the concentration of power in the hands of the big tech companies.
Concepts like Web3 promise a decentralised vision of the internet whereby the power of the big tech companies is broken.
Instead, it’s the individual web user who will once again have the power over what they share and when, and who profits from it.
Web3 would use blockchain technologies to effectively create digital assets which you are then able to exchange or trade as you see fit.
Of course, the reputation of NFTs, blockchain, Bitcoin and much of the De-Fi world has taken a hammering recently, being widely viewed more as a source of dismal get-rich-quick schemes with some major security flaws. than
However, it’s clear that beyond this messy current situation lies the potential for significant disruption.
Virtual reality and augmented reality could allow the digital world to become visible around us, overlaying everyday reality with fantastic creatures or simply serving up reminders of useful information.
Big tech companies also see the emergence of these metaverse technologies as another opportunity to gain more control.
Whoever wins out in this new virtual world could find themselves with a permanently defensible near-monopoly on access to this digital universe, where they are making the decisions about what we see and do, and collecting all the money.
Web3 decentralised technologies such as NFTs and blockchain-based digital currencies might be a way of breaking these virtual monopolies by giving back some control.
Alternatively, they may simply create a new generation of tolls for us all to pay. Either way, they are likely at least a couple of years to a decade away from the mainstream according to tech analyst Gartner.
Just as virtual and augmented reality could mean the digital world is always in our eyeline, other tech trends may increasingly render the internet invisible to us.
Ambient computing aims to embed computing power in the world around us, so that we don’t need to be permanently glued to our screens. For example, smart homes that adapt to our behaviour without us needing to ask.
Cyber Security Awareness
While there could be big benefits it also means we are again handing over lots of intimate information about our lives.
That means privacy and security need to be stronger than ever, which will be a challenge as new innovations always create new security threats.
We haven’t dealt with today’s security challenges particularly well.
From this perspective there’s a high-risk digital Jenga, where a false move could see everything come tumbling down.
The internet and everything we build upon it has never been more central to modern societies, but its future has never been less clear.
There is still a route to building a fairer and more open internet, but the challenges have never been greater. | <urn:uuid:896f422d-15eb-4647-a854-4306c40914db> | CC-MAIN-2024-38 | https://www.bvainc.com/2022/09/20/the-future-of-the-web-the-good-bad-and-very-weird/ | 2024-09-12T12:14:11Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651457.35/warc/CC-MAIN-20240912110742-20240912140742-00112.warc.gz | en | 0.94887 | 1,496 | 2.546875 | 3 |
Enforce file upload limits and implement proper file management
This code represents a file upload feature in a Ruby on Rails application. The
action in the
is responsible for handling file uploads.
Here's how it works:
- It accepts a collection of files as a parameter (
- For each file in the collection, it creates a new instance of the
model, storing the file.
- After all files have been uploaded, it redirects the user to the uploads page.
The vulnerability lies in the fact that there is no limit to the number of files a user can upload. This means that a malicious user could potentially upload a large number of files, filling up the server's storage and potentially causing a Denial of Service (DoS) attack.
Additionally, the system does not delete any previously uploaded files when a new one is uploaded. This means that over time, old and potentially unneeded files could accumulate on the server, further exacerbating the potential for storage issues.
The updated code now includes a limit on the number of files that can be uploaded at a time, as well as a maximum file size for each file.
constant is set to 10, meaning that users can only upload up to 10 files at a time. If a user tries to upload more than this, they will be redirected back to the uploads page with an error message.
constant is set to 5 megabytes. If a user tries to upload a file that is larger than this, they will be redirected back to the uploads page with an error message.
When a file is uploaded, the
method is called on the
model. If there are any errors with this (for example, if the file is of an invalid type), these errors are added to the
hash and the user is redirected back to the uploads page.
If all files are uploaded successfully, a success message is displayed to the user.
This code does not yet include a file retention policy to delete old files from the server. This would need to be implemented separately, perhaps as a background job that runs periodically to delete files that are older than a certain age. | <urn:uuid:b626312c-8eca-40c2-b6c7-66f2a7c3d40a> | CC-MAIN-2024-38 | https://help.fluidattacks.com/portal/en/kb/articles/criteria-fixes-ruby-354 | 2024-09-14T20:33:03Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651580.74/warc/CC-MAIN-20240914193334-20240914223334-00812.warc.gz | en | 0.960896 | 441 | 2.59375 | 3 |
Data Management Glossary
Cloud archiving, a term that is often used interchangeably with cloud tiering, is a data storage strategy that involves moving inactive or infrequently accessed data from primary storage systems to long-term archival storage in the cloud. The primary goal of cloud archiving is to free up space on primary storage systems while retaining access to archived data for compliance, legal, or historical purposes.
Key characteristics and considerations of cloud archiving include:
- Long-Term Retention: Cloud archiving solutions are designed for storing data for extended periods, often spanning years or even decades. They typically offer features such as data durability and integrity checks to ensure that archived data remains intact and accessible over time.
- Cost-Effectiveness: Cloud archiving services often provide cost-effective storage options optimized for long-term retention. These storage options typically offer lower data storage costs per unit compared to primary storage systems, making them suitable for storing large volumes of inactive data.
- Scalability: Cloud archiving solutions offer scalability to accommodate growing volumes of archived data without the need for significant upfront investments in infrastructure. Organizations can scale their archival storage resources on-demand based on their evolving storage requirements.
- Data Security and Compliance: Cloud archiving solutions prioritize data security and compliance by implementing encryption, access controls, and other security measures to protect archived data from unauthorized access or tampering. Additionally, they may offer features such as audit logs and compliance certifications to help organizations meet regulatory requirements.
- Data Accessibility: While archived data is typically accessed infrequently, cloud archiving solutions ensure that archived data remains accessible when needed. They provide mechanisms for retrieving and accessing archived data, such as retrieval APIs or web-based interfaces, allowing organizations to retrieve specific data sets or perform data restores as necessary.
- Data Lifecycle Management: Cloud archiving solutions often include features for managing the entire data lifecycle, from initial archiving to eventual deletion or retention expiration. They may offer automated policies for migrating data to archival storage, as well as retention policies for specifying how long data should be retained in the archive.
