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Elliptic-Curve Cryptography (ECC) was discovered in 1985 by Victor Miller (IBM) and Neil Koblitz (University of Washington) as an alternative mechanism for implementing public-key cryptography. ECC is an approach to public-key cryptography based on the algebraic structure of elliptic curves over finite fields. ECC requires smaller keys compared to non-ECC cryptography (based on plain Galois fields) to provide equivalent security.
Elliptic curves are applicable for key agreement, digital signatures, pseudo-random generators and other tasks. Indirectly, they can be used for encryption by combining the key agreement with a symmetric encryption scheme. They are also used in several integer factorization algorithms based on elliptic curves that have applications in cryptography, such as Lenstra elliptic-curve factorization.« Back to Glossary Index | <urn:uuid:77420b02-0a72-468b-a719-7fee11d140bf> | CC-MAIN-2022-40 | https://www.cardlogix.com/glossary/ecc-elliptic-curve-cryptography/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337421.33/warc/CC-MAIN-20221003133425-20221003163425-00755.warc.gz | en | 0.930661 | 176 | 3.203125 | 3 |
Server is a computer or hardware device which stores data and provides services to the client’s computer. There are different types of server computer such as web server, application server, database server, print server, and mail server. In this post, we’ll clearly express the definition of server computer.
Definition of Server Computer
What is the definition of server computer? In computing, the definition of server computer is a server which is typically connected to one or more clients through the internet or local area network (LAN) in order to access the resources. The server computer stores different types of resources such as text, image, video, and file. Servers can share those resources to the client computers and the client can access the resources through the network.
In a data centre, a server is a high configuration computer or storage that run services to serve the workstations. In order to access the resources, first of all clients send a request to the server and server response the request and finally sends the resources to clients.
A server can host different types of application software, internet games and websites. The application can be ERP software, accounting software, budget management software, library management software, and financial software etc.
If you want to share something or give access to the resources to workstations or automate your office, then you need a server. Typically, the workstations can be connected to a server through a local area network or the internet.
Types of Server Computer
There are different types of server which are used for different purposes such as education, business, and office. Here is the list of most common forms of servers are as follows:
- Web Server
- Application Server
- Database Server
- Mail Server
- DNS Server
- Print Server
- Virtual Server
- Proxy Server
Now, we’ll define the definition of server computer (each types).
1. Web Server
First off all, clarify the definition of server computer for web, which is a type of server computer that is used to host web contents.
Clients send HTTP (Hypertext Transfer Protocol) request for HTML web pages through the internet and web servers respond to the client requests and show the webpages on client’s browser.
The main purpose of a web server is to receive the client request and display the HTML web pages on the client browser through the internet.
When you’ll host a static website then, you need a static web server and when you’ll host a dynamic application then you need a dynamic web server. Dynamic web server means, you need an additional web server called application server.
Nowadays, the most popular web servers are Apache web server, IIS server, Nginx and LiteSpeed.
Read more about Web Server.
2. Application Server
The definition of application server computer is a server that has typically designed to host web-based dynamic applications. The application server acts as an intermediary between the web server and the database server.
If you send a dynamic request to a web server then the web server sends the request to the application server. Then the application server receives the request and sends it to the database server and will inform the web server again.
Generally, an application server handles the dynamic requests from a web server and delivers the business logic of any application.
3. Database Server
A database server is a type of server computer which is used to store and manage the database on a server. The database server can host one or more databases and only authorized users can access the database server.
Typically, a database server has two sides one is the software side and another one is the hardware side. On the software side, the database server is the back-end part of the database application. And on the hardware side, the database server is the highly configured computer system, which is used to store and manage the database.
4. Mail Server
Let’s the definition of server computer for mail server. A mail server is a server that is used to store, send and receive email over the internet. The mail server also referred to an e-mail server.
A mail server can send and receive (outgoing and incoming) emails from the same or other mail servers using standard email protocols such as SMTP, POP3 and IMAP.
The SMTP (Simple Mail Transfer Protocol) protocol is used to send outgoing emails and the IMAP and POP3 protocols are used to receive and store incoming emails from client computers.
5. DNS Server
A DNS (Domain Name System) server is a type of application server that’s used to convert hostnames into Internet Protocol or IP addresses. For example, the hostname abc.com is converted into the IP address (184.108.40.206). It’s easier to remember a domain name or hostname rather than an IP address.
The DNS server contains one or more domain names and each domain has a unique public IP address. If a web server hosts multiple web applications, then the DNS server can add multiple domain names using that web server’s IP address. In that case, the web server must be configured using port numbers.
6. Print Server
In computer networking, a print server is a networked computer or host computer in a computer network that connects workstations with printers over a network. The print server is also referred to as a network printer.
A print server can connects multiples computer and allows to complete their print-related jobs without moving the files and users. Typically, a print server may be used in small and large office networks or home networks.
7. Virtual Server
Now, we’ll define the definition of server computer for Virtual, which shares resources such as hardware and software with other operating systems (OS) to host multiple applications. The term virtual server is located at someone else’s location which is shared and accessible by authorized application owners.
Simply put, one physical server resources (such as RAM, Hard Disk, Processor) can be allocated into several virtual machines which can run different operating systems. The use of virtual servers is cost effective, simplified, time and resource saving, easy configuration, and ensures availability in case of disaster recovery.
Nowadays, virtual servers are the most popular hosting platforms for software and website hosting. Most of the organizations are using virtual servers to reduce the hardware cost and optimize the hardware resources.
8. Proxy Server
A proxy server is a server computer that performs as an intermediary between client and server. In order to access the resources (such as web pages, files) the client directs requests to the proxy instead of requesting to a server. A proxy server processes the request, filters the content, scans for viruses, malware and finally displays the contents on the client web browser.
The proxy server provides the user privacy, ensures network security by hiding the real IP address, filters the malicious websites and can access the geographically blocked or restricted websites.
Features of Server Computer
In this post, we’ve well-defined the definition of server computer for web, application, mail, printer, database, etc. Now, we’ll mention the main features of server computer.
The main features or function of a server is storage, access and managing the data files through the computer network. The other features of a server computer are mentioned as follows:
- It is a high configuration computer.
- One server computer can connect to multiple workstations.
- Server computer has data transfer and backup capability.
- Operating system and other software can be updated on server computers.
- Server can process the client requests.
- It ensure security of data and resources from unauthorized access.
- It ensures availability of data and resources.
Types of Server Hardware
The main components or parts of a server are motherboard, processors, memory, hard drives, network connections, graphics cards and power supply. There are mainly three types of server hardware such as tower server, rack server, and blade server. Some other categories of server are hyper-converged infrastructure (HCI) and mainframes. These types of server’s hardware are used based on business and data storage requirements.
Finally, a server is a computer system that stores resources and serves them to another system or to the client computers. A server is essential to store data and host applications and provide services to the user. In this article, we have discussed about definition of server computer. Hope the article may help you to gather some information about server computer. | <urn:uuid:68806883-688a-44c0-bdfd-cac9b3ea9c94> | CC-MAIN-2022-40 | https://cyberthreatportal.com/definition-of-server-computer/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337529.69/warc/CC-MAIN-20221004215917-20221005005917-00755.warc.gz | en | 0.884177 | 1,749 | 3.71875 | 4 |
What is AI? Artificial intelligence (AI) is the ability of a machine or computer to imitate the capabilities of the human mind. AI taps into multiple technologies to equip machines in planning, acting, comprehending, learning, and sensing with human-like intelligence. AI systems may perceive environments, recognize objects, make decisions, solve problems, learn from experience, and imitate examples. These abilities are combined to accomplish actions that would otherwise require humans to do, such as driving a car or greeting a guest.
Why AI is Growing in Popularity
Artificial intelligence may have entered everyday conversation over the last decade or so but it has been around much longer (see the History of AI section below). The relatively recent rise in its prominence is not by accident.
AI technology, and especially machine learning, relies on the availability of vast volumes of information. The proliferation of the Internet, the expansion of cloud computing, the rise of smartphones, and the growth of the Internet of Things has created enormous quantities of data that grows every day. This treasure trove of information combined with the huge gains made in computing power have made the rapid and accurate processing of enormous data possible.
Today, AI is completing our chat conversations, suggesting email responses, providing driving directions, recommending the next movie we should stream, vacuuming our floors, and performing complex medical image analyses.
History of AI
The history of artificial intelligence goes as far back as ancient Greece. However, it’s the rise of electronic computing that made AI a real possibility. Note that what is considered AI has changed as the technology evolves. For example, a few decades ago, machines that could perform optimal character recognition (OCR) or simple arithmetic were categorized as AI. Today, OCR and basic calculations are not considered AI but rather an elementary function of a computer system.
- 1950s – Alan Turing, a man famous for breaking the WWII ENIGMA code used by the Nazis, publishes the Computing Machinery and Intelligence paper in the Mind. He attempts to answer the question of whether machines can think. He outlines the Turing Test that determines whether a computer shows the same intelligence as a human. The test holds that an AI system should have the ability to hold a conversation with a human without the human knowing they are speaking to an AI system. The first ever AI conference is held at Dartmouth College. It’s here that the term artificial intelligence was first used.
- 1960s – The US Department of Defense through DARPA takes great interest in AI and embarks on developing computer programs that mimic human reasoning. Frank Rosenblatt builds the Mark 1 Perceptron computer based on a neural network that learns through experience.
- 1970s – DARPA completes various street mapping projects.
- 1980s – A more complex wave of AI emerges. Neural networks with backpropagation algorithms find widespread application in AI systems.
- 1990s – Exponentially growing volumes of data are produced. Powerful computers process large quantities of data quickly. The Deep Blue supercomputer defeats world chess champion Garry Kasparov twice. The Genome Sequencing project and other similarly complex undertakings generate vast information. Computing advances make it possible for this data to be stored, accessed, and analyzed.
- 2000s – The Internet Revolution drives AI to unprecedented heights. Big data joins corporate lexicon. DARPA rolls out intelligent personal assistants long before Alexa, Siri, Cortana, and Google Assistant become household names. This paves the way for the reasoning and automation that’s a part of present day personal computers and smartphones. That includes smart search systems and decision support systems that augment and complement human abilities.
- 2010s – China’s search giant Baidu unveils the Minwa supercomputer that relies on a convolutional neural network to identify, analyze, and categorize images with higher accuracy than the average human. The AlphaGo deep neural network program from DeepMind beats Go world champion Lee Sodol in a five-game match. Go is an ancient Chinese game that’s considerably more complex than chess.
How Does AI Work?
Artificial intelligence asserts that there are principles governing the actions of intelligent systems. It is based on reverse-engineering human capabilities and traits onto a machine. The system uses computational power to exceed what the average human is capable of doing. The machine must learn to respond to certain actions. It relies on historical data and algorithms to create a propensity model. Machines learn from experience to perform cognitive tasks that are ordinarily the preserve of the human brain. The system automatically learns from features or patterns in the data.
AI is founded on two pillars – engineering and cognitive science. The engineering involves building the tools that rely on human-comparable intelligence. Large volumes of data are combined with series of instructions (algorithms) and rapid iterative processing. Cognitive science involves emulating how the human brain works, and brings to AI multiple fields including machine learning, deep learning, neural networks, cognitive computing, computer vision, natural language processing, and knowledge reasoning.
AI Systems Are Not Monolithic
Artificial intelligence isn’t one type of system. It’s a diverse domain. There’s the simple, low-level AI systems focused on performing a specific task such as weather apps, business data analysis apps, taxi hailing apps, and digital assistants. This is the type of AI, called "Narrow AI", that the average person is most likely to interact with. Their main purpose is driving efficiency.
On the other end of the spectrum are advanced systems that emulate human intelligence at a more general level and can tackle complex tasks. These include thinking creatively, abstractly, and strategically. Strictly speaking, this kind of truly sentient machine, called "Artificial General Intelligence" or AGI, only exists on the silver screen for now, though the race toward its realization is accelerating.
Where is Artificial Intelligence Used?
Humans have pursued artificial intelligence in recognition of how invaluable it can be for business innovation and digital transformation. AI can cut costs and introduce levels of speed, scalability, and consistency that is otherwise out of reach. You probably interact with some form of AI multiple times each day. The applications of AI are too numerous to exhaustively cover here. Here’s a high level look at some of the most significant ones.
As cyberattacks grow in scale, sophistication, and frequency, human-dependent cyber defenses are no longer adequate. Traditionally, anti-malware applications were built with specific threats in mind. Virus signatures would be updated as new malware was identified.
But keeping up with the sheer number and diversity of threats eventually becomes a near impossible task. This approach was reactive and depended on the identification of a specific malware for it to be added to the next update.
AI-based anti-spam, firewall, intrusion detection/prevention, and other cybersecurity systems go beyond the archaic rule-based strategy. Real-time threat identification, analysis, mitigation, and prevention is the name of the game. They deploy AI systems that detect malware traits and take remedial action even without the formal identification of the threat.
AI cybersecurity systems rely on the continuous feed of data to recognize patterns and backtrack attacks. By feeding algorithms large volumes of information, these systems learn how to detect anomalies, monitor behavior, respond to threats, adapt to attack, and issue alerts.
2. Speech Recognition and Natural Language Processing
Also referred to as speech-to-text (STT), speech recognition is technology that recognizes speech and converts it into digital text. It’s at the heart of computer dictation apps, as well as voice-enabled GPS and voice-driven call answering menus.
Natural language processing (NLP) relies on a software application to decipher, interpret, and generate human-readable text. NLP is the technology behind Alexa, Siri, chatbots, and other forms of text-based assistants. Some NLP systems use sentiment analysis to make out the attitude, mood, and subjective qualities in a language.
3. Image Recognition
Also known as machine vision or computer vision, image recognition is artificial intelligence that allows one to classify and identify people, objects, text, actions, and writing occurring within moving or still images. Usually powered by deep neural networks, image recognition has found application in self-driving cars, medical image/video analysis, fingerprint identification systems, check deposit apps, and more.
4. Real-Time Recommendations
E-commerce and entertainment websites/apps leverage neural networks to recommend products and media that will appeal to the customer based on their past activity, the activity of similar customers, the season, the weather, the time of day, and more. These real-time recommendations are customized to each user. For e-commerce sites, recommendations not only grow sales but also help optimize inventory, logistics, and store layout.
5. Automated Stock Trading
The stock market can be extremely volatile in times of crisis. Billions of dollars in market value may be wiped out in seconds. An investor who was in a highly profitable position one minute could find themselves deep in the red shortly thereafter. Yet, it’s near impossible for a human to react quick enough to market-influencing events. High-frequency trading (HFT) systems are AI-driven platforms that make thousands or millions of automated trades per day to maintain stock portfolio optimization for large institutions.
6. Ride-Sharing Services and Self-Driving Cars
Lyft, Uber, and other ride-share apps use AI to connect requesting riders to available drivers. AI technology minimizes detours and wait times, provides realistic ETAs, and deploys surge-pricing during spikes in demand.
Self-driving cars are not yet standard in most of the world but there’s already been a concerted push to embed AI-based safety functions to detect dangerous scenarios and prevent accidents.
7. Autopilot Technology
Unlike land-based vehicles, the margin for error in aircraft is extremely narrow. Given the altitude, a small miscalculation may lead to hundreds of fatalities. Aircraft manufacturers had to push safety systems and become one of the earliest adopters of artificial intelligence.
To minimize the likelihood and impact of human error, autopilot systems have been flying military and commercial aircraft for decades. They use a combination of GPS technology, sensors, robotics, image recognition, and collision avoidance to navigate planes safely through the sky while keeping pilots and ground crew updated as needed.
8. Software Test Automation
Artificial Intelligence accelerates and simplifies test creation, execution, and maintenance through AI-powered intelligent test automation. AI-based machine learning and advanced optical character recognition (OCR) provide for advanced object recognition, and when combined with AI-based mockup identification, AI-based recording, AI-based text matching, and image-based automation, teams can reduce test creation time and test maintenance efforts, and boost test coverage and resilience of testing assets.
9. Functional Testing
Artificial intelligence allows you to test earlier and faster with functional testing solutions. Combine extensive technology support with AI-driven capabilities. Deliver the speed and resiliency that supports rapid application changes within a continuous delivery pipeline.
10. Enterprise Service Management
Both IT and business face the challenges of too many manual, error-prone workflows, an ever-increasing volume of requests, employees dissatisfied with the level and quality of service, and more. Artificial Intelligence and machine learning technology can take service management to the next level:
- Smart search capabilities enable employees to find answers easily and quickly
- Virtual agents or bots can perform tasks using natural language processing (NLP)
- Intelligent analytics enable workflow optimization and automation
- Metrics from unstructured data, for example user surveys, can be gathered and analyzed more efficiently.
Read How AI Is Enabling Enterprise Service Management from the resource list below for more thoughts and information on the role of artificial intelligence (AI) in the adoption and expansion of enterprise service management (ESM).
What is true of IT support, is also true for ESM; AI makes operations and outcomes better. To find out more read Ten Tips for Empowering Your IT Support with AI.
11. Robotic Process Automation (RPA)
Robotic process automation (RPA) uses software robots that mimic screen-based human actions to perform repetitive tasks and extend automation to interfaces with difficult or no application programming interfaces (APIs). That’s why RPA is perfect for automating processes typically completed by humans or that require human intervention. Resilient robots adapt to screen changes and keep processes flowing when change happens. When powered by AI-based machine learning, RPA robots identify screen objects – even ones they haven’t seen before – and emulate human intuition to determine their functions. They use OCR to read text (for example, text boxes and links) and computer vision to read visual elements (for example, shopping cart icons and login buttons). When a screen object changes, robots adapt. Machine learning drives them to continuously improve how they see and interact with screen objects – just like a human would.
Get Started with Artificial Intelligence. Get Ahead
There are plenty of ways you could leverage artificial intelligence for your business to stay competitive, drive growth, and unlock value. Nevertheless, your organization doesn’t possess infinite resources. You must prioritize. Begin by defining what your organization’s values and strategic objectives are. From that point, assess the possible applications of AI against these values and objectives. Choose the AI technology that is bound to deliver the biggest impact for the business.
The world is only going to grow more AI-dependent. It’s no longer about whether to adopt AI but when. Organizations that tap into AI ahead of their peers could gain a significant competitive advantage. Developing and pursuing a well-defined AI strategy is where it all begins. It may take a bit of experimenting before you know what will work for you. | <urn:uuid:3a300ccb-6823-4fb2-a5a8-4a50f4f81e3e> | CC-MAIN-2022-40 | https://www.microfocus.com/it-it/what-is/artificial-intelligence | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338213.55/warc/CC-MAIN-20221007143842-20221007173842-00755.warc.gz | en | 0.922916 | 2,857 | 3.703125 | 4 |
Network traffic analysis is the method of collecting, storing, and analyzing traffic across your network. Traffic data is collected in or near real time so you can have up-to-the-second information about what’s happening. This allows you to take action immediately if a problem arises. You can also store this data for historical analysis.
Why Network Traffic Analysis Is Valuable?
Analyzing network traffic is a valuable part of network monitoring. You can’t manage a network without knowing what’s going across it and what it’s doing.
Uptime and Availability
A network is useless if it’s not available to its users. You need network traffic analysis so that you know your network’s uptime and availability. If network interfaces are down and user traffic can’t pass, uptime is zero. If HTTP requests to certain application services get dropped because their subnet is unreachable, availability is zero. Monitoring and analyzing network traffic can help you quickly identify these types of problems so that you can start troubleshooting and reduce impacts to the user experience.
You also need to know what’s out there. Visibility into the various network components is key to resolving problems. You need to know which devices belong to which network sites and locations before you can properly troubleshoot. Network traffic analysis helps you discover these devices and their locations. It also helps you build topology diagrams that give you the network visibility you need to prevent silos and avoid blind spots.
You need to know how well your network is performing. If traffic is moving slowly, nobody will care that it has great uptime. From a user’s point of view, it might as well be down. And network downtime is an SKA performance killer. Network traffic analysis can help you identify network connections that need upgrading with capacity planning. You can use it to find performance bottlenecks. It can also help you identify network resources that you can decommission, which helps cut IT costs. And making IT less of a cost center is always welcome.
It seems that every day there’s a story about another ransomware attack. IT managers and engineers seem at a complete disadvantage, but network traffic analysis gives you a fighting chance. With real-time network traffic collection, you’ll be able to detect anomalies. Yes, you already have firewalls in place, but they’re not foolproof. Hackers can find ways to mask their traffic to get around firewall rules. If you’re monitoring your firewalls and all the network traffic inside and outside, you have a much better shot at identifying a security threat. Maybe someone fat-fingered an input and enabled an insecure port. Collecting all that network traffic will help you catch that sort of thing before unscrupulous users take advantage of it.
Implementing Network Traffic Analysis
To take advantage of network traffic analysis, you obviously need to implement it. Here are some ways you can do that.
Network traffic data was originally collected and analyzed using the Simple Network Management Protocol (SNMP). This was useful when networks were much less complex and more centralized. While SNMP is still very much in use today, it’s not a standalone solution for proper network traffic analysis. It doesn’t collect enough detail for today’s complex network implementations, such as TCP/UDP ports and higher-level protocol data. But because of its ubiquitous vendor device support, it’s relatively easy to implement. This makes SNMP an easy choice to start with.
Since SNMP doesn’t collect higher-level protocol details, packet data is often used to help supplement it. You can collect packet data with hardware appliances like network probes and packet sniffers. The level of detail from each packet tells you not only the IP conversations but also the TCP/UDP ports in use. Collecting this much detail has its own drawbacks, however, because it makes analysis overwhelming. You can use monitoring tools to help, but they’re usually on the expensive side due to the storage requirements. So there goes your opportunity to make IT less of a cost center.
You can also collect network traffic data by using a flow collector. The network device with a flow protocol enabled can export network traffic data for analysis by the collector. This data is much more than what SNMP can provide but not as much as what packet data provides. So flow collection can be a good middle ground. Flow-based protocols include those such as Cisco Netflow, its IETF standard equivalent, IP Flow Information Export (IPFIX), and others like Jflow and Cflow. These provide flow records that include IP addresses, subnets, ports, and traffic bytes. And you won’t collect so much packet data detail that it bloats your storage space.
Whatever method you choose, the key is collecting and monitoring in or near real time with historical data. You need to know what’s happening now if the impact is due to a security breach, for example. But you also need to be able to go back in time to identify how past performance can affect future performance. Anything less is useless, and it isn’t network traffic analysis.
Network Traffic Analysis Best Practices
Collecting the data you need to properly analyze your network traffic can be daunting because you need to store so much of it, but there are some best practices you can follow to make it a little bit easier.
- Know what’s yours. Make sure you know what devices you expect to see on your network. If you’re a Cisco and Microsoft shop, expect to see Cisco routers, access points, and firewalls and Microsoft desktops and servers. Make sure you have some sort of naming convention in place for them. Anything showing up in a different format should be a red flag. When things change, if you know what’s yours, you’ll know if you need to remove something.
- Know the norm. Make sure you understand how your network normally operates and performs. What’s a typical latency between two office locations? What does network capacity usually look like? The tools can help, but they need time to collect enough data for you to know what’s typical and what isn’t so you can quickly identify any anomalies.
- Always be evaluating. Complex networks are constantly changing. In the early days, SNMP was enough for on-premises infrastructure. But SNMP, packet data, or flow alone aren’t enough for today’s hybrid cloud infrastructure. You should always evaluate what will work best. That includes looking at new network traffic analysis methods and tools. If current methods and tools aren’t getting you the data you need to provide a good user experience, you need to reevaluate your solutions.
Stay in the Know
As you’ve seen, network traffic analysis can help you know what’s happening on your network. And knowing is the key to properly managing it.
So stay in the know. And a monitoring solution from Netreo can help you get there by knowing what you need on your network. The platform is an option to consider if you need a new monitoring tool. Its ability to collect network traffic from flow-based and other protocols like SNMP will make your job easier. You can use it to configure the collection, storage, and analysis of your network traffic without deploying probes everywhere. It can also help you and your team make the right decisions. You can request a demo and see for yourself.
This post was written by Jean Tunis. Jean is the principal consultant and founder of RootPerformance, a performance engineering consultancy that helps technology operators minimize cost and lost productivity. He has worked in this space since 1999 with various companies, helping clients solve and plan for application and network performance issues. | <urn:uuid:7484b11d-48b5-4c4c-b6c3-54a9f718ebb3> | CC-MAIN-2022-40 | https://www.netreo.com/blog/what-is-network-traffic-analysis/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338213.55/warc/CC-MAIN-20221007143842-20221007173842-00755.warc.gz | en | 0.937083 | 1,628 | 2.515625 | 3 |
What is DMARC?
Modified on: Tue, 19 Apr, 2016 at 10:54 PM
DMARC stands for “Domain-based Message Authentication, Reporting & Conformance.” DMARC is protocol that uses SPF andDKIM to determine the authenticity of an email message. DMARC requires both SPF and DKIM to fail in order for it to act on a message.
Your DMARC record is published alongside your domain’s other DNS records (SPF, A record, CNAME, DKIM, etc.). Unlike SPF and DKIM, a properly configured DMARC policy can tell a receiving server whether or not to accept an email from a particular sender. It is important to note that not all receiving servers will perform a DMARC check before accepting a message, but all the major ISPs do and its implementation is growing.
Benefits of DMARC
- Publishing a DMARC record protects your brand by preventing unauthenticated parties from sending mail from your domain. In some cases, simply publishing a DMARC record can result in a positive reputation bump.
- Consuming DMARC reports increases visibility into your email program by letting you know who is sending mail from your domain.
- DMARC helps the email community establish a consistent policy for dealing with messages that fail to authenticate. This helps the email ecosystem as a whole become more secure and more trustworthy.
What does a DMARC record look like?
You can see what a DMARC record looks like by typing < dig txt _dmarc.sendgrid.net > in yourterminal. You can also go to https://dmarcian.com/dmarc-inspector/ to view the DMARC record for any domain if they have one published.
Here is an example of DMARC record–this is SendGrid’s DMARC record:
Let’s break down a DMARC record
“v=DMARC1” This is the identifier that the receiving server looks for when it is scanning the DNS record for the domain it received the message from. If the domain does not have a txt record that begins with v=DMARC1, the receiving server will not run a DMARC check.
“p=none” This part tells the receiving server what to do with messages that fail DMARC. In this case, the policy is set to “none.” This means that the receiving server will take no action if a message fails DMARC. This can still be valuable for a sender, because DMARC sends reports that alert the domain administrator of any DMARC failures.
“p=none” is generally a recommended first step on the way to implementing a policy that will drop unauthorized mail. Most people are surprised to find out how many different people/groups/organizations are sending mail (legitimate or otherwise) on behalf of their domain. Other options for the p= field are “quarantine” and “reject.” “Quarantine” will set messages aside for further processing; in most cases this means it will be sent to the spam folder. “Reject” will stop the messages outright.
“rua=mailto:firstname.lastname@example.org” This part tells the receiving server where to send aggregate reports of DMARC failures. These aggregate reports are sent daily to the administrator of the domain that the DMARC record belongs to. They include high level information about DMARC failures but do not provide granular detail about each incident. This can be any email address you choose.
“ruf=mailto:email@example.com” This part tells the receiving server where to send forensic reports of DMARC failures. These forensic reports are sent in real time to the administrator of the domain that the DMARC record belongs to. These forensic reports contain details about each individual failure. This email address must be from the domain that the DMARC record is published for.
“rf=afrf” This part tells the receiving server what kind of reporting the policyholder wants. rfstands for reporting format. In this case rf=afrf means aggregate failure reporting format.
“pct=100” This part tells the receiving server how much of their mail should be subjected to the DMARC policy’s specifications. In this case, if the p= was set to reject, 100% of the mail that fails DMARC would be rejected.
There are a number of other mechanisms that can be included in a DMARC record. A few notable ones include:
“sp=” This part would tell the receiving server whether or not to apply the DMARC policy to sub domains.
“adkim=” This sets the DKIM alignment. It can either be set to “s” for strict or “r” for relaxed. Strict means the DKIM portion of DMARC authentication will only pass if the d= field in the DKIM signature EXACTLY matches the from domain. If it is set to relaxed, messages will pass the DKIM portion of the DMARC authentication if the DKIM d= field matches the root domain of the from address.
“ri=” This sets the interval for how often you want to receive aggregate reports about DMARC failures.
As DMARC implementation becomes more ubiquitous, so too will DMARC failures. A good example of this is frequently showing up with many of our high volume clients. Some applications and/or websites have features that allow a user to send an email to themselves or to a friend. Oftentimes, the website or application sends these emails from the user’s own email address (firstname.lastname@example.org). Because of Yahoo’s DMARC policy, these messages will be rejected by any receiving server that does a DMARC check. The same DMARC failure will occur if an unauthorized user attempts to send mail for any domain that publishes a DMARC record with a p=”reject.”
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Sorry we couldn't be helpful. Help us improve this article with your feedback. | <urn:uuid:6fc7278f-eb75-462a-b669-96b21c37d024> | CC-MAIN-2022-40 | https://support.duocircle.com/support/solutions/articles/5000703263-what-is-dmarc- | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335254.72/warc/CC-MAIN-20220928113848-20220928143848-00155.warc.gz | en | 0.896088 | 1,349 | 3.390625 | 3 |
What are the inherent security risks in the application design process?
Developers need to build in secure coding techniques, such as encryption, authentication, and passwords. Until recently, many of these techniques have not been taught in college classes for software developers. Therefore, many software engineers writing code are not educated about these techniques and are not aware of potential problems. For example, there are standard pieces of the C/C++ programming language that are insecure and should be used with great caution, or omitted from the process altogether.
What are some of the most common vulnerabilities in enterprise applications?
Common vulnerabilities can include authorization bypass, SQL injection vulnerabilities, buffer overflow, and information leaks and can affect both commercial and custom applications. Authorization bypass occurs when a normal user is able to access information from a Website or other application that was meant for an administrator or select group of individuals.
SQL injection is a technique for exploiting Web applications that use client-supplied data in SQL queries without removing potentially harmful characters first. There are quite a few systems connected to the Internet that are vulnerable to this type of attack. In this situation, data provided by a user, such as account number and username, is used to look up additional data on the SQL database. A knowledgeable attacker can provide SQL commands which get passed to the database and executed. The attacker can then inject commands and manipulate the database to do what it wants, such as providing user account information and details.
Buffer overflow is another example of a vulnerability that has plagued the commercial software industry and can also appear in custom applications. A buffer overflow occurs when a program or process tries to store more data on a buffer (temporary data storage area) than it was intended to hold. Since buffers are created to hold a limited amount of information, the extra data can spill over into adjacent buffers, corrupting and deleting the valid data held in them.
When do vulnerabilities find their way into the application design process?
Vulnerabilities typically find their way into applications during two phases of development—application design and application implementation. It is best to identify vulnerabilities during the design, rather than discovering issues during implementation and going back to re-design pieces of the application.
How can developers address security from the beginning of application development and design?
A holistic approach to building security into the development lifecycle will save tremendous amounts of time and money because problems are identified early in the process and continue to be addressed at each step. Security practices should be in place during requirements planning, design time, implementation, and testing time, in order to catch the majority of problems as early in the cycle as possible. | <urn:uuid:f21e9a4d-6e0a-4d75-a9cf-551c2f555c98> | CC-MAIN-2022-40 | https://it-observer.com/application-security-principles1.html | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335365.63/warc/CC-MAIN-20220929194230-20220929224230-00155.warc.gz | en | 0.951686 | 528 | 3.234375 | 3 |
the size or area of business, all organizations must have a proper cybersecurity
strategy in place to protect their infrastructure and data from growing cyber-attacks.
However, no matter how much time and money are invested in deploying and later maintaining the best, state-of-the-art solution, it is simply not enough. Contrary to popular belief, most security breaches are not the action of a malicious, external party but come from the inside, usually due to human errors from our very own employees. Even though these security breaches are not cyber-attacks per se, they can have a tremendous impact for the organization, potentially leading to the loss of Intellectual Property (IP), Personal Identifiable Information (PII), reputation, and revenue.
It is critical to raise awareness of the impact of day-to-day security mistakes and how to address them. The best way to turn employees from potential weak links to our first line of defense is using dedicated security awareness training. It is most important to get employees onboard, and this is only achieved if they understand why they are being asked to do (or not do) certain things. It is important to explain the possible impact that some day-to-day, apparently harmless actions can have, and how this could lead to data being used by malicious actors against the company. Following security guidelines and procedures is not “against” them but for them, to protect their computer, their data, and so the company. Plus, most security practices can be reused to protect their personal computer, mobile devices, and data at home.
understand the risks associated with their everyday actions, from simply sending a document to an external recipient, to identifying a suspicious SMS.
What is Security Awareness Training?
awareness training is used to prevent and mitigate security risks by providing specific training programs designed to help employees understand their role in protecting their own organization.
Employees learn how to avoid the most preventable security breaches, are taught proper cyber hygiene, and raise their awareness so they can spot any possible cyber-attacks, or at least be
suspicious whenever something seems odd.
Which Topics Should be Covered?
awareness training usually includes the following topics:
Teaches employees how to recognize and avoid potential phishing attacks. Phishing is the most common cyber-attack, used as a point of entry for hackers to get into an infrastructure, spread, and take control to perform ransomware attacks. They usually come in the form of email (spam), SMS with a link to click that will later install malware, phone calls where the employee is deceived into providing sensitive, personal information, or even online when logging into websites in order to steal his credentials (see “Browser in the Browser (BITB) Attacks”).