Overall, cloud archiving enables organizations to effectively manage their data storage needs by offloading inactive data to cost-effective, scalable, and secure cloud-based archival storage solutions. By doing so, organizations can optimize their primary storage resources, reduce data storage costs, and ensure compliance with data retention requirements. | <urn:uuid:06f3aefd-46de-4756-b524-1bfb49606c22> | CC-MAIN-2024-38 | https://www.komprise.com/glossary_terms/cloud-archiving/ | 2024-09-19T21:59:23Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652067.20/warc/CC-MAIN-20240919194038-20240919224038-00412.warc.gz | en | 0.92134 | 489 | 2.5625 | 3 |
In the fall of 2016, a new kind of attack was launched against web-connected devices. A powerful piece of malware called Mirai hacked into and then harnessed the connectivity of thousands of gadgets, creating a botnet capable of launching a Distributed Denial of Service (DDoS) attack against web platforms, shutting down web access in huge portions of the US and Europe for several hours. Just about a year later, a copy-cat named Reaper took what Mirai had done and multiplied it, gathering a botnet army of somewhere around a million devices. That’s a lot of gadgets, ready and waiting to do the unknown–but certainly nefarious–bidding of a hacker. A DDos attack might, in fact, be the least of our worries–another botnet powerful enough to shut down the web could potentially wreak much more serious havoc on our society if we do not understand preventative security.
What makes an attack of this type tricky in a new and unique way is the type of devices it uses to get around and gather horsepower. Unlike viruses that infect PCs or mobile devices—which our security measures are at least somewhat equipped to handle at this point–botnet viruses target any Internet of Things (IoT) devices they can get ahold of. For Mirai, it was Linux devices like routers and IP cameras whose default passwords never got reset. Reaper took things a step further by actively hacking into “a range of consumer and commercial products.” More than anything else, this hack demonstrated the variety of devices that are potentially susceptible to attack. Both of these attacks focused primarily on home and office routers and cameras, but they serve as a startling reminder of all the devices we rarely think of as “hackable” that are, in fact, easy targets. It’s been projected that, by the end of 2018, somewhere in the ballpark of 8 billion devices will be part of the IoT: and very few of these devices are as well-protected as PCs. This leaves a lot of potential targets for the next botnet attack, including any “smart” gadget: app-controlled thermostats, smart locks, even the ubiquitous Amazon Echo. Basically, all the things we use on a daily basis without even thinking.
These devices pose a significant danger at home and at the workplace, and not just because they could be harnessed into a DDoS or similar attack. Consider what information a hacker would be able to access if they breached an IoT device connected to the same network as your PC. Botnets and DDoS attacks aren’t the only risk that IoT devices pose to us—on a smaller but equally destructive scale, hackers can access other data on a network by hacking a poorly protected gadget. This is perhaps even more of a risk at the workplace, where computers are likely to house even more sensitive information than a personal PC. Reaper targeted a million organizations—imagine the kind of information it could have gotten ahold of if its goal had been to access private data through the devices it hacked.
Given that fact, how can we stay safe with preventative security? How can we ensure that the devices we use–all of them–are safe against outside attack? First of all, be aware of software bugs, and any patches that the manufacturer might offer for them. While few “smart” devices are likely to come with the same caliber of software updates and protections as computers, there are more security implementations available than you might think. Take advantage of them, the same way you would for your PC (and if you’re not updating your PC, that’s an even worse problem).
Something else to keep in mind with Preventative Security is this: how many of your “smart” devices are worth the risk? Given that even the best-secured gadget isn’t likely to come close to being as secure as, say, your PC, how many of them do you really want–or need? I would recommend taking an inventory of all devices you own that connect to your network. Some, you can’t do without–like your router. And most routers can be updated regularly. But what about the others? While it might be convenient to turn on your heat from your phone, or for a smart-pod to be able to play your favorite music on-command, is it worth the possibility of a hack? Convenience only comes at a cost. And that cost might just be loss of important data or an internet blackout.
At the end of the day, all progress comes with its own cost/benefit analysis. In many ways, the IoT is making our lives easier and more streamlined. But it’s also making them infinitely riskier and more complicated. Our ancestors’ predictions of artificial intelligence and a world run by robots are not so far off. The IoT is real. It surrounds us. We can limit its hold over our lives, but without retreating to the woods to live as hermits, we’ll never be able to avoid it completely. So, we really only have one option: be smart, and be vigilant with Preventative Security. We need to utilize every tool at our disposal, including updates and system checks. We need to educate ourselves about how to keep our systems secure. And we need to stay on top of current threats. As the IoT continues to grow and the risks increase, there’s no greater danger to us than lack of awareness.
What Can You Do?
Get More Resources on Leadership
3 Tips to Transition from Optional to Mandatory Security Awareness Training
Cyber Security Awareness – Lead by Knowledge, Not Fear
Request information on our course – Leading a Secure Organization | <urn:uuid:1c72f4bb-ba03-468d-beb9-bd39a71ad74d> | CC-MAIN-2024-38 | https://globallearningsystems.com/preventative-security/ | 2024-09-07T17:51:54Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700650898.24/warc/CC-MAIN-20240907162417-20240907192417-00612.warc.gz | en | 0.956436 | 1,170 | 2.78125 | 3 |
On Sunday, August 6, an undersea landslide in one of the world’s longest submarine canyons knocked out two of the most important submarine cables serving the African internet. The loss of these cables knocked out international internet bandwidth along the west coast of Africa. In this blog post, we review some history of the impact of undersea landslides on submarine cables and use some of Kentik’s unique data sets to explore the impacts of these cable breaks.
On Sunday, August 6, an undersea landslide in one of the world’s longest submarine canyons knocked out two of the most important submarine cables serving the African internet. The landslide took place in the Congo Canyon, located at the mouth of the Congo River, separating Angola from the Democratic Republic of the Congo.
The SAT-3 cable was the first to suffer an outage, followed hours later by the failure of the WACS cable. The loss of these cables knocked out international internet bandwidth along the west coast of Africa. In this blog post, I review some history of the impact of undersea landslides on submarine cables and use some of Kentik’s unique data sets to explore the impacts of these cable breaks.
Seismic threats to submarine cables
By far, the greatest threat to the submarine cables connecting the global internet is human maritime activity. This usually involves seafaring vessels breaking submarine cables either by snagging them during fishing operations (especially trawling) or by inadvertently dragging their anchors along the seafloor, the cause of the 2008 submarine cable cuts in the Mediterranean Sea.
But after marine activity, the next biggest category of threat consists of natural causes — and let me emphasize, I’m not talking about sharks biting cables. On numerous occasions, undersea landslides and earthquakes have damaged cables laying on the seafloor.
In December 2006, a large earthquake off the southern coast of Taiwan crippled internet communications in East Asia by rupturing numerous submarine cables. According to a press release from the International Committee for the Protection of Cables, as a result of the Hengchun earthquakes, “21 faults were recorded in … 9 cables, and it took 11 ships 49 days to restore everything back to normal.”