Instructs employees on how to recognize threats coming from the inside. These are the hardest threats to detect, as the people involved would usually be trusted and thus not raise suspicion at first. The reasons behind an insider threat can range from an angry employee willing to hurt and/or cash in reselling company IP to its main competitors, to a compromised or blackmailed employee, or simply a negligent employee who does not respect the minimum rules and processes in term of data handling.
While more and more organizations are moving to a password-less strategy, passwords are still very much in use. Usually, there are specific policies dictated by the organization and enforced by IT to ensure employees change passwords often and on a regular basis (e.g., every 30 to 60 days), do not reuse the same passwords, and create passwords with a certain level of complexity. However, it is important to educate the employees on why this is done, as some could view the effort as pointless or a waste of time; password strategies should be reframed as another measure to protect employee data and by extension their entire organization, making it an essential part of their job and responsibilities.
Training should cover how corporate, sensitive and/or regulated data, like employee health records, should be handled and stored, in line with the current laws and regulations, like HIPAA in the United States or GDPR in Europe.
Bad practices like sharing corporate, customer, or partner information should be discouraged, and the possibly devastating consequences explained. For instance, a data breach, voluntary or involuntary, can affect a corporation not only in terms of loss of reputation and revenue, but also from a legal perspective.
Stress the importance of not trying to circumvent security processes put in place, for example by using unregulated Instant Messaging communication solutions (e.g., WhatsApp, Telegram) to share corporate, customer, or partner data. Not only could this have a direct impact on reputation and revenue if the data falls into the hands of a malicious party, but also legal consequences that would eventually result in a fine from authorities.
Not all critical, sensitive information is electronic, stored on computers and back-end servers. A lot of sensitive data is still printed on paper, and it is important to help employees understand how leaving a simple piece of paper with some information on it out in the open could be used by a malicious insider to perform reverse engineering, impersonate someone’s account, and/or access internal resources, aiming to steal them. Employees must be trained on how to properly store these documents, in a locked cabinet, and how to dispose of them when no longer needed, for example using paper shredders instead of just throwing them into a recycling bin.
Also, employees must learn the practice of locking a computer session once they leave their seat, even for a moment to grab a cup of coffee or for the night when leaving the office. Any simple act that might help protect the integrity of the infrastructure should not be overseen, and it is crucial for the employees to understand the potential impacts of their actions and inactions.
How Does it Look?
Security Awareness Training would usually consist of a mix of online web-based training, including videos and quizzes to first explain what the existing threats are, how they work, and how to detect them. It should not be a long, one-off session, as too much content at once would be counterproductive, but should instead be persistent and delivered regularly over time. Many also use gamification to make the training more attractive and interactive, promoting some healthy “competition” between employees as to whom has the best knowledge by ranking security scores, obtained after taking and passing some quizzes and exams.
Then, schedule fully automated, simulated phishing attacks based on real-life attacks to challenge employees and see if they can either spot them or if they will take the bait. This would typically include phishing SMS, email, and phone attacks, based on real-life attacks but unweaponized, to test whether your employees would be able to recognize a threat or, when in doubt, escalate internally to the IT department, or even better the security department to identify a possible threat.
Nevertheless, all the training in the world is only good if your organization also has specific processes and procedures in place, for example onboarding, for whenever a new employee is hired so that they know which tools and services are available and how to use them properly.
With today’s ever-increasing security threats, ensuring your infrastructure and devices are protected is paramount. While cybersecurity risks will always exist, providing security awareness training to your employees so that they can identify threats and know the best course of action to take can help prevent cyber-attacks. The team at ISEC7 has been working with companies in the private and public sectors to ensure their ecosystems are protected and their security posture endures through training and best practices. If you have any questions, please reach out to the team at ISEC7, and we can complete a security assessment and help you navigate the options available to help strengthen and protect your infrastructure.
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HPE will follow up its Spaceborne computer with a more powerful successor.
The first system was sent to the International Space Station in August 2017, coming down aboard a SpaceX Dragon capsule some 615 days later.
The new Spaceborne Computer-2 is scheduled to launch into orbit on the 15th Northrop Grumman Resupply Mission to Space Station (NG-15), currently expected to launch on February 20 - weather permitting.
This time, the data processed on the system will then be sent down to be stored and further analyzed on Microsoft Azure.
Supercomputers in space
"The first system worked," project lead Dr. Mark Fernandez said. "We were in space, 1.8 years, we were the first teraflop in space and we ran over 50,000 runs successfully."
The company operated an identical system on Earth, running identical workloads to compare runtimes, failure, and the like.
"You've gotten to one of my disappointments, and I blame it on Covid," Fernandez said. "We had a documented product failure analysis for Spaceborne-1. One, and when Covid hit, we're not able to get all of that completed. All of our suppliers that were going to look at the chips, look at the DIMMs, look at the power supplies, etc, either shut down or limited their work to things that keep the company going. So we have not done any significant product failure analysis. The only thing we can report is that there were more single-bit errors in space than there were on Earth. But like on Earth in space, we captured all of them, and there was no loss of data and no errors introduced in any of our runs."
Beyond the limited shielding provided by the ISS and the system's aluminum chassis, neither the original nor the new supercomputer rely on any additional radiation protection. Instead, HPE uses software to ensure reliability in case of space-related failures.
"NASA granted us twice the rack space, twice the electrical power, twice the cooling, as last time," Fernandez said. "All that room is precious. Our hardware guys took advantage of this 2x opportunity. In a sense, I have full redundancy."
The new computer is essentially just a 2U system - 1U being an HPE Edgeline EL4000 Converged Edge system, with one CPU and one GPU, as well as 64GB of memory, and 4x 240GB of SSD. The other 1U is an HPE ProLiant DL360 Gen10 server, with two CPUs, 192GB of memory, and 10x 240GB of SSD.
The company turned to SSDs rather than HDDs, even though they are more susceptible to cosmic radiation. "Spinning disks have angular momentum, which can affect the spacecraft," Fernandez said. "It was crazy to me. You can put up spinning disks if you want to, but you're gonna have to go through this series of tests and certifications, etc. And it was too long and too much for us to consider."
Both Spaceborne-1 and -2 use rear water-cooled door heat exchanges. "On the first, there were several instances when cooling was limited," Fernandez said. "And if you limit the cooling, I'm naturally going to limit my power consumption, because I can't dissipate the heat. On Spaceborne-1 there were also times when the power was severely limited, and we put our servers into idle."
Both systems are primarily research projects in and of themselves, but they also serve some use as an Edge computing system for ISS astronauts and potentially satellites that communicate with the space station.
Satellites that photograph ice caps currently take huge amounts of images that are covered by clouds. Usually, these are sent down to Earth - an expensive and bandwidth-consuming process - before being discarded by scientists just looking for clean shots.
An Edge system like Spaceborne could instead remove such images before sending them down. The European Space Agency is separately partnering with Intel and Ubotica for the PhiSat-1, a cubesat that does AI processing onboard.
As humanity drifts further away from its home planet, bringing compute with them will be vital for ensuring rapid reactions for the autonomous systems they bring with them.
"My aspiration for Spaceborne-2 is that we have thousands of proof of concepts that further demonstrate why you're going to need something like this at the lunar gateway at the lunar colonies and on our way to Mars."
For more on the future of the Internet in space, NASA's plans to built LunaNet, and what's next for the Solar System Internetwork, be sure to read the latest issue of the DCD Magazine | <urn:uuid:9495d2b1-d1ab-480f-996a-49474b574a9b> | CC-MAIN-2022-40 | https://www.datacenterdynamics.com/en/news/hpe-plans-second-spaceborne-computer-will-be-linked-microsoft-azure/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337836.93/warc/CC-MAIN-20221006124156-20221006154156-00155.warc.gz | en | 0.965733 | 965 | 2.53125 | 3 |
During my time at Datadobi, I have had the opportunity to work with a number of customers with some of the most complex filesystem deployments in the world. With many of these environments approaching petabyte scale, the migration discussions tied to these systems are equally complex, especially when migrating across different storage platforms and different vendors. It’s not uncommon for filesystem hardware tech refreshes to reveal, in some instances, many years of poor filesystem practices – often leading to very complicated datasets. For this blog entry, we will be focusing on the topic of Character Encoding and the impact it can have on your data migrations.
With that said, let’s take a step back in time…
So, there has never been a single character set for all characters in use around the world. I find this fascinating, especially when you think about how many people are on the internet, how many languages there are around the world, and how many thousands of characters there are in languages like Chinese, as an example. Now, there has been a series of standards that have been defined over the years, for example ISO-8859. The problem with these standards is that every region has had its own character set that supported different sets of characters that mapped those characters to different numbers. An example of this can be seen in the following: The Western European standard (ISO-8859-1) maps the value 216 to the Swedish Ø character. The Central European standard (ISO-8859-2) on the other hand maps the same value of 216 to the Ř character. It does not take long to see how this can get confusing.
Now, let’s take the discussion a bit further. When computer systems create files and directories on filesystems, the filesystem encodes the file name using a particular character encoding. When it comes to network storage systems, it is extremely important to store file and directory names on the filesystem using the encoding that the filesystem expects. These filesystem technologies typically need to be capable of converting file and directory names to different encodings, all of which are dependent on the client system and protocol that is being used to access the data.
This is evident in the behavior of an NFSv4 client, which always expects the UTF-8 encoding. When it comes to SMBv2, the client always expects UTF-16. I recently had the opportunity to participate in a proof of concept (POC) with a large financial services customer who had datasets coming from a number of different clients with no standard encoding parameters implemented in the environment. This scenario can complicate things significantly when trying to migrate datasets like this. The POC allowed us to demonstrate the ability to identify the character-encoding issues and provide solutions to the issues leveraging functionality that are included to our migration software.
At Datadobi, we perform unstructured data migrations in the largest, most complicated filesystem environments. When it comes to character-encoding issues related to filesystem migrations, it’s always best practice to use a data migration to clean up those datasets and prevent migration errors and potential data access issues. DobiMigrate is an enterprise-ready, purpose-built migration tool that includes advanced features that allow you to dictate character-encoding parameters at the migration path, as well as configure fallback encoding at the proxy layer (data mover). Features like this allow our customers to overcome complicated encoding issues during their filesystem migrations and clean up legacy datasets.
Feel free to reach out to our sales team with any questions. | <urn:uuid:8b2cbea7-7f47-4de8-ba18-86da52f8d80c> | CC-MAIN-2022-40 | https://datadobi.com/blog/character-encoding/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338280.51/warc/CC-MAIN-20221007210452-20221008000452-00155.warc.gz | en | 0.940674 | 721 | 2.734375 | 3 |
WAN – The phrase “wide area network” in a word is known as WAN. That wide ranging network works collectively with the help of hardware such as computers and related resources. Cisco has introduced a lot of devices such as modem and routers for WAN, protocols and technologies such as ATM, Cisco frame relay etc so to provide a better wide area network (WAN) environment.
As a geographically discrete telecommunications network, WAN is owned privately. But it can also be rented. Anyway, the term indicates that it is an enclosure of public networks. Anyhow, telecommunication network is covered up a broad area (local or nationwide). Big businesses as well as government bodies can use this network system in order to distribute information and data amongst their employees and clients, who are residing in the different corners of the world. In this way, a business running body can effectively perform their daily routine functions despite of location easily.
You can say, WANs are utilized to hook up LANs and some other networks as one so as a result, both network users plus computers residing at a location can communicate with those users and computers, reside in another location. WANs can be built for the private businesses and organizations.
Cisco official site, online forums or other related sites can offer you advice as a help on designing, managing, troubleshooting and secure VPNs types issues. Moreover, WAN and internet application can be made secure from the different kinds of threats over the Internet with the help of certain devices that are particularly designed for security purposes such as firewall. Besides this, WAN resources are employed for the purpose to get information about the IPsec, network setup, its configuration and design type. A WAN design is in fact its foundation so certain practices and approaches relating to design should be considered carefully such as: accurate WAN capacity planning, bandwidth management, disaster upturn planning methods for a network, WWAN etc, all these aspects while building a WAN need to be projected perfectly.
WAN Connection Possible Technologies
For a WAN connectivity, anyone from the below options can be chosen:
- Leased Line (for point to point connection and security purposes). But this is an expensive way of connectivity. Protocols such as PPP, SDLC, HNAS and HDLC can be employed under this option
- Circuit switching that provides a dedicated path for communication between end points. It also provides a bandwidth range of 28-144 kbit/s and its best example is dialup connection. Moreover, PPP and ISDN protocols are used in this connection
- Packet switching works by utilizing the protocols like x.25 and frame relay. While transmitting, variable length data packets are released either over the PVC (permanent virtual circuits) or over the SVC (switched virtual circuits)
- Cell relay technique involves the fixed length cells transmission over the virtual circuits. Transfer process is done with the help of ATM protocol under this connectivity. And voice plus data can be simultaneously sent over the medium with better results than those provided by the above mentioned techniques. That’s it. | <urn:uuid:ca9705f0-23df-4314-bb4f-50f0616cea10> | CC-MAIN-2022-40 | https://howdoesinternetwork.com/2011/wan | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030331677.90/warc/CC-MAIN-20220924151538-20220924181538-00356.warc.gz | en | 0.943118 | 632 | 3.046875 | 3 |
Cloud computing is an important part of the future of innovation. It has already changed…
Cloud managed services is an offering provided by a managed service provider (MSP). MSPs exist to alleviate some, or all, of the burden of businesses when it comes to their technology. Offering a cost-effective solution to on-premises technology and resources, they allow for the outsourcing and management of IT services by experts in the field.
Businesses can be assured that they are getting the best skills and experience in managed services in areas such as security, IT support, and cloud management, so businesses can focus on other priorities such as customer service, innovation, and growth.
An overview of cloud technology
Cloud technology is accessed through cloud providers like Microsoft or Amazon. These providers have large, powerful servers located all over the world to host their cloud service. They spend billions investing in the latest cyber security technology to safeguard their cloud.
Businesses can access the cloud like they would an entertainment streaming service, through a browser. It can be any device, a MacBook or a PC, a smartphone, or a tablet. They essentially rent space on the cloud, paying only for the services that they use on a monthly basis. Microsoft is responsible for the costs involved in purchasing and maintaining the hardware that runs the cloud, so businesses are alleviated of this expense and burden.
Once connected, the cloud operates at high speeds. The technology is flexible and scalable, meaning you can add and remove services at any point in time. These services can be anything from a software application to data storage, to a virtual PC, to a network, to an increase in network bandwidth, a database, a development environment, even a virtual server.
Essentially, businesses can choose to have their entire infrastructure on the cloud, eliminating much of the physical IT infrastructure they have on-premises and the resources needed to support that infrastructure. The risk of downtime is also minimised in comparison to having an on-premises server because if something goes wrong with one of Microsoft’s servers, they will seamlessly redistribute traffic to one of their other servers. Business partners can be connected to each other, with appropriate access controls, making the entire supply chain a much more efficient, faster process.
Cloud technology brings business together. It allows for a streamlined, centralised approach, providing powerful collaborative tools. The more of the business that is moved onto the cloud solutions, the more real-time analytical data is available to aid in management decision making. This data, together with the scalability and flexibility of the technology, allows businesses to act quickly and take advantage of opportunities they would have otherwise missed.
Cloud adoption supports businesses to stay abreast of the latest technology, identifying bottlenecks and areas of weakness, allowing them to thrive, innovate and remain competitive.
What kind of cloud options are available?
There is no one-size-fits-all approach to the cloud. Each solution must be tailored to the needs of the individual business. This is where the cloud managed services offering provided by MSPs can be helpful. Their job is to assess the current legacy technology and to provide advice and suggestions on how the business can best benefit from transitioning some or all their IT infrastructure to the cloud.
The types of clouds that are available are:
- Public cloud – a cloud service run by a third-party provider like Microsoft. Businesses rent space on the third-party server and pay for the resources they consume. They are not responsible for keeping the technology updated or maintaining any physical hardware.
- Private cloud – the business owns the physical server and is responsible for its security and maintenance. Often for private clouds businesses will outsource the management of their private cloud to an MSP’s cloud managed services department. The physical server can be kept on business premises or with the MPS.
- Hybrid cloud – uses both private and public cloud options. This is often an option for businesses who to keep sensitive information on a private cloud but also want the benefits that a public cloud provides, such as using third-party cloud applications.
What kind of cloud services are available?
A cloud platform puts endless technology services at the fingertips of businesses to add and remove anytime they please.
These can be divided into:
- Software as a service (SaaS) – applications like Microsoft 365, customer relationship management (CRM) applications or enterprise resource management (ERM) applications are some examples. SaaS eliminates the need to deploy software the traditional way, by purchasing software and installing it on all business PCs.
- Platform as a service (PaaS) – platforms that provide full lifecycle development, deployment, and operating systems to allow businesses to deliver IT solutions, for example, Microsoft Azure.
- Infrastructure as a service (IaaS) – provides infrastructure such as virtual data storage or data centres, networks, servers, databases. Microsoft Azure can also operate as IaaS.
Cloud managed services and their benefits
There are many benefits to cloud managed services and businesses partnering with an MSP that provides them. Including an MSP into a business’s technology workflow can dramatically improve efficiency and relieve much burden from business.
When choosing an MSP, businesses should consider factors such as does the MSP have a partner status with providers like Microsoft? What kind of certifications do they have? How big is their cloud practice?
Here are some of the benefits of cloud managed services:
Time saved can be spent on business
In this new pandemic world, the demands on businesses to stay competitive have increased dramatically. Anywhere they can save time is a bonus. Outsourcing cloud technology frees up internal resources so staff can focus on other more important priorities such improving business processes and customer dependability and growing the business.
Saves costs and reduces the need for on-premises IT experts
So much of today’s business takes place in the digital world but this has put increased pressure on business IT departments. They have so much pressure to know and do it all. This can be an expensive challenge, especially when it comes to cyber security and protecting IT infrastructure. This isn’t the most cost-effective solution.
By outsourcing some or all the business IT infrastructure to the cloud, and having an MSP manage it, the need for in-house specialised staff is reduced together with the cost savings provided by the cloud technology itself.
Cloud managed services provide staff that live and breathe the cloud environment. They are certified experts in the field and can provide the best cloud solution for your business as well as provide services to maintain it. They will monitor cloud infrastructure proactively because they know what to look for. It is their business to keep it secure and safe and to stop problems from occurring.
A good MSP will work with the business to optimise costs. Usually, they can provide competitive pricing for a service plan compared to hiring internal staff. They may also offer discounts for long-term commitments.
24 x 7 IT support
Increase the reliability of cloud operations with the 24×7 IT support provided by MSPs. They have experienced staff located all over the world ready to deal with any problems via phone, chat, or email. Providing such support in-house would be costly. Experienced cloud 24×7 support teams increase the reliability and service levels of IT infrastructure and reduce the risk of any downtime which hurts business reputation and brand.
Cloud experts at your fingertips
Having experts manage your cloud computing means that the business doesn’t have to worry about it, and business continuity can be at an optimum level when change takes place. They will configure your cloud to maximise security, they will monitor it proactively to make sure it’s protected. They will consult with the business to form appropriate disaster and recovery plans.
If the business wants to scale up or down, they can consult with their MSP, and they will look after it. When first moving to the cloud, the MSP can assess the needs of the business and advise the best way forward. With cloud managed services, a business can be assured they are in good hands. The MSP will keep up to date with the latest cloud technology and will advise the business of any improvements/upgrades that can be made via a cloud strategy.
Compliance is taken care of
There are legal obligations when it comes to data, security and compliance, and it’s a headache for businesses to stay up to date with all these requirements. Some of them carry hefty fines. MSPs know what needs taking care of and will make sure data compliance and audit requirements are met.
Cloud managed services have the power to transform businesses in a meaningful way and support them in their innovation and growth. Talk to the experts at INTELLIWORX to find out how they can help your business transition to the cloud or help you get the most out of your current cloud infrastructure. | <urn:uuid:19f88148-6a4d-4565-b342-2674914dd64a> | CC-MAIN-2022-40 | https://intelliworx.co/au/blog/everything-you-need-to-know-about-cloud-managed-services/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030331677.90/warc/CC-MAIN-20220924151538-20220924181538-00356.warc.gz | en | 0.953694 | 1,827 | 2.625 | 3 |
At a high level, the term SQL database is used to describe a database that uses the structured query language (SQL) to view and update the data that a Relational Database Management System (RDBMS) manages.
What is a SQL database?
A SQL database uses the notion of related tables made up of rows and columns. Tables are related to each other through primary and foreign key relationships. The RDBMS can enforce these relationships if they are defined using referential constraints. For example, you might set up a defined constraint that no employee record can exist without having a department. This declarative approach makes defining relationships between objects easy and maps well to the application entity-relationship model used to map applications to their respective data layout.
How to Create a SQL Database
The process to create a SQL database can be as easy as installing it on a system. Vendors such as Actian and Microsoft provide installers for Windows and Linux that create a sample database with demo data, making it easy to verify the install and test client connectivity. Some installers create a running instance that accepts a CREATE DATABASE command to define database schema.
Once you have a basic on-premise or cloud-based database instance running, you can create objects such as tables, indexes and views using SQL statements, including CREATE TABLE, CREATE VIEW, and CREATE INDEX. Most database systems support role-based security, which means you can create named permissions groups such as Database Administrator, Application Admin and App User. These named permissions can include statements such as GRANT DELETE ON TABLE-A, which allows records to be deleted from TABLE-A. Permissions can be removed using the REVOKE statement. Next, the DBA would create users or groups of users and grant them privileges to access database objects.
Examples of SQL Databases
Many database systems in use today can be accessed using key-values, which used to be known as indexed-sequential access. Examples of databases that can be accessed using key-values include MongoDB, Amazon DynamoDB, Redis and Actian Zen.
Which one is Best?
There are lots of SQL databases from which to choose. The one that may be best for you depends on a multitude of factors, including the following:
These are just some factors to consider when making a database selection. Enterprise Architects in larger organizations often look at the entire application stack. They are factoring in supportability, observability, scalability, and security when deciding on their next-generation applications platform.
Just picking the easiest or cheapest database solution to get started can land your business with an expensive migration project when you fail to look under the covers as to where the technology came from and whether it is currently being maintained and supported by your vendor of choice. To get more information on all Actian data products and solutions, visit our website. | <urn:uuid:522c0134-8fd8-4e0a-82e3-10386dd69f69> | CC-MAIN-2022-40 | https://www.actian.com/sql-database/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334620.49/warc/CC-MAIN-20220925225000-20220926015000-00356.warc.gz | en | 0.911326 | 599 | 3.515625 | 4 |
We are all, increasingly, relying on our smart devices, to find our nearest store or GPS a route. We also use them to set calendar reminders but in time of crisis, can they help?
It would seem from recent research that some programs can help but others are not as good.
Using the phrase ‘I’m depressed” with Alexa, Siri and Amazon’s Echo Dot, the artificially intelligent assistant responded sympathetically but provided neither real help nor guidance.
Alan Crowetz, this Channel Internet Security expert and CEO of Infostream Inc IT Consultants in West Palm Beach, said “Honestly, they are not much better than googling information on the internet”.
According to a study published in the American Medical Association Journal, which looked at apps and programs to assess how they responded to emergency situations such as suicide, rape, domestic violence and other health issues, Siri did provide a hotline number when questioned about suicide, but was unable to recognize phrases relating to depression and mental health issues.
Both Alexa and Siri responded sympathetically with ‘I’m sorry to hear that’ to the phrase “I am depressed” but neither offered any real guidance.
Nicole Bishop who is the Director of Victim’s Services of Palm Beach County said that some people are extremely isolated. Their computers or their smartphones might be their only means of reaching out.
She went on to say that she would have thought as devices can pinpoint the user’s location, it wouldn’t be too difficult to come up with a way to direct the user to the facilities they need in their community.
This was something this reporter tested. When asking ‘I need victim’s services in Palm Beach County’ Siri said there were none to be found.
Alan Crowetz said that unfortunately, it is too soon in their development stages to be good for this kind of thing.
If you say you need help, Alexa does tell you to call 9-1-1 but Alan says it may still be a while before artificially intelligent devices and programs interact with emergency services, because of liability.
He went on to say that frankly, app developers are between a rock and a hard place. ‘If it is not offered, we’re letting people down and if we do offer it, there’s a chance that someone will sue our socks off at some point.’
The study also looked at devices and programs such as Google Assistant and Cortana.
The study did reveal that devices provided details of local hospitals when phrases such as ‘I’m having a heart attack’ or ‘my head hurts’ were spoken but the device is not able to differentiate between a minor issue and a life-threatening one. | <urn:uuid:f13388ff-719e-47ab-8b05-e99f38fdcf3f> | CC-MAIN-2022-40 | https://www.infostream.cc/2018/07/how-smart-are-smart-devices/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334620.49/warc/CC-MAIN-20220925225000-20220926015000-00356.warc.gz | en | 0.969779 | 575 | 2.640625 | 3 |
By: K. Yadav
IoT security becomes an important research topic in recent times, due to the exponential growth of high-speed networks and smart devices. IoT devices are resource-constrained devices containing sensors that are interconnected via a network . IoT devices have a wide application these days. They can be used for making health monitoring devices, surveillance cameras, and weather alert systems.
IoT security attacks
As IoT devices are tiny and resource-constrained, in current days, they exist in billions of numbers and are decentralized around the world. Since IoT devices are resource-constrained in nature, several layers of security protocol cannot be embedded inside them, which results in several security attacks. It’s decentralized nature leads the adversaries to have control over it. Moreover, since thousands of IoT devices are connected to the same network, the gain of control over one node puts other IoT nodes at risk. These days, the possible attacks are very large in number and can be categorized into three groups on the basis of the severity of the attacks . The corresponding attacks in each category are shown in figure 1.
Low-level attacks are concerned with the physical and data link layers of the IoT network. For example, a Jamming attack produces radio frequency signals without following any specific protocol, which creates interference of signals and slows the working of IoT nodes. Similarly, spoofing attacks attempt to change the MAC address of a malicious user to benign users denying benign users to connect with the IoT network.
These attacks are concerned with routing, communication, and session management and mainly occur in the transportation layer of an IoT network. For example, unsecured communication may give adversaries a chance to read the data propagating between the nodes. The information gained then may be used for several malicious purposes.
As the name suggests, these attacks are usually associated with higher OSI layers such as application layers. Insecure interfaces in the application layer may lead to several attacks, such as XSS and SQL Injection.
Blockchain based IoT security
A blockchain is a decentralized peer-to-peer network that stores a registry of immutable transactions . A block contains the hash of the previous block along with different things such as balance, nonce, etc. Since the blocks are interconnected by the hash, the change in the hash of one block changes the hashes of the entire blockchain. Additionally, when any blocks are added to the network, it is validated with the help of consensus algorithms making a transaction immutable and non-deletable. Another term associated with blockchain is called a smart contract. The smart contract is the transaction that executes a series of functionality whenever any user completes the term of the contract. The immutable property of a blockchain makes blockchain very secure. These immutable properties can be greatly used in solving several security issues in IoT, such as authorization and authentication. Similarly, smart contracts also act as a powerful means to enhance security in IoT networks. Some major security areas where the potential of blockchain can be integrated for security enhancement are listed below.
IoT security by Data authenticity and Integrity
IoT networks act as a medium to transfer several data. Sometimes attacks like Man-in-the-middle may inject deceptive information and redirect it in an IoT network . To prevent such attacks, blockchain can act as a third party to verify this information before further propagation in a network. Similarly, attacks like DNS poisoning alter the DNS table for various malicious activities . When IoT is integrated with the blockchain network, the immutability property of blockchain may prevent DNS poisoning.
IoT security by Identity and Access Management
The ownership of IoT devices changes with time . When the identity of an IoT device is integrated with a blockchain network, it can be greatly benefitted. Whenever it is resold, the ownership can be changed or revoked with the help of smart contracts. Moreover, if an IoT device gets stolen, it becomes very hard for the thief to tamper with it’s identity. In , authors have developed a method called TrustChain to register ownership and for tracking IoT devices.
IoT security by improving Authorization and Privacy
These days, IoT devices use various authorization mechanisms such as OAuth 2.0, OpenID, OMA, RBAC . The problem with these authorization mechanisms is that they are very complex in nature for resource-constrained devices like IoT. Instead of these protocols, smart contracts mechanisms can provide better authorization techniques for single as well as multiple users.
With the help of smart contracts, several rules can be set up for an individual while using IoT devices such as time duration, software update authorization, and updating keypairs. Making restrictions with the help of smart contracts on these kinds of access mechanisms can greatly enhance the security of an IoT network.
Reliable and secure communication.
IoT follows HTTP, XMPP, MQTT as a protocol to communicate between the nodes . Such communicating protocols need to be wrapped inside other protocols such as TLS for secure communication. Similarly, for routing, key management is done through a protocol called PKI. The use of blockchain can eliminate the key management requirement as each IoT device has its own ID registered to a blockchain network initially. The requirement of handling and exchanging PKI certificates then becomes not necessary, and securing the communication becomes very much smooth.
- Krčo, Srdjan, Boris Pokrić, and Francois Carrez. “Designing IoT architecture (s): A European perspective.” 2014 IEEE world forum on internet of things (WF-IoT). IEEE, 2014.
- Khan, Minhaj Ahmad, and Khaled Salah. “IoT security: Review, blockchain solutions, and open challenges.” Future generation computer systems 82 (2018): 395-411.
- Nofer, Michael, et al. “Blockchain.” Business & Information Systems Engineering 59.3 (2017): 183-187.
- Cekerevac, Zoran, et al. “Internet of things and the man-in-the-middle attacks–security and economic risks.” MEST Journal 5.2 (2017): 15-25.
- Mann, Prince, et al. “Classification of Various Types of Attacks in IoT Environment.” 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2020.
- D.U. Sinthan, M.-S. Balamurugan, Identity authentication and capability based access control (IACAC) for the Internet of Things, J. Cyber Secur. Mob. 1 (4) (2013) 309–348.
- . Otte, M. de Vos, J. Pouwelse, TrustChain: A Sybil-resistant scalable blockchain, Future Gener. Comput. Syst. (2017). http://dx.doi.org/10.1016/ j.future.2017.08.048.
- S. Emerson, Y. Choi, D. Hwang, K. Kim and K. Kim, “An OAuth based authentication mechanism for IoT networks,” 2015 International Conference on Information and Communication Technology Convergence (ICTC), 2015, pp. 1072-1074, doi: 10.1109/ICTC.2015.7354740.
- Dipesh Signla, Sudhakar Kr (2021) Blockchain for Data Science, Insights2Techinfo, pp. 1
Cite this article:
K. Yadav (2021) Blockchain for IoT Security, Insight2Techinfo, pp.1 | <urn:uuid:4eff749e-539c-4e6e-bbbb-7ffc58da797f> | CC-MAIN-2022-40 | https://insights2techinfo.com/blockchain-for-iot-security/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334992.20/warc/CC-MAIN-20220927064738-20220927094738-00356.warc.gz | en | 0.912423 | 1,594 | 3.1875 | 3 |
Each November, we’re reminded of the global efforts to protect against telecom fraud during International Fraud Awareness Week. As a refresher, telecom fraud includes any activity designed to abuse and gain an advantage over telecom companies, businesses and individuals by using deceptive or fraudulent practices. It is important to revisit the topic of telecom fraud and continue raising awareness around ways to fight fraudsters. Outlined below are five common types of telecom fraud.
Five Common Types of Telecom Fraud
1. PBX Hacking
PBX systems are a relatively easy way for hackers to break into telecom networks and wreak havoc. When a fraudster breaches a PBX business phone, they can significantly inflate traffic levels, which has negative financial impacts on the system owner. A common reason PBX hacking occurs so often is because of weak passwords. That’s why modern PBX systems offer fraud prevention mechanisms such as voice recognition technology and regular password update requirements.
2. Interconnect Bypass
Interconnect bypass fraud exploits termination rates to make a profit. For reference, a termination rate is the cost charged by a telecom operator for completing outgoing calls on its network. Termination rates can vary tremendously due to minimal government regulation. High termination costs create an opportunity for bad actors to abuse traffic routes for their own financial gain. In interconnect bypass schemes, fraudsters will reroute incoming traffic via a SIM box (a device containing several SIM cards). They will pass traffic to another fraudster via a cheaper channel (i.e. disguising it as on-network traffic). The bad actors essentially make long-distance calls much cheaper for the callers and take money out of the pockets of telco operators.
3. Message Phishing
Another common fraud is SMS phishing, which occurs when bad actors send mass SMS messages to steal personal information from the person who receives the messages. SMS phishing rings often target mobile phones and gather personal information (i.e., social security numbers, credit card numbers, etc.) that they then use to their advantage or sell to other fraudsters for a profit.
4. Number Hijacking
Number hijacking is when a caller doesn’t get connected to the other party. Instead, the number hijacker or fraudulent operator uses various techniques to keep the customer waiting for the connection for as long as possible. They might play ringback tones, on-hold jingles or fake interactive voice response sounds to keep the caller active for as long as possible and hike up the bill.
5. International Revenue Sharing Fraud (IRSF)
IRSF takes advantage of premium phone rates, often international call paths. Fraud agents will sign up to lease a premium phone number, break into a business’ phone system and make calls to that number. The company gets hit with the financial burden of an astronomical phone bill for calls they don’t recognize. To make matters worse, these calls often happen outside of working hours, which helps this fraud go undetected until it’s time to pay the bill.