During a panel at the Suboptic 2013 submarine cable conference in Paris, the audience listened in rapt attention as a speaker from Japan described the efforts to repair submarine cables damaged by the Great East Japan Earthquake two years earlier. According to him, one of the cables had been dragged over a kilometer by an undersea landslide triggered by the powerful earthquake. Additionally, the sequence in which the cables were to be restored was driven, not by usual contractual priorities, but by where the cable ship could safely navigate while avoiding the radiation cloud emanating from the crippled Fukushima Daiichi Nuclear Power Plant.
In another case, a decade ago, I wrote about an undersea earthquake in the Black Sea that unexpectedly impacted Iranian transit. It was initially reported that an underwater volcano had severed a submarine cable in the Black Sea running between Poti, Georgia, and Sochi, Russia. This caught the attention of WIRED magazine’s resident geologist, who dutifully pointed out that there were no volcanoes in the Black Sea. As was later reported in the Iranian press, it was an earthquake that led to the failure of the cable — likely by triggering another underwater landslide.
Finally, this isn’t the first time that these cables (SAT-3 and WACS) have been downed by undersea landslides in the Congo Canyon. A study, published in June 2021, described how these cables had suffered breaks in 2020 due to, in one instance, “an exceptionally large and powerful submarine mudslide that originated at the mouth of the Congo River.”
Make no mistake; the seafloor can be a dangerous place for cables.
Internet impacts due to the cable cuts
Shifting back to the cable cuts in Africa, let’s begin by looking at the impact on cloud connectivity.
Last year, a terrestrial cable cut in Egypt temporarily knocked out service for multiple submarine cables, a situation I analyzed by illustrating the impact on internal connectivity for the three major public cloud providers: AWS, Azure, and Google Cloud. Well, this cable incident was no different, proving once again that even the big hyperscalers must rely on the same submarine cable infrastructure as everybody else.
Below is a screenshot of our performance monitoring from af-south-1
, AWS’s region in Cape Town, South Africa, to eu-west-2
in London, England. It shows an increase in latency, from 150 to 195 ms, as AWS’s traffic is diverted to a backup route, presumably with a longer geographic distance, to reach London in this example.
Conversely, we can also see a drop in latency from af-south-1 to some points in Asia. The screenshot below shows a latency decrease from 386 to 304 ms from Cape Town to Seoul at 17:30 UTC, when the WACS cable was cut.
While this may seem counterintuitive, this is a phenomenon I have often encountered when analyzing submarine cable cuts — see slide 10 in my presentation at Suboptic 2013. Essentially a higher latency route becomes unavailable, and traffic is forced to go a more direct path.
Why would traffic be using the higher latency path in the first place? What you can’t see in these visualizations are factors like cost. The business case for maintaining the lowest possible latency between Cape Town and Seoul may not justify a higher-cost but lower-latency route.
Traffic volume as measured by aggregate NetFlow
We observed a drop in traffic volume as seen in our aggregate NetFlow to the affected countries following the cable cuts. Let’s take a closer look at the impacts in the largest affected market, South Africa. According to our data, the largest traffic destination in South Africa is Telkom SA (AS37457), who experienced a 20% drop in peak traffic following the cuts.
Namibia was another country in southwest Africa impacted by these cable cuts. When WACS was cut at 17:30 UTC, Telecom Namibia (AS20459) lost transit from Cogent (AS174) and BICS (AS6774). Two hours later, the Namibian incumbent partially restored service using transit from Angola to the south.
Kentik Market Intelligence (KMI) also reported on these changes. Recall that KMI, based on BGP, enables users to navigate the dynamics hidden in the global routing table by identifying the ASes operating in any given country, determining their providers, customers, and peers, and reporting when there are changes to those relationships.
Telecom Namibia, for example, lost its two main transit providers Cogent (AS174) and BICS (AS6774) as a result of the WACS cable cut. To restore service, it had to activate emergency service from Angola Cables (AS37468). Those developments were reported in KMI Insights and are shown below.
Since KMI is strictly based on interpreting BGP data, let’s see what an individual route change looked like. Let’s take this Telecom Namibia route as an example: 220.127.116.11/19.
When we take the upstream view from AS20459, we can see that, like the NetFlow-based graphic above, Telecom Namibia lost AS174 and AS6774 at around 17:30 UTC and gained transit from AS37468 at 22:00 UTC on August 6. In the interim, the reachability of the route became very low, along with traffic reaching its destination.
At the time of the cuts, the cable repair ship operating in the region (CS Leon Thevenin) was busy with submarine cable work in West Africa but has since shifted its mission and set sail for Cape Town, South Africa. Once on location, the repairs may take additional weeks to complete leaving a significant portion of the African internet without critical internet bandwidth well into September.
To make up for the loss of capacity, traffic has been shifted to other submarine cables, such as Google’s new Equiano cable, which was activated earlier this year. Like WACS and SAT-3, Equiano also runs along the west coast of Africa, but was not impacted by the undersea landslide earlier this month. This fact was highlighted by Equiano client Liquid Dataport (formerly Liquid Telecom) in a press release last week. Liquid has managed to use their service on Equiano to fill the gaps left by the loss of WACS and SAT-3.
For more information about the fascinating world of submarine cables, check out our Telemetry Now podcast episode with Alan Mauldin of Telegeography. | <urn:uuid:cfeefc20-a3d9-4e74-9da2-87c5f9c090f9> | CC-MAIN-2024-38 | https://www.kentik.com/blog/dual-subsea-cable-cuts-disrupt-african-internet/ | 2024-09-08T23:43:54Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651035.2/warc/CC-MAIN-20240908213138-20240909003138-00512.warc.gz | en | 0.949714 | 1,810 | 3.421875 | 3 |
Are you tired of your computer’s loud and noisy fan? Or do you want to increase the fan speed for better cooling performance? Whatever the reason may be, changing the CPU fan speed without accessing the BIOS can seem like a daunting task. However, with the right knowledge and tools, it is possible to adjust the fan speed without having to enter the BIOS settings.
In this article, we will discuss various methods that you can use to change the CPU fan speed without BIOS.
- Understanding CPU Fan Speed
- Why Change CPU Fan Speed Without BIOS?