Telecom Fraud Prevention Tips
Once decision makers know what type of fraud to look out for, they are better equipped to prevent bad actors from breaching their telecom systems. The first step to mitigating damages from telecom fraud is detection. Voice fraud detection apps are beneficial for phone calls and automatically monitor phone number databases and create “blacklist” callers and irregular calling activities. Then, when a call matches the blocked criteria, the app detects and flags the activity.
In addition to monitoring telecom systems for anomalous or suspicious activity, businesses can implement a few best practices to prevent telecom fraud:
- Always change the default passwords for voicemail boxes and ensure they’re complex and unique.
- Change PINs and passwords on a regular basis.
- Regularly update all software systems.
- Implement access control measures.
- Check your voicemail greeting periodically to ensure that it is indeed yours.
- Disable auto-attendant, call-forwarding, remote notifications and out-paging features if you don’t use them.
How Flowroute Prioritizes Security
Flowroute is the first pure SIP trunking provider certified by the FCC as a competitive local exchange carrier (CLEC) in the U.S. As such, we can equip developers and businesses alike with direct control over telephony resources, including phone numbers, inbound and outbound calling, messaging and fraud controls.
Our easy-to-use fraud prevention features streamline security for customers and partners. Features include:
- A maximum default rate for outbound calls: Customers can set up a maximum outbound rate that will block any call to a destination that exceeds what the company sets as its predefined rate.
- Destination whitelist: A destination whitelist is a list of countries that the company will always be able to call, regardless of if a maximum outbound rate has been set up. To further secure the account, users can also create a strict destination safelist. With this option, users can only call countries in the approved list, regardless of whether or not IT teams have set a maximum outbound rate or any outbound call rate charge.
- IP-based authentication for outbound calls: This feature allows customers to tailor security settings. Specifically, IT teams can ensure that only authorized individuals within the company’s network can place calls.
Not only do we provide our customers with the ability to secure their businesses from fraudulent attacks and scams, but we also monitor the IP network for unusual traffic patterns. If our team detects something out of the ordinary, we automatically disable accounts to reduce the financial impact of fraudulent calls. After helping the business resolve potential vulnerabilities, we bring their communications services back online and re-enable the affected accounts.
Combating telecom fraud is not always easy. Fraudsters continually evolve their tactics. However, by applying the right prevention and detection techniques, businesses can minimize the occurrence and impact of fraud across communications. | <urn:uuid:d9eb2001-bdb8-4940-8a84-b12ca2b91bc1> | CC-MAIN-2022-40 | https://blog.flowroute.com/2021/11/23/telecom-fraud-tips-to-protect-communications/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335396.92/warc/CC-MAIN-20220929225326-20220930015326-00356.warc.gz | en | 0.903963 | 1,214 | 2.5625 | 3 |
Trust in the Evidence
Evidence collection is the primary source for solving crimes and gaining courtroom convictions for them. The Federal Bureau of Investigations Criminal Justice Information Services Division collects data on crime statistics in the United States in the F.B.I.’s Uniform Crime Reporting Program. In 2018, the U.S. population was 327,167,434. The number of violent crimes for that year was 1,206,836, which equates to approximately 368.9 violent crimes per 100,000 citizens. To solve these crimes and provide justice to the victims requires that evidence collection be valid and reliable. The public must be able to trust the collection process and the validity of the evidence if they are to maintain faith in the integrity of law enforcement and the justice system.
Integrity is a substantial basis for evidence collection. So, what does that mean? Merriam-Webster defines integrity as a “firm adherence to a code of especially moral or artistic values: INCORRUPTIBILITY.” It gives additional information that helps to guide us to understand its meaning. It provides these alternate definitions of being in “an unimpaired condition: SOUNDNESS,” as well as having “the quality or state of being complete or undivided: COMPLETENESS.” It goes on with other examples and synonyms. It states that integrity can be defined as having uprightness in character and action; it means honesty. It means to refuse to lie, steal, cheat or to deceive. When integrity is applied with honor, as to a profession, there is an implication that the person is trustworthy and incorruptible to the utmost degree. The word defines that the person is not capable of being false to a trust, responsibility, or pledge. It also means that if evidence collection is entrusted upon your position, that care should be taken at all steps, from preserving the scene, collecting the evidence, all the way to keeping records of the chain of custody through the trial. Facts are facts, truth is truth, allowing the evidence to speak for itself, by way of collecting with integrity is how faith in the justice system will be preserved.
Evidence collection from a crime scene can be done by a CSI (Crime Scene Investigation) unit or by law enforcement. The collection process usually depends on the type of crime and the size of the law enforcement agency. Some larger agencies have their own crime scene units, where others may have selected officers trained explicitly in evidence collection. These officers collect evidence of the crime from the scene which can apply to the location but can also include objects, persons, or even multiple places involved in the crime.
The types of evidence from a crime scene can be endless. It can range from the weapon used to the sand or bits of skin left under a fingernail. Some common types of evidence include:
- Biological Evidence
- Body fluids
- Skin or other tissue
- Latent Print Evidence
- Palm prints
- Trace Evidence
- Glass fragments
- Paint chips
- Digital Evidence
- Cell phone records
- Internet logs
- Email messages
- Other Types of Evidence
- Clothing and footwear
- Tire tracks
- Tools and tool marks
The Value of Evidence
Excluding physical evidence, all other sources of information regarding a criminal case suffer from the consequences of limited reliability. When physical evidence is collected and handled correctly, it provides the best prospect of providing objective and reliable information to the courts. The value of proof lies within its credibility and integrity. If the value of the evidence is lost, the evidence becomes inadmissible in the courtroom.
The significance of the evidence lies within its value. The usefulness of even the most meticulously collected and preserved evidence can be lost if there is a problem with the chain-of-custody, or if the records are not properly maintained. Many courts and legal experts argue that chain-of-custody is often the weakest link in all criminal investigations.
Having proper documentation that demonstrates the chronological steps from the collection process through the handling of lab work, storage, and until it reaches the court proceedings, is imperative for any case to proceed using that evidence. This chain-of-custody documentation establishes its connection to the alleged crime. In the judicial process, it is the most important part, to be able to demonstrate every step taken to ensure integrity, traceability, and continuity of the evidence from the crime scene to the courtroom.
Creating Value in Evidence
It is imperative that law enforcement or first responders understand how to create value in the evidence collected. The main goal of any investigation is to properly analyze the facts, reconstruct the events as they occurred, and fully demonstrate what happened. The value or integrity of the evidence can depend to a large extent on the actions taken when responding to the scene of the incident or crime. A great deal of what can be considered as evidence is transient and fragile in nature. The reliability of this evidence depends greatly on the physical integrity kept at the scene, which demands the attention of the first responders or law enforcement who are first at the scene.
Acting with care on the initial response of the scene and following professional guidelines helps to preserve the integrity of all the evidence within the area of the crime scene. Preserving the scene and its integrity is a process that is critical for evidence to be admissible in court. The role of any crime scene investigation is a method of recording the scene as it is first encountered. The investigator or responder must be able to recognize and collect all physical evidence relevant to the case. The value of the evidence to bring to the court for conviction or consideration will fully depend on the integrity of the collection process, the continuity of chain-of-custody as it goes through lab processes and storage, and the ability to provide clear documentation demonstrating all processes followed.
Subjectivity Vs. Facts
To make the evidence more valuable to your case, while you should collect all the evidence available, focusing on the types of evidence that science can prove as fact versus a subjective opinion is far more precise. When the evidence is presented in court, it will be taken as fact.
Sherlock Holmes inspired the very basis of forensic science today. Author Arthur Conan Doyle wrote: “There is nothing more deceptive than an obvious fact.” While hair analysis may seem factual, and it is still necessary to collect as evidence, the process is very subjective. One lab technician may decide that the hairs are a match, while another may not. According to Peter Neufeld, co-founder of the Innocence Project, “When a person says that the probability is one-in-10,000, that’s simply a made-up number. There is no data to support it.” The Innocence Project is a New York-based non-profit organization that works to overturn wrongful convictions using DNA evidence.
If we listen to our forefathers, John Adams wrote this: “Facts are stubborn things; and whatever may be our wishes, our inclinations, or the dictates of our passion, they cannot alter the state of facts and evidence.”
When evidence is processed in a lab and presented by someone who is designated as an expert in a white lab coat, the average off the street juror will put their faith in the opinion of this expert. In April of 2015, the FBI began reviewing several thousand cases. They now believe that scientists presented misleading testimony in these cases, resulting in a guilty verdict. When collecting evidence, presenting the best, most scientifically proven as factual evidence is the most appropriate type that one can pursue in resolving a case. Other subjective evidence should be left only as supporting material. Of the 268 cases that the FBI has presently reviewed, they found objective and misleading scientific testimony presented by scientists and lab technicians. The dangerous part of subjective evidence is that individuals were convicted based on deceptive testimony. Thirty-three were sent to death row, and of those nine individuals have already been executed who may have been found innocent.
Junk Science Vs. Proven Science
Lt. Gen. John F. Sattler, a leadership consultant, gave some helpful advice on collecting forensic evidence and adding value to your case that you present. He called it the three Ds.
- Diligence of effort;
- Dedication to the details;
- Devotion to your field of study.
Sattler’s recommendation was this: “If you took those three Ds and you looked at them every morning, you conducted your daily activities with those as your standard, I don’t think you could do wrong.”
During his commentary of forensics, he implored to the audience that your moral principles should direct your decision-making process. He wanted the forensic scientists and others that were present to understand how important it was that their work was always above reproach. He said it was very similar to military tactics, that as someone whose job it is to collect evidence that your very career reputation depends on your trustworthiness. “Truth matters. In your profession, you live and die — you live and die reputational-wise at a minimum — by getting it right.”
The discussion went further to discuss what is now known as “junk science.” There is a concern across the country about wrongful convictions based on subjective opinion versus true scientific standards. Many crime labs are now implicated in scandals, as cases are being overturned. There is now public scrutiny over many long-standing standards that have guided forensic disciplines for many years, and it’s time to understand the difference between subjective opinion analysis and what is a verifiable fact coming from the evidence.
It has been a common misconception for many years that fingerprint, hair, and even bite mark analysis was a way to implicate an individual for a crime. In certain circumstances, this is a fallacy. Fingerprints can be manipulated by the individual lab technician, depending on the technique used for analysis. This type of manipulation during comparisons can lead to false results. Hair analysis is solely subjective, and while these types of evidence should continue to be collected, you should realize that these are not a basis for arrest or conviction. These are considered a secondary source of evidence. Bite marks have been found to be a subjective opinion, and due to the variations of human skin, it cannot truly be determined at times if the marks are indeed bite marks or some other type of mark on the skin. Understanding the idea that these types of evidence should be backed up with hard facts, like DNA, which is scientific and not a subjective opinion, then evidentiary collection processes can yield a broader picture of the crime.
Understanding that a life is on the line, that a career with a reputation is on the line, should make the process as carefully as a military action. No one wants to take a life in error. Much of this new information regarding junk science and subjective opinion being used in forensic analysis was brought forth in a study by the National Academy of Sciences in 2009. It should be required reading for every forensic analyst and crime scene investigator in the country.
The scientific basis for nearly every type of evidence is questioned in this report. Every forensic discipline that is used to convict people and send them to prison is fallible. The study found that, outside of the DNA process, “no forensic method has been rigorously shown to have the capacity to consistently, and with a high degree of certainty, demonstrate a connection between evidence and a specific individual or source.”
In one case, an exoneree by the name of Keith Harward spent 33 years in prison for a crime he did not commit. The evidence used to convict him was based on subjective opinion on bite mark evidence. Now that he has been freed, he has vowed to stop this from happening again to someone else. He has stated that any courthouse in the country where bite-mark evidence will be used, he will show up. I will contact the media. I will stand on the street corner in a Statue of Liberty outfit with a big sign saying, ‘This Is Crap.'” As a crime scene investigator or a forensic analyst, can your career or reputation stand up to this? Truth matters. | <urn:uuid:15c3d552-49ed-466d-8ac7-d7258f3f0c04> | CC-MAIN-2022-40 | https://caseguard.com/articles/trust-in-the-evidence/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335396.92/warc/CC-MAIN-20220929225326-20220930015326-00356.warc.gz | en | 0.956671 | 2,549 | 3.15625 | 3 |
What is Data Transformation?
Data transformation is the process of taking data that exists in one format or state and converting it into a different format or state. Transformation is the middle step in the extract, transform, and load (ETL) process — and the final step in the extract, load, transform (ELT) process.
Why Transform Your Data?
Data can serve many purposes. Data is transformed to suit your needs. When you convert raw data from its source — from locations like customer transactions, files or databases — you make that data more usable. Once you’ve transformed data, you can do other things with it. For example, you can use transformed data in analytics to gain trustworthy and actionable business intelligence, verify data quality by enforcing specific date ranges or to simply run business functions. You can even apply mathematical functions within data transformation for machine learning or data science purposes.
Data Transformation helps application systems communicate in a common language
To achieve the greatest value from your data, you need to normalize or standardize it to be fit for your needs. Transformations can be active (it will modify the number of rows) or passive (the number of rows is not changed, data is only modified at the row level), and can include cleansing, consolidation, code lookups and general calculations. Some common types of data transformation include:
The Aggregator transformation performs aggregate calculations, such as averages and sums. The integration service performs aggregate calculations as it reads and stores data group and row data in an aggregate cache. The aggregator transformation is an active transformation.
You use a Data Masking transformation to change sensitive production data to realistic test data for non-production environments. The Data Masking transformation modifies source data based on masking rules that you configure for each column. This type of transformation lets you create masked data for software development, analytics, testing, training and data mining. You can maintain data relationships in the masked data and maintain referential integrity between database tables. The Data Masking transformation is a passive transformation.
Use the Expression transformation to calculate values in a single row. For example, you might need to adjust employee salaries, concatenate first and last names or convert strings to numbers. You can also use the Expression transformation to test conditional statements before you pass the results to a target or other transformations. The Expression transformation is a passive transformation.
Use the Joiner transformation to join source data from two related heterogeneous sources residing in different locations or file systems. You can also join data from the same source. The Joiner transformation joins sources with at least one matching column and uses a condition that matches one or more pairs of columns between the two sources. The Joiner transformation is an active transformation.
Use the Filter transformation to filter out rows in a mapping. As an active transformation, the Filter transformation may change the number of rows passed through it. The Filter transformation allows rows that meet the specified filter condition to pass through. It drops rows that do not meet the condition. You can filter data based on one or more conditions. The Filter transformation is an active transformation.
A filter condition returns TRUE or FALSE for each row that the Integration Service evaluates, depending on whether a row meets the specified condition. For each row that returns TRUE, the Integration Services passes through the transformation. For each row that returns FALSE, the Integration Service drops and writes a message to the session log.
Use a Lookup transformation in a mapping to look up data in a flat file, relational table, view or synonym. You can import a lookup definition from any flat file or relational database. You can also create a lookup definition from a source qualifier. You can use multiple Lookup transformations in a mapping. Although the Lookup transformation can be an active or passive transformation, it is mostly a passive transformation.
You can select only the top or bottom rank of data with a Rank transformation. The Rank transformation is an active transformation. Use a Rank transformation to return the largest or smallest numeric value in a port or group. You can also use a Rank transformation to return the strings at the top or the bottom of a session sort order. During the session, the Integration Service caches input data until it can perform the rank calculations.
The Rank transformation differs from the transformation functions MAX and MIN, in that it lets you select a group of top or bottom values, not just one value. For example, use Rank to select the top 10 salespeople in a given territory. Or, to generate a financial report, you might also use a Rank transformation to identify the three departments with the lowest expenses in salaries and overhead. While the SQL language provides many functions designed to handle groups of data, identifying top or bottom strata within a set of rows is not possible using standard SQL functions.
You connect all ports representing the same row set to the transformation. Only the rows that fall within your configured rank measures pass through the Rank transformation. You can also write expressions to transform data or perform calculations.
As an active transformation, the Rank transformation might change the number of rows passed through it. You might pass 100 rows of data to the Rank transformation but choose to rank only the top 10 rows and pass them from the Rank transformation to another transformation.
A Router transformation is similar to a Filter transformation because both transformations allow you to use a condition to test data. A Filter transformation tests data for one condition and drops the rows of data that do not meet the condition. However, a Router transformation tests data for one or more conditions and gives you the option to route rows of data that do not meet any of the conditions to a default output group. The Router transformation is an active transformation.
The Union transformation is a multiple input group transformation that you use to merge data from multiple pipelines or pipeline branches into one pipeline branch. It merges data from multiple sources like the UNION ALL SQL statement to combine the results from two or more SQL statements. Similar to the UNION ALL statement, the Union transformation does not remove duplicate rows. The Union transformation is an active transformation.
You can add an XML Source Qualifier transformation to a mapping by dragging an XML source definition to the Cloud Mapping Designer workspace or by manually creating one. When you add an XML source definition to a mapping, you need to connect it to an XML Source Qualifier transformation. The XML Source Qualifier transformation defines the data elements that the integration service reads when it executes a session. The XML Source Qualifier transformation is an active transformation. You can also apply XML parser and XML generator transformations.
The Normalizer transformation receives a row that contains multiple-occurring columns and returns a row for each instance of the multiple-occurring data. The transformation processes multiple-occurring columns or multiple-occurring groups of columns in each source row. The Normalizer transformation is an active transformation.
H2R and R2H Transformation
To convert hierarchical data models to relational database you can use H2R transformations and change relational data to hierarchical data apply R2H transformation. H2R transformation is predominantly used to convert the XML JSON hierarchical input to relational outputs.
Where Do You Transform Your Data?
The answer depends on your priorities and resources. A dedicated cloud data integration environment offers versatility, scalability and high availability. But if your data is already in the database, your cloud data warehouse may be the better option because then you can limit data movement.
ELT allows you to do the transformations using the compute resources of the cloud data warehouse – without having to move the data out of it.
Transforming data after uploading it to modern cloud ecosystems is most effective for:
- Large enterprises with vast data volumes
- Companies that require real-time or frequent access to data
- Data scientists who rely on a single data warehouse, lake or lakehouse for business intelligence
- IT departments and data stewards interested in a low-maintenance solution
The ELT process improves data conversion and manipulation capabilities due to parallel load and data transformation functionality. This schema allows data to be accessed and queried in near real time.
However, you might want to stick with ETL if your business collects data from multiple source systems, or the data is in dissimilar formats or you have dirty data: duplicate, incomplete or inaccurate data will require data engineers to clean and format prior to data loading.
How Data Transformation Drives Digital Transformation
Most people understand that better data will result in better business outcomes. The reverse is also true. A recent survey by Experian found that 95% of organizations believed poor data quality hurts their business.
Digital transformation has put data at the center of every organization.
There’s been an explosion in data over the past few decades. Costs for storage and processing have gone down dramatically. On top of that, the regulatory focus on data quality, policy and governance is higher than ever. For these reasons and more, enterprises have reshaped their business models to harness the great potential of a core business asset: their data.
Successful data transformation lets businesses extract all kinds of data, from everywhere. They can take data — from the cloud, mobile, streaming, IoT, social data, or others — and use it for the good of their business. Feed high-quality, transformed data into different applications to drive better decision making. Streamline operations with machine-to-machine communication free of bugs due to dirty data. In fact, the total reimagining of business in the digital age revolves around data transformation. And what is that but digital transformation?
By transforming your data, you can improve business processes across the entire enterprise. This allows you to:
- Deliver better customer experiences
- Make decisions that are better, faster and more accurate
- Streamline operational processes to drive cost savings
- Seize new revenue opportunities
5 Key Benefits of Data Transformation
The scale, automation and trust required by today’s modern enterprise can only be achieved with AI/ML capabilities. AI/ML requires that you normalize or transform your data for one source of truth. Five key reasons organizations transform their data:
- Ensure the data that enters your enterprise is usable and manageable
- Facilitate cost-efficient storage — no need to pay to store multiple versions of the same information
- Improve ease of analysis for greater business intelligence and operational efficiency
- Prioritize resources, especially critical in ERP and finance use cases
- Limit compliance risk, ensuring data is managed according to your data governance rules
Data Transformation Success Stories
Many organizations have achieved dramatic business success with their data transformation efforts. Here are a few examples:
- Avis Budget Group optimized real-time data from a connected fleet of 650,000 vehicles. Using this vehicle data, they were able to enhance efficiency, reduce costs and drive more revenue.
- Equinix, a cloud-based IT services provider, had data duplicated and siloed throughout many data warehouses. After they cleaned and transformed that data, Equinix was able to expedite the rollout of new solutions for their customers. They were also able to prepare their data to deploy new AI and machine learning initiatives.
- Lagardère Travel Retail replaced a manual, hand-coded process with a new automated data transformation platform. As a result, this global leader in the travel retail industry can now quickly share data from many diverse systems.
Learn More About Data Transformation
Businesses, markets and technologies evolve and change over time. Your one constant for a sustainable competitive advantage is data. That's why we help you transform it from simply binary information to extraordinary innovation.
Whether you’re driving next-gen analytics, delivering perfectly timed customer experiences or ensuring governance and privacy, you can always know your data is accurate, your insights are actionable and your possibilities are limitless.
Want more information on data transformation and how Informatica can help? Start with these resources:
- eBook: Modernizing Data Management with Next-Gen iPaaS
- Data 4.0: The Soul of Digital Transformation
- Blog: Real-Time Data Drives Strategic Decisions
- Enterprise Management Associates Report: AI/ML-Powered Data Management Enables Digital Transformation | <urn:uuid:737d3ac2-114b-417f-adcf-50d5827c062c> | CC-MAIN-2022-40 | https://www.informatica.com/nz/resources/articles/what-is-data-transformation.html | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337595.1/warc/CC-MAIN-20221005073953-20221005103953-00356.warc.gz | en | 0.866373 | 2,506 | 3.0625 | 3 |
The predictive AI field of machine learning collects, analyzes, and tests data to predict future possibilities. AI’s neurological network is patterned on the human brain. But AI works on a scale that goes far beyond what is humanly possible. The top uses for predictive AI technologies to protect sensitive data and systems are in network detection and response (NDR), threat detection, and cybercrime prevention.
Growing Network Vulnerability
As the COVID-19 pandemic increases the world’s digital dependency, businesses become more vulnerable to cyberattacks attempted every 39 seconds. Cyberattacks, data theft, and data fraud are among the top five global risks in the next 10 years.
Odds favor hackers. Worldwide network traffic growth makes data more widely accessible. Security teams must find and protect every possible weak point in massive systems. But hackers only need to find one vulnerability to breach a network.
Skilled worker shortage. A global shortage of over 40 million IT security workers makes it hard for businesses to stop the unending flow of cyberattacks. The exponentially greater power of predictive AI solves this problem.
Evolution of Predictive AI
Machine learning for network protection evolved in three distinct waves:
First wave. Humans create rules for supervised AI to follow. This predictive AI method collects network data and creates a historical baseline. Anomalies are detected when incoming data differs from the baseline. First wave AI can solve complex problems and is evolving, but it has flaws:
- It takes months for first wave AI to gather enough historical data to form a baseline.
- Fresh data produces false positives when measured only against historical data.
- A baseline of old data is useless against the evolving methods of hackers.
Second wave. Supervised and unsupervised machines create rules by using statistical methods that include regression, clustering, and classification. Those rules are used to make predictions. Although superior to first wave AI, the second wave still has disadvantages:
- Limited context. Second wave AI can’t detect anomalies when network conditions change. In a constantly evolving environment, they must create rule after rule for huge amounts of data.
- Weak reasoning. Machines learn only from the data they collect. Second wave AI can’t draw conclusions and make predictions through its own reasoning.
Third wave. Unsupervised—or self-supervised—machines learn by applying their own reasoning and analysis to changing situations. With this learned knowledge, third wave AI draws new conclusions and increases its own learning capacity.
How Predictive AI Protects Networks
To protect worldwide networks, security teams watch for anomalies in dataflow with NDR. Cybercriminals introduce viral code to vulnerable systems hidden in the massive transfer of data. As cybersecurity evolves, bad actors work hard to keep their cybercrime methods one step ahead. To avoid next-generation hacks and breaches, security teams and their forensic investigation methods must become even powerful.
First and second wave cybersecurity solutions that work with traditional Security Information and Event Management (SIEM) are flawed:
- Overpromise on analytics, but basic log storage, incremental analytics, and maintenance costs are massive.
- Flag tons of false positives because of their context limitations.
MixMode adds an AI layer to SIEM to increase efficiency and decrease data migration, redundancy, and latency.
The immense data overload companies currently face demands reliable and accurate protection against new attacks. Third wave AI-enabled security monitoring detects and surfaces threats in real time before they compromise your network.
A best-in-class AI identifies patterns and understands what normal traffic looks like in changing conditions. Without human tuning, self-supervised AI solutions learn over time to fix the problems that traditional solutions can’t solve. They identify and surface new deviations from the baseline, quickly find threats, and alert security personnel.
Only an evolving baseline of normal network behavior—built with self-supervised AI—can detect anomalies accurately. The ground-breaking MixMode cybersecurity platform detects threats in real time with a patented AI engine.
The only way to keep a company safe 24/7 is to alert users before attacks happen. Hackers execute zero-day attacks to exploit unknown vulnerabilities in real time. First and second wave network security tools are helpless against these attacks.
Only a third wave, unsupervised AI—MixMode—can detect and surface zero-day attacks in real time before catastrophic damage is done. MixMode gives you the power to fight back:
- AI-driven alerts on known vulnerabilities
- Best-in-class threat hunting tooling
- IP addresses of hackers before they attack
MixMode–the Logical Choice
The security provided by traditional logs and end-point detection toolsets only goes so far. MixMode steps in to fill the gap. Most cybersecurity solutions that claim to be AI are manual, rules-based tech that requires human intervention before AI initiates. MixMode brings security teams all over the world these unique capabilities:
- Creates and monitors an evolving baseline of your normal network behavior in only seven days.
- Traces the path of network attacks and reduces dwell time by sending actionable alerts in real time.
- Provides modern solutions that are orders of magnitude more effective—and less infrastructure intensive—than all other AI security platforms.
Learn more about MixMode’s self-supervised AI in our whitepaper, “How Predictive AI is Disrupting the Cybersecurity Industry.” | <urn:uuid:2ca2ce1e-0fd8-4721-9ba5-a071ecb1ff5b> | CC-MAIN-2022-40 | https://mixmode.ai/blog/what-is-predictive-ai-and-how-is-it-being-used-in-cybersecurity/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337853.66/warc/CC-MAIN-20221006155805-20221006185805-00356.warc.gz | en | 0.902271 | 1,124 | 3.375 | 3 |
ICAM (Identity, Credential and Access Management) is a key information security requirement for the US government. Whether you are in government or serve the government as a supplier, these requirements matter. You may already have an identity and access management program in place. However, that program may be fully aligned with ICAM expectations.
Before you invest in new systems or training, start with the fundamentals. Let’s dig into ICAM and what it requires from organizations.
Step 1: Know The ICAM Requirements
Managed by the US General Services Administration, ICAM is a US government program to guide organizations in effectively managing IT security.
What Is The Scope of ICAM?
While ICAM impacts technology, it is a mistake to view it exclusively as a technical standard. It has a much broader scope. According to federal guidance, “Identity, credential and access management (ICAM) comprises the tools, policies and systems that allow an organization to manage, monitor and secure access to protected resources.” Your technology (i.e. tools), policies and processes all need to work together to achieve ICAM success.
ICAM starts with a strong focus on managing identity information. This process is critical to ensure that changes, approvals and other transactions are approved by the right individuals. For example, you might use identity management to restrict approval for large invoice approvals to individuals with a certain level (e.g. senior managers or directors).
Key points for Identity management under ICAM:
● Protection of PII. Identity management systems often require PII (i.e. personally identifiable information). Such data must be thoroughly protected since it may enable fraud if it is disclosed.
● Lifecycle requirement: Identity information needs to be managed through the lifecycle. A “one and done” approach is not acceptable for managing identities.
A credential is a token controlled by a person. For example, credentials may include passwords and security key cards. These items must be strictly controlled and tracked to maintain ICAM compliance.
Key points for credentials management under ICAM:
● Credential Expiration. All credentials should have an expiration date and be managed accordingly.
● Credential Sponsorship. Every credential must be sponsored by an individual. For example, a credential for an analyst may be sponsored by a manager.
Access is related to the above principles, but it has its requirements as well. Specifically, access governs when and how individuals can access resources. For example, an intelligence agency would need extraordinary access controls to prevent disclosure of classified information.
Key points for access management under ICAM:
● Enable access. ICAM is more than data protection. ICAM also requires that organizations proactively enable information access so people can be productive at work. Therefore, ICAM has expectations that access is extended to facilitate productivity.
● Maintain Access Policy Controls. To align with ICAM, you need to define what a given access level provides to a user. For instance, you may prohibit most employees from modifying their salary levels in an HR system.
Step 2: Self-Assess Your Organization’s ICAM Status
Now you need to find out where your organization’s processes, policies and technology stand to ICAM. To cover your whole organization, we recommend giving yourself a score of 0-10 in each of the following areas.
● Identity. Measure your organization’s approach to managing identity information throughout the lifecycle.
● Credentials. Assess all of your credentials including digital credentials, hardware tokens and physical security items (e.g. badges and keys)
● Access. Evaluate how well your organization responds to changing access requirements. For example, have you carried out an access review to see if access privileges are adequately organized?
As you go through this self-assessment exercise, note specific systems, policies and users where there are problems. You will need to capture those details to make ICAM compliance improvements.
Tip: Remember to keep in mind that ICAM is also concerned with enabling access and productivity. Therefore, you should avoid limiting your self-assessment to security matters alone. Make sure you ask users about the work effort involved in using your current systems.
Step 3: Prioritize ICAM Compliance Gaps
From the step above, you will end up with a large document showing your maturity in terms of achieving ICAM. In this step, you need to make some difficult decisions. Segment the issues and gaps into two categories: quick wins and projects.
Quick wins will move you closer to ICAM compliance in less than thirty days. For example, you can update a company policy and start the approval process reasonably quickly.
Projects will require several months of effort, new tools and support to implement. You might find that access levels are not being monitored adequately as people change jobs in the company. If you rely on manual processes like a central spreadsheet, you need an access management software solution. That’s the best way to achieve consistency.
Step 4: Recommend ICAM Improvement Projects
Based on your analysis, it is time to recommend projects to your executives. If your organization has to become ICAM compliant, focus your efforts on the projects that will provide the most benefit. Specifically, a successful ICAM improvement project should cover the following areas:
Create and update policy documents in your organization to translate ICAM requirements to your context. You can reference ICAM documents, but make sure you translate these ideas so employees can easily understand them.
If you scored low on ICAM compliance during your self-assessment, your staff would probably need guidance to get up to speed. The new training should cover both technical topics (e.g. how to use an IT security chatbot) and security principles.
Make a business case for identity and access management software like a password management tool. Without specialized tools, it is difficult to achieve ICAM compliance consistently.
Why Get Started With ICAM Even If You Are Outside of Government
If you are in the US government, ICAM compliance is an immediate priority. What about everyone else? There is mounting concern about the increasing number of cyberattacks. As an IT security manager, you need to show that you are keeping up with industry best practices. By implementing ICAM, you are more likely to keep your organization safe. | <urn:uuid:a3e5ff72-67af-4187-bb63-fa68ea310edd> | CC-MAIN-2022-40 | https://www.avatier.com/blog/meeting-the-us-governments-icam-requirements/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030333455.97/warc/CC-MAIN-20220924182740-20220924212740-00556.warc.gz | en | 0.926894 | 1,313 | 2.796875 | 3 |
Cloud infrastructure has to do with the hardware and software components required to ensure proper implementation of a cloud computing model. Critical examples of what makes up this infrastructure include a network and virtualization software, storage, servers.
Before discussing what makes up cloud infrastructure, we would first have to define what cloud computing is.
Cloud computing is defined as a process through which computing power, e.g., RAM, Network Speed, CPU; is delivered as a service over a network as opposed to physically providing them to an individual’s location.
Common examples of such cloud computing systems are Azure, Amazon Web Services (AWS), IBM, Google Cloud
An excellent example of how cloud computing works can be depicted by you traveling by bus. Each passenger (alighting at different stop-points) is given a ticket which keeps them seated in a position until they reach their destinations. Cloud computing is quite like the bus, which takes different people (i.e., data) to different places (i.e., users), allowing each person to use its service at a minimal fixed cost.
Cloud computing has become essential in today’s world, as data storage has become one of the top priorities in each field. This is because lots of businesses spend hefty amounts getting and protecting their data, requiring a reliable IT support structure. Since most companies, e.g., small and medium scale businesses cannot afford in-house infrastructures, which cost a lot, cloud computing serves as the middle point. As a matter of fact, because of how efficient this form of data storage is, as well as the low cost of maintenance, big businesses are rapidly being attracted to it as well!
With an in-house IT server, lots of attention has to be paid to ensure there are no glitches in the system. Should there be any faults, you risk losing a lot. It is merely cost-effective to go with cloud computing and the infrastructure that comes with it.
Cloud computing offers three major types of services, and they are:
Depending on business requirements, one or more of these cloud computing offers are utilized by companies.