- Possible Methods for Changing CPU Fan Speed
- Precautions to Take When Changing CPU Fan Speed
Understanding CPU Fan Speed
Before we dive into the methods of changing CPU fan speed without BIOS, let’s first understand what exactly is CPU fan speed and why it is important. The CPU fan is responsible for keeping the processor cool by circulating air over its heat sink. The fan speed is measured in revolutions per minute (RPM) and it determines how fast the fan blades spin. The higher the RPM, the faster the fan spins and the more air it moves.
The ideal fan speed for your CPU depends on various factors such as the type of processor, the workload, and the ambient temperature. If the fan speed is too low, the CPU may overheat and cause damage to the system. On the other hand, if the fan speed is too high, it can create unnecessary noise and put extra strain on the fan motor. Therefore, it is important to find the right balance for your CPU fan speed.
Why Change CPU Fan Speed Without BIOS?
Traditionally, the only way to change the CPU fan speed was through the BIOS settings. However, not all computers have a user-friendly BIOS interface and some may not even allow access to the fan speed settings. Moreover, constantly entering the BIOS to make changes can be time-consuming and inconvenient. This is where the need for alternative methods to change the CPU fan speed without BIOS arises.
Another reason to change the fan speed without BIOS is for those who are not comfortable with making changes to their computer’s BIOS settings. Messing with the BIOS can be risky and may lead to system instability if not done correctly. Therefore, using alternative methods can provide a safer and more user-friendly approach to adjusting the fan speed.
Possible Methods for Changing CPU Fan Speed
There are several methods that you can use to change the CPU fan speed without accessing the BIOS. Each method has its own advantages and limitations, so it is important to choose the one that best suits your needs. Let’s take a closer look at each method.
Method 1: Using Third-Party Software
One of the easiest ways to change the CPU fan speed without BIOS is by using third-party software. There are various free and paid software available that allow you to monitor and control your fan speed. These software programs work by communicating with the fan controller on your motherboard and adjusting the fan speed accordingly.
Some popular options for controlling fan speed include SpeedFan, Argus Monitor, and HWiNFO. These software programs not only allow you to adjust the fan speed but also provide real-time monitoring of your system’s temperature and fan speeds. They also offer customizable fan profiles, allowing you to set different fan speeds for different scenarios such as gaming or idle mode.
However, it is important to note that not all motherboards are compatible with third-party software. You may need to do some research to ensure that your motherboard supports fan control through these programs. Additionally, make sure to download the software from a trusted source to avoid any potential malware or viruses.
Method 2: Modifying System Settings
Another way to change the CPU fan speed without BIOS is by modifying the system settings. This method involves changing the power plan settings on your computer, which can affect the fan speed. By default, most computers are set to the “Balanced” power plan, which aims to balance performance and energy consumption. However, switching to the “High Performance” power plan can increase the fan speed and provide better cooling for your CPU.
To change the power plan settings, follow these steps:
- Open the Control Panel on your computer.
- Click on “Hardware and Sound” and then select “Power Options.”
- In the Power Options window, click on “Change plan settings” next to the selected power plan.
- Click on “Change advanced power settings.”
- In the Advanced Settings tab, scroll down to “Processor power management” and expand it.
- Expand “System cooling policy” and change the settings for both “On battery” and “Plugged in” to “Active.”
- Click on “Apply” and then “OK” to save the changes.
This method may not work for all computers, as some may not have the option to change the system cooling policy. Additionally, switching to the High Performance power plan can increase energy consumption and may not be suitable for laptops or devices with limited battery life.
Method 3: Adjusting Fan Speed in BIOS
Although this article is focused on changing the CPU fan speed without BIOS, it is worth mentioning that accessing the BIOS is still one of the most effective ways to control fan speed. Most modern motherboards come with a built-in fan control feature in the BIOS, allowing you to adjust the fan speed according to your needs.
To access the BIOS, restart your computer and press the designated key (usually F2 or Delete) repeatedly during the boot-up process. Once in the BIOS, navigate to the “Hardware Monitor” or “Fan Control” section and make the necessary changes to the fan speed settings. Keep in mind that the BIOS interface may vary depending on your motherboard manufacturer.
Method 4: Replacing the CPU Fan
If none of the above methods work for you, or if you are looking for a more permanent solution, you can consider replacing your CPU fan. Upgrading to a better and more efficient fan can not only provide better cooling for your CPU but also give you the option to control the fan speed through the BIOS or third-party software.
When choosing a new CPU fan, make sure to check its compatibility with your motherboard and ensure that it is suitable for your processor’s TDP (thermal design power). You may also want to consider factors such as noise level, size, and airflow when making your decision.
Precautions to Take When Changing CPU Fan Speed
Before attempting to change the CPU fan speed without BIOS, it is important to take some precautions to avoid any potential damage to your system. Here are some things to keep in mind:
- Make sure to research and understand the methods before attempting to change the fan speed.
- Always download software from trusted sources to avoid any potential malware or viruses.
- Keep an eye on your system’s temperature after making changes to the fan speed.
- If using third-party software, regularly update it to ensure compatibility with your system.
- When accessing the BIOS, be cautious and make changes only if you are familiar with the settings.
- If replacing the CPU fan, follow proper installation procedures and ensure compatibility with your system.
Changing the CPU fan speed without BIOS may seem like a challenging task, but with the right knowledge and tools, it can be easily achieved. Whether you choose to use third-party software, modify system settings, or replace the CPU fan, make sure to do your research and take necessary precautions to avoid any potential issues. By finding the right balance for your CPU fan speed, you can ensure optimal performance and longevity of your computer.
Information Security Asia is the go-to website for the latest cybersecurity and tech news in various sectors. Our expert writers provide insights and analysis that you can trust, so you can stay ahead of the curve and protect your business. Whether you are a small business, an enterprise or even a government agency, we have the latest updates and advice for all aspects of cybersecurity. | <urn:uuid:38b8ab84-f008-461a-939c-f82f00a0cf3b> | CC-MAIN-2024-38 | https://informationsecurityasia.com/how-to-change-cpu-fan-speed-without-bios/ | 2024-09-13T21:46:18Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651540.48/warc/CC-MAIN-20240913201909-20240913231909-00112.warc.gz | en | 0.909856 | 1,667 | 2.8125 | 3 |
Spontaneous Robot: Researchers are now planning to introduce autonomous functions to robots such as spontaneity, which has been a sought after trait in robots and unachievable till now.
Coypright by www.analyticsindiamag.com
Humans have been obsessed with making robots human-like. While there have been many developments to bring about cognitive features such as emotions, intellect and common sense in robots, the success rate hasn’t been entirely satisfactory. However, researchers are now planning to introduce autonomous functions to robots such as spontaneity, which has been a sought after trait in robots and unachievable till now.
Researchers at Intelligent Systems and Informatics Laboratory and the Next Generation Artificial Intelligence Research Center at the University of Tokyo have explored this dimension in robots inspired by animals, including humans. Further, roboticists often design robot behaviours using predefined modules and control methodologies, which makes them task-specific, limiting their flexibility.
To overcome the challenge, researchers suggested an alternative machine learning-based method for designing spontaneous behaviours by capitalising on complex temporal patterns such as neural activities of animal brains. With this research, they hope the design will be implemented in robotic platforms to improve their autonomous capabilities.
What Have Researchers Done?
Designing robots and their controls are a dynamic system that works on a mathematical model describing the ever-changing internal states. Often classified as the high-dimensional chaos, which is one of the classes of the dynamic system, researchers have constantly explored modelling animal brains based on this system.
However, one of the significant challenges is the ability to gain control over the high-dimensional chaos as the system is highly complex and sensitive to varying initial conditions. This phenomenon in the scientific community has been popularised as the “butterfly effect.”
In recent research, researchers have used Chaotics Itinerancy to design spontaneous behaviour in robots. As they explain, Chaotic Itinerancy (CI) is a frequently observed phenomenon in high-dimensional nonlinear dynamical systems and is characterised by itinerant transitions among multiple quasi-attractors. […]
Read more: www.analyticsindiamag.com
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR! | <urn:uuid:24fa9142-40ae-4208-a763-c842dddadb60> | CC-MAIN-2024-38 | https://swisscognitive.ch/2020/11/18/spontaneous-robot/ | 2024-09-13T20:58:02Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651540.48/warc/CC-MAIN-20240913201909-20240913231909-00112.warc.gz | en | 0.947535 | 465 | 3.1875 | 3 |
Vulnerabilities found in Gmail can be exploited by phishing attacks
Two vulnerabilities have recently been found in Gmail. The major concern is that the flaws allow Gmail to be used in phishing attacks, which is when cybercriminals try to impersonate known brands and people to deceive their victims.
The bugs were described by software developer Tim Cotten, who reported his findings in blog posts and also to Google.
Table of Contents
Hiding the sender email address
One of the flaws allows a cybercriminal to forge the From field, making the sender’s email address look anonymous. It means, as Cotten outlined, “a completely blank sender”.
This bug can be exploited, for example, by fraudsters who want to impersonate Google, sending emails to users regarding official and system warnings. Even a user with experience in the Gmail platform could click on a malicious link or a malicious attachment believing that it would be a legitimate message.
“By tailoring a malicious input in a certain way the Gmail app leaves the sender display completely blank both in the list view and in the detailed email view. This could be further weaponized for phishing attacks based on faking the appearance of official warnings or system messages”, said Cotten.
Falsifying the From field
The other vulnerability allows scammers to place emails into the Sent folder of their targets. Yes, you’ve never sent that email, but, even then, it will be labeled in your folder as a sent message.
As Cotten pointed out, “you can force an email to enter someone’s Gmail Inbox, Sent folder, and in:sent filter by adding their own email to the From field’s name area (the part in quotes)”.
The bug is both worrying and dangerous as users may feel tempted to confirm the emails by clicking on malicious links or even malicious attachments, which can lead to malware and ransomware infections. | <urn:uuid:7b3de4ba-9a71-4105-b802-6001577be9a2> | CC-MAIN-2024-38 | https://gatefy.com/blog/vulnerabilities-gmail-can-be-exploited-phishing/ | 2024-09-15T04:22:09Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651614.9/warc/CC-MAIN-20240915020916-20240915050916-00012.warc.gz | en | 0.950364 | 402 | 2.53125 | 3 |
This week’s myth is interesting because if we weren’t talking security it wouldn’t be a myth. Say what?
The phrase “96 more bits, no magic” is basically a way of saying that IPv6 is just like IPv4, with longer addresses. From a pure routing and switching perspective, this is quite accurate. OSPF, IS-IS, and BGP all work pretty much the same, regardless of address family. Nothing about finding best paths and forwarding packets changes all that much from IPv4 to IPv6. For many experienced network engineers, instruction in IPv6 contains a lot of things that can be described to “work just like in/with IPv4.”
This likely explains why virtually every transit provider and backbone operator on the planet has already rolled out IPv6. If all you’re concerned about is moving data, the phrase is true: IPv6 is 96 more bits, no magic.
From a security perspective however, that view has some complications.
Myth: 96 More Bits, No Magic
Reality: IPv6 Address Format is Drastically new
Routing 128 bit addresses is really not much different from routing 32 bit addresses. There’s a source address, a destination address, and hopefully a path or more between them.
Things get more complicated when we start talking about securing the network though. In addition to IPv6 addresses being 96 bits longer, they are also represented in hexadecimal notation instead of decimal. They use colons as delimiters instead of periods. They also introduce zero compression, in addition to zero suppression, expanding the possible formats that an IPv6 address may be represented in.
So what? Well, a lot of network security involves either filtering or forensics, both of which are often heavily (or completely) reliant on identifying nodes by IP address. You can no longer grep logs for decimal numbers separated by periods to find all instances of IP addresses. Now you need to look for hex characters and colons—and don’t forget to think about those double colons! Scripts, filters, and other tools written with IPv4 addresses in mind must be updated to handle IPv6 addresses.
Myth: 96 More Bits, No Magic
Reality: Multiple Addresses on Each Node
To make matters even more complicated, IPv6 nodes (hosts) are pretty much assumed to always have multiple addresses. At the very least they should all have a link-local IP address and a Global Unicast Address (GUA / public IP address), likely in addition to a legacy IPv4 address. Many nodes will also have a Unique Local Address (ULA—somewhat similar to RFC1918 address space in IPv4), one or more constantly changing privacy addresses, and other GUAs as needed.
This means that the node you are searching for may have a different IP address in the logs than the one you are looking for. It means that you may need to filter multiple addresses to have the desired affect on a single node. It means a paradigm shift in how you think about IP addresses as they relate to securing your network.
Myth: 96 More Bits, No Magic
Reality: Syntax Changes
In addition to changing how we think about IP addresses in this new IPv6 enabled world, we must also deal with syntax changes on our gear.
One of the great things about deploying a new version of IP is that we can use the opportunity to fix mistakes made in the old version. This is as true at the software and hardware level as it is at the network and security levels. The downside of this is that improvements at many equipment manufactures mean new syntax for network operators and security experts alike.