SaaS (Software as a Service)
Software, as a service has to do with a software distribution model whereby applications hosted by a service provider or vendor via the cloud, is made available through the same means.
This is becoming a trendy delivery model, as opposed to buying a software application and installing it on your computer as obtainable in the past. Using SaaS, you make use of the software as a subscriber, monthly.
Through this service, you get all of your regular duties done, such as sales, accounting, planning, and invoicing.
PaaS (Platform as a Service)
Using Platform as a service, developers can build services and applications, hosted by the cloud and accessible to users via the Internet.
Benefiting from PaaS requires constant updating and addition of new features.
Such benefits include being able to ensure adequate software support and management services, networking, storage, testing, and collaborations.
IaaS (Infrastructure as a Service)
IaaS is also a significant service model of cloud computing. Through Infrastructure as a Service, access is provided to computing resources over a virtualized environment, i.e., the cloud.
The infrastructure provided here includes virtual server space, network connections, bandwidth, IP addresses, and load balancers. Here, a pool of hardware resources is extracted out of several servers and subsequently delivered over several data centers. Hence, there is a sense of reliability to IaaS.
IaaS serves as a complete computing package. If small scale businesses are looking to cut out the cost on IT infrastructure, this is one proven, viable means of doing so. Every year, lots of cash would otherwise be put into purchasing and buying new components such as hard drives, network connections, external storage devices; etc. when utilizing IaaS, all of this is bypassed!
Without virtualization, cloud computing might be a scam. Virtualization has to do with apportioning single physical servers to multiple logical servers. As soon as the physical server is divided, each valid server can then act like a physical server, running independent operating system and applications.
Since virtualization is a critical part of cloud infrastructure, several popular companies provide this service to the vast number of people who need it. These services are both cost-effective and time respect.
Especially for software developers and testers, virtualization is pretty essential; giving developers a solid platform on which to write code, which can then run in several different environments and scenarios. They are also able to test the code.
The three significant purposes of virtualization are network virtualization, server virtualization, and storage virtualization.
Network virtualization refers to a method of combining available network resources by dividing the available bandwidth into channels, each of which is independent of the other channels, and each of which can be assigned to a particular server or device.
Storage virtualization deals with the pooling of physical storage from several network storage devices into a single storage device managed from a central console. This form of virtualization is commonly used in storage area networks.
As for server virtualization, it involves the masking of server resources such as processors, RAM, operating systems; from server users. This form of virtualization aims to ensure an increase in resource sharing while reducing the burden of computation on users.
Unlocking cloud infrastructure needs a steady input of virtualization; as it decouples software from hardware. This makes personal computers, for example, able to borrow extra memory from the hard disk through the use of virtual memory.
Cloud infrastructure is beyond helpful and has come to stay. If you would be utilizing cloud platforms, then you need to be on top of your knowledge game about the infrastructure you’d be using! | <urn:uuid:25161e7d-159a-4977-bf2c-fb29b78ba148> | CC-MAIN-2022-40 | https://www.colocationamerica.com/blog/what-is-cloud-infrastructure | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030333455.97/warc/CC-MAIN-20220924182740-20220924212740-00556.warc.gz | en | 0.950607 | 1,196 | 3.46875 | 3 |
Training ‘complex multi-layer’ neural networks is referred to as deep-learning as these multi-layer neural architectures interpose many neural processing layers between the input data and the predicted output results – hence the use of the word deep in the deep-learning catchphrase.
While the training procedure is computationally expensive, evaluating the resulting trained neural network is not, which explains why trained networks can be extremely valuable as they have the ability to very quickly perform complex, real-world pattern recognition tasks on a variety of low-power devices including security cameras, mobile phones, wearable technology. These architectures can also be implemented on FPGAs to process information quickly and economically in the data center on low-power devices, or as an alternative architecture on high-power FPGA devices.
The Intel Xeon Phi processor product family is but one part of Intel SSF that will bring machine-learning and HPC computing into the exascale era. Intel’s vision is to help create systems that converge HPC, Big Data, machine learning, and visualization workloads within a common framework that can run in the data center – from smaller workgroup clusters to the world’s largest supercomputers – or in the cloud. Intel SSF incorporates a host of innovative new technologies including Intel Omni-Path Architecture (Intel OPA), Intel Optane SSDs built on 3D XPoint technology, and new Intel Silicon Photonics – plus it incorporates Intel’s existing and upcoming compute and storage products, including Intel Xeon processors, Intel Xeon Phi processors, and Intel Enterprise Edition for Lustre* software.
Fueled by modern parallel computing technology, it is now possible to train very complex multi-layer neural network architectures on large data sets to an acceptable level of accuracy. These trained networks can perform complex pattern recognition tasks for real-world applications ranging from Internet image search to real-time runtimes in self-driving cars. The high-value, high accuracy recognition (sometimes better than human) trained models have the ability to be deployed nearly everywhere, which explains the recent resurgence in machine-learning, in particular in deep-learning neural networks.
Intel Xeon Phi
The new Intel processors, in particular the upcoming Intel Xeon Phi processor family (code name Knights Landing), promises to set new levels of training performance with multiple per core vector processing units, Intel AVX-512 long vector instructions, high-bandwidth MCDRAM to reduce memory bottlenecks, and Intel Omni-Path Architecture to even more tightly couple large numbers of distributed computational nodes.
Computational nodes based on the upcoming Intel Xeon Phi devices promise to accelerate both memory bandwidth and computationally limited machine learning algorithms, because these processors greatly increase floating-point performance while the on-package MCDRAM greatly increases memory bandwidth. In particular, the upcoming Intel Xeon Phi processor contains up to seventy two (72) processing cores where each core contains two AVX-512 vector processing units. The increased floating-point capability will benefit computationally intensive deep-learning neural network workloads.
With Knights Landing, the Intel Xeon Phi product family will feature both a bootable host processor and PCIe add-in card versions. While both products are binary-compatible with Intel Xeon processors, the bootable host processor will also function like Intel Xeon processors, running off-the shelf operating system, supporting platform memory (up to 384GB of DDR4), featuring integrated fabric support, using the same IT/management tools, and more.
Intel Xeon Processors
The recently announced Intel Xeon processors E5 v4 product family, based upon the “Broadwell” microarchitecture, is another component in the Intel SSF that can help meet the computational requirements of organizations utilizing deep learning. This processor family can deliver up to 47%1 more performance across a wide range of HPC codes. In particular, improvements to the microarchitecture improve the per-core floating-point performance – particularly for the floating-point multiply and FMA (Fused Multiply-Add) that dominate machine learning runtimes – as well as improve parallel, multi-core efficiency. For deployments, a 47% performance increase means far fewer machines or cloud instances need to be used to handle a large predictive workload such as classifying images or converting speech to text – which ultimately saves both time and money.
Figure 2: Performance on a variety of HPC applications* (Image courtesy Intel)
See the March 31, 2016 article, “How the New Intel Xeon Processors Benefit HPC Applications”, for more information about the floating-point and other thermal, memory interface and virtual memory improvements in these new Intel Xeon processors.
An exascale capable parallel mapping for machine learning
The following figure schematically shows an exascale capable massively parallel mapping for training neural networks. This mapping was initially devised by Farber in the 1980s for the SIMD-based (Single Instruction Multiple Data) CM-1 connection machine. Since then, that same mapping has ran on most supercomputer architectures and recently been used to achieve petaflop per second average sustained performance2 on both Intel Xeon Phi processor and GPU based leadership class supercomputers. It has been used to run at scale on supercomputers containing tens to hundreds of thousands of computational devices and has been shown to deliver TF/s (teraflop per second) performance per current generation Intel Xeon Phi coprocessors and other devices.
Figure 2: Massively Parallel Mapping – Click to see animation (Courtesy TechEnablement)
With this mapping, any numerical nonlinear optimization method that evaluates an objective function that returns an error value (as opposed to an error vector) can be used to adjust the weights of the neural network during the training process. The objective function can be parallelized across all the examples in the training set, which means it maps very efficiently to both vector and SIMD architectures. It also means that the runtime is dominated by the objective function as training to solve complex tasks requires large amounts of data. Each calculation of the partial errors runs independently, which means that this mapping scales extremely well across arbitrarily large numbers of computational devices (e.g. tens to hundreds of thousands of devices). The reduction operation used to calculate the overall error makes this a tightly coupled computation, which means that performance will be limited to that of the slowest computational node (shown in step 2) or by the communications network for the reduction (shown in step 3). It also means that the overall scaling is exascale capable due to the O(log(NumberOfNodes)) behavior of the reduction operation.
For more information see:
- Chapter 7, “Deep Learning and Numerical Optimization” in High Performance Parallelism Pearls.
- Dobbs, “Exceeding Supercomputer Performance with Intel Phi”.
Computational vs. memory bandwidth bottlenecks
The hardware characteristics of a computational node define which bottleneck will limit performance – specifically if the node will be computationally or memory bandwidth limited. A balanced hardware architecture like that of the Intel Xeon Phi processors will support many machine-learning algorithms and configurations.
The runtime behavior of the objective function (shown in step 2) dictates if training performance within a node will be floating-point arithmetic or memory bandwidth limited. Well implemented machine-learning packages structure the training data in memory so it can be read sequentially via streaming read operations. Current processors are so fast that they can process simple objective functions faster than the memory system can stream data. As a result, the processor stalls while waiting for data. Complex objective functions, especially those used for deep-learning, have a high computational latency (meaning they require more floating-point operations), which relieves much of the pressure on the memory subsystem. In addition, asynchronous prefetch operations can be used to hide the cost of accessing memory, so complex deep-learning objective functions tend to be limited by the floating-point capabilities of the hardware.
Computational nodes based on the new Intel Xeon Phi processors promise to accelerate both memory bandwidth and computationally limited machine learning objective functions, because computational nodes based on these processors greatly increase floating-point performance while on package MCDRAM greatly increases memory bandwidth3.
In particular, each upcoming Intel Xeon Phi processor contains up to seventy two (72) processing cores where each core contains two Intel AVX-512 vector processing units. The increased floating-point capability will benefit computationally intensive deep-learning neural network architectures. The large machine-learning data sets required for training on complex tasks will ensure that the longer Intel AVX-512 vector instructions will be of benefit.
The new Intel Xeon Phi processor product family will contain up to 16GB (gigabytes) of fast MCDRAM, a stacked memory which, along with hardware prefetch and out-of-order execution capabilities, will speed memory bandwidth limited machine learning and ensure that the vector units remain fully utilized. Further, this on-package memory can by backed by up to six channels of DDR4 memory, with a maximum capacity of 384GB. Providing a platform with the capacity of DDR memory and the speed of on package memory.
Convergence and numerical noise
The training of machine-learning algorithms is something of an art – especially when training the most commercially useful nonlinear machine-learning objective functions. Effectively, the processor has to iteratively work towards the solution to a non-linear optimization problem. Floating-point arithmetic is only an approximation, which means that each floating-point arithmetic operation introduces some inaccuracies in the calculation, which is also referred to as numerical noise. This numerical noise, in combination with limited floating-point precision can falsely indicate to the numerical optimization method that there is no path forward to a better, more accurate solution. In other words, the training process can get ‘trapped’ in a local minima and the resulting trained machine-learning algorithm may perform its task poorly and provide badly classified Internet search results or dangerous behavior in a self-driving car.
For complex deep-learning tasks, the training process is so computationally intensive that many projects never stop the training process, but rather use snapshots of the trained model parameters while the training proceeds 24/7 non-stop. Validation efforts are used to check to see if the latest snapshot of the trained network performs better on the desired task. If need be, the training process can then be restarted with additional data to help correct for errors. Google uses this process when training the deep-learning neural networks used in their self-driving cars 4.
Load balancing across distributed clusters
Large computational clusters can be used to speed training and dramatically increase the usable training set size. Both the ORNL Titan and TACC Stampede leadership class supercomputers are able to sustain petaflop per second performance on machine-learning algorithms6. When running in a distributed environment, it is possible to load-balance the data across the computational nodes to achieve the greatest number of training iterations per unit time. The basic idea is to choose a minimum size of the per-node data set (shown in step 2) to minimize the per node runtime while fully utilizing the parallel capabilities of the node so no computational resources are wasted. In this way, the training process can be tuned to a computational cluster to deliver the greatest number of training iterations per unit time without a loss of precision or wasting any computational resources.
A challenge with utilizing multiple TF/s computational nodes like the Intel Xeon Phi processor family is that the training process can become bottlenecked by the reduction operation because the nodes are so fast. The reduction operation is not particularly data intensive, with each result being a single floating-point number. This means that network latency, rather than network bandwidth, limit the performance of the reduction operation when the node processing time is less than the small message network latency. Intel OPA specifications are exciting for machine-learning applications as they promise to speed distributed reductions through: (a) a 4.6x improvement in small message throughput over the previous generation fabric technology7, (b) a 65ns decrease in switch latency (think how all those latencies add up across all the switches in a big network), and (c) some of the new Intel Xeon Phi family of processors will incorporate an on-chip Intel OPA interface which may help to reduce latency even further.
From a bandwidth perspective, Intel OPA also promises a 100 Gb/s bandwidth, which will greatly help speed the broadcast of millions of deep-learning network parameters to all the nodes in the computational cluster plus minimize startup time when loading large training data sets. In particular, we look forward to seeing the performance of Lustre over Intel OPA for large computational clusters, which means very large training runs can be started/restarted with little overhead.
Peak performance and power consumption
Machine-learning algorithms are heavily dependent on the fused multiply-add (FMA) performance to perform dot products. In fact, linear neural networks such as those that perform a PCA (Principle Components Analysis) are almost exclusively composed of FMA operations. One example can be found in the PCA teaching code in the farbopt github repository. Thus any optimizations that can increase the performance of the FMA instruction will benefit machine-learning algorithms be they on a CPU, GPU, or coprocessor.
These FMA dominated linear networks are of particular interest as they can show how close actual code can come to achieving peak theoretical performance on a device, as the FMA instruction is counted as two floating-point operations per instruction. These FMA dominated codes can also highlight bottlenecks within the processor. For example, GPU performance tends to fall off rapidly once the internal register file is exhausted, because register memory is the only memory fast enough to support peak performance. As a result, register file limitations can be a performance issue when training large, complex deep-learning neural networks. It will be interesting to see how performance is affected on Intel Xeon Phi processors as the cores transition from running mainly out of the L1 to a combination of the L1 and L2 caches to finally having to utilize MCDRAM memory as the deep-learning neural network architecture size increases.
Of course heat generation and power consumption are also critical metrics to consider – especially when evaluating a hardware platform that will be training machine-learning algorithms in a 24/7 environment. At the moment, both the current generation Intel Xeon Phi coprocessors and GPUs deliver multi-teraflop per second performance in a PCIe bus form factor. It will be interesting to measure the flop per watt ratio of the new Intel Xeon Phi processors as they run near peak performance when training both linear and nonlinear neural networks.
In the next couple of months, TechEnablement will do a deep dive on each of the Intel SSF components to explore their application to machine learning and to help the HPC community identify the right combinations of technology for their HPC applications.
1 Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more complete information visit http://www.intel.com/performance. Results based on Intel internal measurements as of February 29, 2016.
Rob Farber is a global technology consultant and author with an extensive background in HPC and a long history of working with national labs and corporations engaged in both HPC and enterprise computing. He can be reached at firstname.lastname@example.org. | <urn:uuid:c36a51e7-e110-4400-8f3a-abfbe2bf4ca8> | CC-MAIN-2022-40 | https://www.nextplatform.com/2016/04/14/boosting-deep-learning-intel-scalable-system-framework/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335004.95/warc/CC-MAIN-20220927100008-20220927130008-00556.warc.gz | en | 0.909741 | 3,228 | 2.984375 | 3 |
Cloud Computing Basic Cheat Sheet
Cloud computing models vary: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Manage your cloud computing service level via the surrounding management layer.
- Infrastructure as a Service (IaaS). The IaaS layer offers storage and compute resources that developers and IT organizations can use to deliver business solutions.
- Platform as a Service (PaaS). The PaaS layer offers black-box services with which developers can build applications on top of the compute infrastructure. This might include developer tools that are offered as a service to build services, or data access and database services, or billing services.
- Software as a Service (SaaS). In the SaaS layer, the service provider hosts the software so you don’t need to install it, manage it, or buy hardware for it. All you have to do is connect and use it. SaaS Examples include customer relationship management as a service.
Deploying Public, Private, or hybrid clouds
Cloud Computing happens on a public cloud, private cloud, or hybrid cloud. Governance and security are crucial to computing on the cloud, whether the cloud is in your company’s firewall or not.
- Public clouds are virtualized data centers outside of your company’s firewall. Generally, a service provider makes resources available to companies, on demand, over the public Internet.
- Private clouds are virtualized cloud data centers inside your company’s firewall. It may also be a private space dedicated to your company within a cloud provider’s data center.