Instead of just ping, we now must remember to ping6. Our old friend tracert requires that we add -6 when executing an IPv6 traceroute. The ‘show route’ command is now supplemented by ‘show ipv6 route’ on some routers. The list goes on and on, and is different for each platform or vendor.
These changes affect everyone. As we learned in Myth #1; ignorance is no protection, and no excuse. To keep your network secure today, you must learn the new syntax of IPv6.
Myth: Configure IPv6 Filters the Same as IPv4
Reality: DHCPv6 and Neighbor Discovery Introduce Nuance
This is a more specific version of the ‘no magic’ myth and again, it’s not far from the truth. From a policy perspective you really should treat IPv6 and IPv4 security the same. For example: If a particular activity, destination, or traffic type is blocked for IPv4 it should very likely be blocked for IPv6 as well. The nuts and bolts of doing this aren’t quite the same however.
We’ve already talked about how address format, multiple addresses, and syntax changes may affect your configurations and actions. In addition to these general considerations, firewall filters have a couple of additional things to remember.
One of the biggest things to keep in mind when creating IPv6 filters is that Neighbor Discovery (ND) uses ICMP. This of course means that default ‘deny all ICMP’ rule you are likely to be using in legacy IPv4 filters can’t be copied over directly. Another consideration that may not be obvious at first is that DHCPv6 messages use link-local addresses, which you may typically want to filter out (why would link-local traffic be transiting a router?).
Here is an example stateful firewall filter for a Mikrotik router:
Flags: X—disabled, I—invalid, D—dynamic
0 ;;; Not just ping—ND runs over icmp6.
chain=input action=accept protocol=icmpv6 in-interface=ether1-gateway
1 chain=input action=accept connection-state=established in-interface=ether1-gateway
2 ;;; related means stuff like FTP-DATA
chain=input action=accept connection-state=related in-interface=ether1-gateway
3 ;;; for DHCP6 advertisement (second packet, first server response)
chain=input action=accept protocol=udp src-address=fe80::/16 dst-address=fe80::/16
4 ;;; ssh to this box for management (note non standard port)
chain=input action=accept protocol=tcp dst-address=[myaddr]/128 dst-port=2222
5 chain=input action=drop in-interface=ether1-gateway
As you can see, rule 0 is in place to allow ND to work and rule 3 allows the node to hear its own DHCPv6 reply. This is just an example but hopefully it illustrates the point: There are subtle differences between IPv4 and IPv6 that must be considered when securing modern networks. | <urn:uuid:370e9dd1-e6c3-48c7-bb7b-56eabfa37520> | CC-MAIN-2024-38 | https://circleid.com/posts/20150301_ipv6_security_myth_7_96_more_bits_no_magic | 2024-09-16T06:44:37Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651676.3/warc/CC-MAIN-20240916044225-20240916074225-00812.warc.gz | en | 0.928295 | 1,434 | 2.875 | 3 |
The promise of artificial intelligence (AI) is that it could remove the possibility of human error. Indeed, it is already showing great potential across a number of disciplines.
A recent study found that the technology is already rivalling the accuracy of healthcare professionals; an AI system used to predict breast cancer based on X-ray scans performed, on average, 11.5% better than radiologists – even when the humans were given additional information like patient and family histories.
The question is, would patients ever be willing to put their faith entirely in AI to perform medical procedures? What’s more, how would society respond if any mistakes were made by machines?
Let’s go with an example to put this dilemma into perspective. Picture this: a patient must undergo routine surgery and is presented with two options – the operation is either carried out by a human doctor or the surgery is performed entirely by AI. To inform this decision, the patient is also told that the human doctor has an 89% success rate, while the AI performing the operation has a 95% success rate.
Rationally, it would make sense to choose the AI based on its higher success rate. However, it is natural for people to still hold apprehensions when it comes to trusting machines over humans. Many will argue that AI simply can’t replace inherent ‘human’ qualities, such as empathy, which inspire trust and confidence.
Moreover, there is still a risk of something going wrong even with a higher likelihood of success. Would humans expect AI to function faultlessly, and thus be less forgiving if it made a mistake?
Why we should forgive AI
From a philosophical standpoint, humans might be less willing to forgive crucial mistakes made by machines. After all, in our minds they are designed to improve accuracy and efficiency. This poses an interesting dilemma, and something we as a society will need to confront as AI becomes integrated into our daily lives.
Let us play devil’s advocate for a moment. It is true that mistakes made by AI can cause unintended consequences. But if they are far and few between, is this better in the long run as we attempt to mitigate human error? After all, how else can we refine the technology if we do not let it learn from its mistakes?
The World Health Organisation has indicated that 1.35 million people die in road traffic accidents every year. Driverless cars have subsequently been deemed an important technology in reducing a portion of those deaths caused by human error.
A 2017 study from RAND Corporation found that, in the long term, deploying driverless cars that are just 10% safer than the average human driver will save countless lives– preventing thousands, if not hundreds of thousands of casualties. Importantly, this demonstrates that we do not have to wait for the autonomous vehicles to be 75% better, or even 90% better than humans for a huge impact to be made.
Despite the compelling evidence, we must work to gain public support for solutions which set out to improve safety standards. As we have seen with the tragic pedestrian fatality in 2018 at the hands of an autonomous vehicle, mistakes made by technologies that we consider relatively safe will incur a major backlash.
While this is an extreme example of an AI failure, it highlights the reality that machines will make mistakes before they are perfected. The machine learning (ML) element of many AI toolsets enables algorithms to constantly learn and improve. Each time new data is inputted – whether this is a new X-ray scan or traffic situation – ML algorithms will fine-tune their decision-making and demonstrate better results the next time around. So, while at first self-driving cars might struggle with unexpected circumstances on the road, every encounter is a new opportunity to learn. In time, they will reach new levels of ‘perfection’ and become more capable at interacting with, and understanding, the world.
That is why it is important to be able to forgive AI. While it might be difficult to excuse a machine, like humans it will make mistakes as it learns. Only by letting AI fail will it truly progress.
New research coming soon…
In a society where humans and AI are beginning to coexist, our relationship with machines is forever being transformed. The objective is to ensure we are compassionate and willing to let AI fulfil its true potential, which will ultimately benefit society.
Here at Fountech.ai, we will soon be releasing some exciting new research which will show just how willing people are to trust and forgive AI. Stay tuned for upcoming announcements… | <urn:uuid:0ef0968c-3a18-4a25-bb26-4005308ba48f> | CC-MAIN-2024-38 | https://resources.experfy.com/ai-ml/should-we-forgive-ai/ | 2024-09-16T06:06:29Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651676.3/warc/CC-MAIN-20240916044225-20240916074225-00812.warc.gz | en | 0.961071 | 926 | 3.25 | 3 |
New Iceland-Ireland subsea cable could drive sustainable AI
The subsea cables that make up the earth’s ‘digital central nervous system’, transmitting the majority of the world’s data across oceans at 99.7% of the speed of light, are our most efficient way of sending information around the globe. With higher carrying capability and lower latency than transporting data via satellites, these cables form the backbone of the internet, facilitating the quick global transfer of data – especially when there are multiple paths available between countries.
The Icelandic government recently announced plans for ‘IRIS’, a new subsea cable connecting the country to Ireland. The country already has two connections to Europe: FARICE-1, which connects Iceland and the United Kingdom, and DANICE, connecting it to Denmark. As its third connection to Europe, IRIS will further strengthen Iceland’s global connectivity and digital edge.
Subsea cables provide island nations – such as Iceland, or for that matter, Australia and the UK – with international connectivity, and advance their role in the global digital ecosystem. As a third cable providing two levels of redundancy, IRIS and other cables like it significantly reduce the impact of cable faults. However, on the flip side, as countries and enterprises around the globe go through almost continuous digital transformation, the growth in cloud computing that these cables support has become a cause for environmental concern.
The UN stated that this year is the year that the world must act to avoid runaway climate change. According to The Shift Project research, Information and Communications Technology (ICT) already accounts for approximately 4% of worldwide carbon emissions. High intensity compute in particular contributes to this hugely: AI models themselves can be so power-hungry that the carbon emissions from training one deep learning model can be up to 5 times greater than the amount generated during the entire lifetime of a car, per research conducted by the University of Massachusetts in 2019.
Unfortunately, the phenomenal growth we’ve seen in recent years in cloud computing means that even as computer server technology continues to improve, the consumption of power by data centres could double over the next ten years. Indeed, European Commission research shows that one viral video – whether that’s Despacito’s 7.03bn YouTube views or Baby Shark Dance’s 6.98bn – can consume the same energy as an entire nation’s energy requirements for a whole year.
Indeed, just a few years ago, a Toronto-based company proposed plans for a subsea cable that would run through the Arctic and connect Tokyo to London through a route 4,280km shorter than the existing available low-latency routes that run through the Suez Canal. The rub is that running a cable through this location would have previously been impossible – but climate change and melting ice caps means that this is no longer the case.
However, there is a way that increased international connectivity provided by subsea cables can help to solve this issue. Subsea cable systems allow companies much greater flexibility in choosing where to locate their high intensity compute. Plus, as over 80% of high performance computing (HPC) equipment does not need to be located near the end-user in terms of latency and accessibility, businesses can now think about processing and storing data almost anywhere in the world. Given the heavy carbon footprint of AI, businesses need to think about this as a matter of urgency.
As the only country in Europe that generates 100% of its power from renewable hydroelectric and geothermal energy sources, Iceland is already in a unique position. And as a third connection between Iceland and Europe, IRIS increases the redundancy and resilience of the Nordic nation’s connectivity, enhancing its digital advantage and cementing its position as a viable home for businesses’ high intensity compute. In this way, IRIS accentuates Iceland’s appeal for businesses looking to locate their HPC in a country with such environmental benefits. The growing concerns surrounding the sustainability of AI show that we need to tackle these issues head-on, and cable systems such as IRIS are facilitating practical actions that do so.
While the pace of the digital economy continues to accelerate, these subsea cables connecting Iceland to the rest of the world provide means as well as reason to move from rhetoric to reality in achieving sustainable AI. HPC can and should be located where data can be processed in the most efficient, cost-effective and sustainable way possible, and the new IRIS system endorses the location of high intensity compute in Iceland as a real and viable solution to the sustainability of AI.
Dominic Ward is the CEO of Verne Global, a UK-based data centre operator with a 40 acre campus near Keflavik, Iceland, focused on supporting HPC IT loads. | <urn:uuid:eaf6fe76-5070-4532-9dc2-c5b37908a46d> | CC-MAIN-2024-38 | https://datacentremagazine.com/technology-and-ai/new-iceland-ireland-subsea-cable-could-drive-sustainable-ai | 2024-09-18T18:54:22Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651931.60/warc/CC-MAIN-20240918165253-20240918195253-00612.warc.gz | en | 0.950496 | 971 | 2.875 | 3 |
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Overcoming Limitations of SAST and Other Traditional Software Security Testing Tools
Embedded software is increasingly becoming a crucial part of modern-day life. From cars to medical devices and home appliances, embedded software is everywhere. However, with the increasing complexity of these systems, securing them has become an ever-growing challenge. In addition, there is a shortage of skilled security professionals to address this challenge. Various security testing tools, including Static Application Security Testing (SAST), have emerged to mitigate this issue.
What is SAST?
SAST tools are automated testing tools that use a set of rules and algorithms to analyze code for potential security vulnerabilities without running the application itself. While source code analysis is the most common use case for SAST tools, they can also analyze lower-level bytecode and binary code.
- For example, SAST tools can identify buffer overflow vulnerabilities by looking for instances where the length of user input is not correctly validated.
- Similarly, SAST tools can detect SQL injection vulnerabilities by identifying code segments where the application concatenates user input into SQL queries without proper escaping or sanitization, allowing attackers to execute arbitrary SQL commands on the database server.
- By looking for patterns that match known attack vectors, SAST tools can identify other common security flaws, such as cross-site scripting, directory traversal, etc.
SAST tools can identify security flaws in the code early in the software development lifecycle and help developers find and fix potential security issues well before product deployment.
What are some benefits and limitations of SAST?
One of the most significant benefits of SAST tools is that they are automated. They can analyze a large amount of code quickly and easily, saving developers time and effort.
SAST tools can also help identify vulnerabilities that manual code reviews may miss.
Another advantage of SAST tools is that vendors can integrate them into their processes. Software developers can receive feedback on security issues as they write the code rather than waiting until the end of the development cycle. Close integration can help prevent security issues from being introduced into large, thus difficult-to-maintain codebases in the first place.
However, SAST tools also have some limitations. For example, they may generate many false positives, which can be time-consuming to investigate. In addition, SAST tools may not be effective in identifying all types of vulnerabilities, particularly those related to runtime behavior or misconfiguration.
The next step - How to expand your testing scope?
Therefore, engineering teams should utilize SAST and other security testing tools, such as Dynamic Application Security Testing (DAST), Interactive Application Security Testing (IAST), and Software Composition Analysis (SCA). However, despite these tools’ many advantages, it is essential to acknowledge their notable limitations.
These limitations could be overcome by following the defense-in-depth principle in the software development process. By combining various security testing tools, developers can identify vulnerabilities that a specific tool might miss by itself.
- Common SAST tools examine an application’s source code. Hence, they can only identify vulnerabilities in the source code.
- In contrast, DAST tools can pinpoint vulnerabilities during runtime but cannot analyze the source code.
- Similarly, IAST tools can detect vulnerabilities by instrumenting the code, allowing them to identify vulnerabilities that SAST and DAST tools might miss.
- Additionally, SCA tools can flag known vulnerabilities in third-party components used in an application but cannot recognize security flaws in custom code written by in-house developers.
Furthermore, every tool may produce false positives (issues that are not true) and false negatives (missed issues), which can be time-consuming for developers to sift through. Another advantage of using multiple security testing tools is that by cross-referencing the results generated by different tools, developers can isolate and eliminate false issues, saving valuable time.
Where does BugProve fit in the picture?
BugProve's automated firmware analysis platform uses both static and semi-dynamic analysis techniques, which can provide additional value to existing security testing tools. While the most common traditional SAST tools can identify potential security vulnerabilities in the source code, BugProve's platform can analyze fully built device firmware to detect potential zero-day vulnerabilities and monitor known vulnerabilities even in closed-source third-party software components to ensure compliance with industry standards. By combining our comprehensive security testing capabilities with existing SAST tools, development teams can further enhance their security testing processes and ensure their products are safe and secure for end-users. | <urn:uuid:820e70a3-315e-4f05-a48a-6732d22c75c3> | CC-MAIN-2024-38 | https://bugprove.com/knowledge-hub/overcoming-limitations-of-sast-and-other-traditional-software-security-testing-tools/ | 2024-09-20T00:13:09Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700652073.91/warc/CC-MAIN-20240919230146-20240920020146-00512.warc.gz | en | 0.925977 | 933 | 2.546875 | 3 |
The Data Protection Bill, Brexit and Data Transfers
Purposes of the Bill
The Bill performs two core functions.
- The Bill will implement the GDPR into the law of England and Wales and sets out the United Kingdom's derogations under the GDPR.
- The Bill will ensure that at the point the United Kingdom exits the European Union the United Kingdom will have a data protection regime which is largely aligned with that of the remaining European Union member states.
Following the referendum of 23 June 2016 and the United Kingdom's subsequent notification under Article 50 of the Lisbon Treaty, the United Kingdom's membership of the European Union is due to end on 29 March 2019, subject to any transitional or implementation period that may be agreed with the European Union (and ratified by its continuing member states).
Third country status and international transfers
At the point that the United Kingdom exits the European Union it will for the purposes of the GDPR become a third country. Therefore, transfers of personal data from a European member state to the United Kingdom will engage the provisions of the GDPR relating to the transfer of personal data to third countries (Chapter V). Organisations in European member states will still be able to transfer personal data to the United Kingdom, however, such transfers will need to meet the requirements of the GDPR in relation to transfers of personal data outside of the European Economic Area.
Transfers on the basis of a decision of adequacy
The optimum position for the United Kingdom post-Brexit would be to obtain and maintain a decision of the European Commission that the laws of the United Kingdom provide an adequate level of protection for the rights of data subjects whose data are transferred to the United Kingdom.
A decision of adequacy would remove the need for an organisation which transfers personal data to the United Kingdom to rely on compliance mechanisms to ensure such transfers meet the requirements of the GDPR (for example, Standard Contractual Clauses and Binding Corporate Rules). Implementing such compliance mechanisms requires organisations to invest additional time and expenditure which will inevitably reduce the ease with which personal data can currently be transferred from mainland Europe to the United Kingdom.
Maintaining a decision of adequacy
The Bill will help to align the data protection regimes of the United Kingdom and the European Union on day one following Brexit, however, it does not guarantee that the European Union will recognise the adequacy of the United Kingdom's data protection regime. Two decisions of the Court of Justice of the European Union << Tele2 Sverige AB v Post- och telestyrelsen (C‑203/15) and Secretary of State for the Home Department v Tom Watson and others (C 698/15) >> illustrate Europe's concerns regarding elements of the United Kingdom's privacy regime. The CJEU held that the Investigatory Powers Act did not comply with the requirements of European Union Law.
Furthermore, decisions of the United Kingdom's courts could cause national data protection law to diverge from the GDPR which could prevent a finding of adequacy or call into question a finding of adequacy granted by the European Commission.
Mind the gap
The United Kingdom's exit from the European Union is unprecedented and shrouded in uncertainty. We cannot be certain as to the length of time it will take for the European Commission to grant the United Kingdom a decision of adequacy, if at all.
In theory, post-Brexit, it is conceivable that the United Kingdom could be without a decision of adequacy for a significant period of time and that organisations would need to implement appropriate GDPR compliant safeguards to facilitate the cross-channel flow of personal data.
Challenges to Standard Contractual Clauses
Standard Contractual Clauses would appear to be the natural fall-back position for organisations in the absence of an adequacy decision. However, the future of the Standard Contractual Clauses remains uncertain given that the validity of the Standard Contractual Clauses has been called into question by Data Protection Commission v Facebook & Schrems.
Preparing for uncertain times ahead
It is impossible for organisations to foresee every scenario that may arise in connection with the cross-channel transfer of personal data but it does not mean that organisations cannot take simple practical steps.
- Identify existing agreements which will be in force beyond March 2019 and concern the transfer of personal data between the European Union and the United Kingdom. Consider remediating such agreements to includes provisions and mechanisms to facilitate the transfer of personal data in the event that the United Kingdom is not subject to a decision of adequacy.
- When entering into agreements which will be in force beyond March 2019 organisations should ensure that such agreements contain provisions which will enable the transfer of personal data in compliance with the requirements of the GDPR irrespective of whether the United Kingdom obtains a decision of adequacy. | <urn:uuid:6be076aa-358b-4ba9-bf56-bfcc83fde9cf> | CC-MAIN-2024-38 | https://inplp.com/at/latest-news/article/the-data-protection-bill-brexit-and-data-transfers/ | 2024-09-12T19:42:57Z | s3://commoncrawl/crawl-data/CC-MAIN-2024-38/segments/1725700651491.39/warc/CC-MAIN-20240912174615-20240912204615-00312.warc.gz | en | 0.92555 | 963 | 2.515625 | 3 |
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