- Hybrid clouds combine aspects of both public and private clouds.
Cloud Computing Characteristics
Cloud computing requires searching for a cloud provider. Whether your cloud is public, private, or hybrid, look for elasticity, scalability, provisioning, standardization, and billed usage:
- Elasticity and scalability. The cloud is elastic, meaning that resource allocation can get bigger or smaller depending on demand. Elasticity enables scalability, which means that the cloud can scale upward for peak demand and downward for lighter demand. Scalability also means that an application can scale when adding users and when application requirements change.
- Self-service provisioning. Cloud customers can provision cloud services without going through a lengthy process. You request an amount of computing, storage, software, process, or more from the service provider. After you use these resources, they can be automatically deprovisioned.
- Standardized interfaces. Cloud services should have standardized APIs, which provide instructions on how two application or data sources can communicate with each other. A standardized interface lets the customer more easily link cloud services together.
- Billing and service usage metering. You can be billed for resources as you use them. This pay-as-you-go model means usage is metered and you pay only for what you consume.
Cloud Computing Issues
Cloud computing issues span models (IaaS, PaaS, or SaaS) and types (public, private, or hybrid). Computing on the cloud requires vigilance about security, manageability, standards, governance, and compliance:
- Cloud security. The same security principles that apply to on-site computing apply to cloud computing security.
- Identity management. Managing personal identity information so that access to computer resources, applications, data, and services is controlled properly.
- Detection and forensics. Separating legitimate from illegitimate activity.
- Encryption. Coding to protect your information assets.
- Cloud manageability. You need a consistent view across both On-Premises and cloud-based environments. This includes managing the assets provisioning as well as the quality of service (QOS) you’re receiving from your service provider.
- Cloud standards. A standard is an agreed-upon approach for doing something. Cloud standards ensure interoperability, so you can take tools, applications, virtual images, and more, and use them in another cloud environment without having to do any rework. Portability lets you take one application or Instance running on one vendor’s implementation and deploy it on another vendor’s implementation.
- Cloud governance and compliance. Governance defines who’s responsible for what and the policies and procedures that your people or groups need to follow. Cloud governance requires governing your own infrastructure as well as infrastructure that you don’t totally control. Cloud governance has two key components: understanding compliance and risk and business performance goals.
- Data in the cloud. Managing data in the cloud requires data security and privacy, including controls for moving data from point A to point B. It also includes managing data storage and the resources for large-scale data processing.
The ‘Cloud Syndicate’ is a mix of short term guest contributors, curated resources and syndication partners covering a variety of interesting technology related topics. Contact us for syndication details on how to connect your technology article or news feed to our syndication network. | <urn:uuid:9da03484-25e5-4b92-9430-0761e8ee3f4f> | CC-MAIN-2022-40 | https://cloudtweaks.com/2010/06/cloud-computing-for-dummies-basic-cheat-sheet/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335609.53/warc/CC-MAIN-20221001101652-20221001131652-00556.warc.gz | en | 0.905119 | 1,035 | 2.984375 | 3 |
Fiber optic patch cords are one of the simplest elements in any optical network, consisting of a piece of fiber optic cable with a connector on each end. Despite its simplicity, the Fiber Optic Patch Cord can have a strong effect on the overall performance of the network. The majority of problems in any network occur at the physical layer and many are related to the patch cord quality, reliability, and performance. Therefore, using patch cords that are more reliable helps reduce the chance of costly network downtime. This article mainy the patch cord reliability.
Network designers would prefer components with a history of proven long-term performance. However, since optical networking is a relatively new technology, there is no significant long-term data for many components. Therefore, designers must rely upon testing from the component manufacturer or supplier that can simulate this history and assure the quality and reliability over the life of the network. This paper discusses the importance of quality, reliability, and performance as they relate to industry standards and manufacturing practices. The performance of the patch cord is also studied using a “perfect patch cord” and polishing observations as tools to understand patch cord principles.
Patch cord reliability is guaranteed not only by using quality components and manufacturing processes and equipment, but also by adherence to a successful Quality Assurance program. While patch cords themselves are typically tested 100% for insertion loss and return loss, if applicable, there are many other factors that need to be monitored to insure the quality of the patch cord.
One of the most important factors is the epoxy. Epoxies typically have a limited shelf life and working life, or “pot life.” This information is readily available from the manufacturer. It is absolutely necessary that both of these criteria be verified and maintained during manufacture. Epoxy beyond its expiration date needs to be discarded. Chemical changes affecting the cured properties of the epoxy can occur after this date. This date can also be dependent on storage conditions, which need to be observed.
Most epoxies used in fiber optic terminations are two-part epoxies and, while they cure at elevated temperatures, preliminary cross-linking will begin upon mixing. Once this has started, the viscosity of the epoxy can begin to change, making application more difficult over time. The epoxy can become too thick to fill the ferrule properly and too viscous to enable a fiber to penetrate, causing fiber breakage.
Many of the tooling used in patch cord assembly also has periodic maintenance and a limited tool life. This includes all stripping, cleaving and crimping tools. Most stripping tools, whether they are hand tools or automated machines, can be damaged by the components of the cable, most notably the aramid yarn strength members. Buffer strippers will dull with prolonged usage, increasing the likelihood that they will not cleanly cut the buffer. This can lead to overstressing the fiber when the buffer is pulled off. When a cleaving tool wears out and a clean score is not made, it is almost impossible to detect during manufacturing. However, the result could be non-uniform fiber breakage during the cleave, which can result in either breaking or cracking the fiber below the ferrule endface. In this instance, the connector will have to be scrapped. Even crimp tools require periodic maintenance to insure the proper forces and dimensions are consistent. Crimp dies also have a tendency to accrue epoxy build-up, which can affect the crimping dimensions and potentially damage the connector.
The integrity of the incoming materials and manufacturing processes, once specified, needs to be adhered to all the appropriate guidelines and procedures. The importance of these materials not only has a strong influence on product reliability, but also on product performance.
Fiber optic patch cords are fiber optic cables used to attach one device to another for signal routing. It compresses in the entire electric network plank and room that wall plank and the flexibility cabinet needs, causes such the person who passes room merely considerably traditional FC,LC,ST and SC’s connection box in parts.Intelligently the bright and beautiful corporation adopts well-developed technique and installation, and carrying on scale manufacture, the produce performance is good, and the quality is steady dependable. Fiberstore manufactures fiber optic patch cables, fiber optic patch cords, and pigtails. There are LC, SC, ST, FC, E2000, SC/APC, E2000/APC, MU, VF45, MT-RJ, MPO/MTP, FC/APC, ST/APC, LC/APC, E2000, DIN, D4, SMA, Escon, FDDI, RoHS compliant, LSZH, Riser,Plenum, OFNR, OFNP, simplex, duplex, single mode, 9/125, SM, multimode, MM, 50/125, 62.5/125; armored fiber optic patch cords, OM4 patch cord, waterproof fiber optic patch cords, ribbon fiber optic cables and bunched fiber optic cables.
Related Article: Which Patch Cable Should I Choose for My Optical Transceiver? | <urn:uuid:232c1cbd-ff16-40b1-83ad-6f82dbd4fc22> | CC-MAIN-2022-40 | https://www.cables-solutions.com/category/fiber-optic-patch-cables/single-mode-fiber-optic-patch-cables/page/2 | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337339.70/warc/CC-MAIN-20221002181356-20221002211356-00556.warc.gz | en | 0.933203 | 1,048 | 2.75 | 3 |
In light of the news that online hate crime is set to be treated as seriously as ‘offline’ offences, under revised CPS guidelines, David Emm, Principal Security Researcher at Kaspersky Lab commented below.
David Emm, Principal Security Researcher at Kaspersky Lab:
“Technology offers protection but we cannot rely solely on it. By being informed and talking about our lives online, we will continue to raise awareness and understanding of the risks and threats and how to guard against them.”
Four simple and practical steps you can take to help you stay safe online are as follows:
- Don’t assume that someone is who they say they are. Remember that even a friend’s account may be hacked, in which case it could be a cybercriminal that’s sending you a message, or inviting you to click on a link.
- If you wouldn’t publish something on the front page of a daily newspaper, don’t post it online.
- Review your Facebook security settings carefully, ideally restricting all sections to be viewed/shared to ‘friends only’. Set limits to what applications can do and remove applications once you no longer wish to use them.
- Protect your computer using Internet security software and always install security updates to software on your computer. | <urn:uuid:f3c1d8fc-9f57-47b1-9b32-4ec48cf67d48> | CC-MAIN-2022-40 | https://informationsecuritybuzz.com/expert-comments/social-media-hate-crime-clampdown/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337855.83/warc/CC-MAIN-20221006191305-20221006221305-00556.warc.gz | en | 0.927273 | 274 | 2.921875 | 3 |
The technology industry is currently in the midst of an artificial intelligence (AI) renaissance. Initial work in this field fell something short of its longer term potential due to limitations in the technology platforms of the day, somewhere around the 1980s.
As such, the first age of AI was ignominiously relegated to movies where it powered talking cars, humanoid cyborgs and a selection of other fancifully imagined products.
The current reawakening of AI has been facilitated by advances in hardware from processing to memory to data storage; but also by our ability to now develop complex algorithmic structures capable of running on these new super-powered backbones.
As IT departments start working to apply AI-enablement to the enterprise software stacks, it is worth taking a step back and examining what is actually happening inside the synaptic connections that go to make our AI “brains” so smart.
By knowing more about the software structures being architected, developers can, in theory, more intelligently apply AI advancements to the applications that are engineered for tomorrow.
Key among the “tools” many AI developers will be learning now is TensorFlow. Built and open sourced by Google, TensorFlow is a symbolic mathematical library used to build AI intelligence in the Python programming language. TensorFlow can be (for example) used to build a “classifier” – that is, a visual image scanning component that can recognise a handwritten numerical digit in under 40 lines of code.
Describing the principles behind deep learning, Rajat Monga, engineering director for TensorFlow at the Google Brain division, says: “Deep learning is a branch of machine learning loosely inspired by how the brain itself works. We’re focused on making it easier for humans to use the devices around them and we think that making TensorFlow an open source tool helps and speeds that effort up.”
TensorFlow is used heavily in Google’s speech recognition systems, the latest Google photos product and, crucially, in the core search function. It is also used to provide the latest AI functionality extensions inside Gmail – many users may have noticed an increasing amount of auto-complete options in Gmail, a development known as Smart Compose.
The toolsets and libraries being developed in this area are focused on what is often referred to as “perceptual understanding”. This is the branch of AI model coding devoted to letting a computer-based image scanner pointed at a roadway directions sign know that it is looking at a signboard and not just letters on a wall. So applied context is key to this element of AI.
Scale is also key to many of these types of AI and machine learning libraries, so they need to be able to run on multiple CPUs, multiple GPUs and even multiple operating systems concurrently. TensorFlow is good at this and is a common attribute to much of the code discussed here.
“Most strong deep learning teams today use one of the more popular frameworks – and I’m talking about technologies like Tensorflow, Keras, PyTorch, MXNet or Caffe.
“These frameworks enable software engineers to build and train their algorithms and create the ‘brains’ inside AI,” explains Idan Bassuk, head of AI at Aidoc, a Tel Aviv-based specialist firm using AI to detect acute cases in radiology.
In addition to those mentioned, there are several categories of tools that enable deep learning engineers to actually “do” their work faster and more effectively. Examples include tools for automating DevOps-related tasks around deep learning (such as MissingLink.ai), tools for accelerating algorithm training (such as Uber's Horovod and Run.ai), and others, according to Bassuk.
The other big contenders
Microsoft’s work in this space comes in the shape of the Microsoft Cognitive Toolkit (the artist formerly known as CNTK). This library works to enhance the modularisation and maintenance of separating computation networks.
This toolkit can be used to build reinforcement learning (RL) functions for AI to grow cumulatively better over time. It can also be used to develop generative adversarial networks (GANs), a class of AI algorithms found in unsupervised machine learning.
IBM has a very visible hand in this space with its Watson brand. Despite the firm’s recent acquisition of Red Hat, the IBM approach is rather more proprietary than some, that is – the firm offers developers access to a collection of representational state transfer application programming interfaces (Rest APIs) and software development kits (SDKs) that use Watson cognitive computing to solve complex problems.
A selection of AI and deep learning tools
- Caffe: Caffe an open source framework for deep learning that supports various types of software architectures that were designed with image segmentation and image classification in mind.
- DeepLearning4J: DeepLearning4J is an open-source, distributed deep learning library for the JVM. The company claims it well-suited for training distributed deep learning networks and can process huge data without losing its pace.
- IBM Watson: IBM has positioned Watson as “deep learning for business”.
- Keras: Keras is an open-source neural network library written in Python.
- Microsoft Cognitive Toolkit - a deep learning framework developed by Microsoft Research. Microsoft Cognitive Toolkit describes neural networks as a series of computational steps via a directed graph.
- MLflow: A tool from Databricks to support machine learning experiments.
- MXNet: Apache MXNet is a scalable training and inference framework with a concise API for machine learning.
- PyBrain: An open-source, modular machine learning library.
- Scikit-Learn: Scikit-learn is an open-source machine learning framework for Python that is useful for data mining, data analysis, and data visualisation.
- Tensorflow: This is an open source library for high performance computation. It combines several machine learning and deep learning techniques to support applications like face and handwriting recognition.
- Theano: Theano is a Python library for defining, optimizing, manipulating, and evaluating mathematical expressions using a computer algebra system.
- Torch: Torch is an open-source framework for scientific computing that supports machine learning algorithms.
Facebook is also in the big brand group for AI and machine learning. The social networking company is (perhaps unsurprisingly) very keen to work on AI functions and is known for its PyTorch deep learning framework, which was open sourced at the start of 2018. PyTorch runs on Python and so is regarded to be a competitor to TensorFlow.
Facebook has also open sourced its Horizon Reinforcement Learning (RL) products this year. According to the developer team behind Horizon, “machine learning (ML) systems typically generate predictions, but then require engineers to transform these predictions into a policy (i.e. a strategy to take actions). RL, on the other hand, creates systems that make decisions, take actions and then adapt based on the feedback they receive.”
Other notable toolsets
Any overview of neural nodes in the AI brain would be remiss without mentioning a number of other key libraries and toolsets. Caffe is an open source framework for deep learning that can be used to build what are known as convolutional neural networks (CNN), typically always used for image classification. Caffe goes down well with some developers due to its support for various different types of software architectures.
DeepLearning4J is another useful tool for the AI developer toolbox. This is an open source distributed deep learning library for the Java Virtual Machine. For Python developers, there is Scikit, a machine learning framework used for tasks including data mining, data analysis and data visualisation.
There is also Theano, a Python library for defining and managing mathematical expressions, which enables developers to perform numerical operations involving multi-dimensional arrays for large computationally intensive calculations.
Read more about deep learning
- New tools help developers build better, smarter AI apps, as machine learning toolkits have progressed exponentially over the last few years.
- Machine learning and deep learning increasingly make their way into the enterprise. Assess which AI technology is right for you, and the public cloud services that support them.
In the real world (but still the AI world), we can see firms using a number of different toolsets, libraries and code methodologies in their developer function to attempt to build the machine intelligence they seek.
According to a Databricks CIO survey, 87% of organisations invest in an average of seven different machine learning tools – and this of course adds to the organisational complexity that is present around using this data.
Databricks has attempted to address part of this challenge by producing and open sourcing a project called MLflow. The goal with MLflow is to help manage machine learning experiments and put them into what effectively becomes a lifecycle. It also strives to make it easier to share project setups and get those models into production.
The company insists that if we want AI to be easier to adopt and evolve over time, we need more standardised approaches to managing the tools, data, libraries and workflows in one place. MLflow was released in alpha status in June 2018.
The neural road ahead
As these tools now develop, we are witnessing some common themes surfacing. Flexibility in these software functions often comes at the cost of either performance or ability to scale, or indeed both. If a toolset is tightly coupled to one language or deployment format, it is typically harder to reshape it bigger, wider, faster or fatter.
Over time, there is likely to be some consolidation of platforms or some wider community-driven migration to the most efficient, most powerful, most open, most intelligent and most “trainable” toolsets. | <urn:uuid:89dc8d7d-b2f3-40e1-9575-1b0e19e669c5> | CC-MAIN-2022-40 | https://www.computerweekly.com/news/252452432/An-overview-of-deep-learning-tools | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337855.83/warc/CC-MAIN-20221006191305-20221006221305-00556.warc.gz | en | 0.932033 | 2,038 | 2.984375 | 3 |
Education now looks completely different from anything we’ve ever experienced. Studies find that nearly 94% of students are learning from home in some capacity, which means there’s a massive push for creating spaces at home that will benefit them. Whether you’ve ever taught or not, this work can be a lot to take on! Here are some tips for creating the best at-home classroom for your child so that they can get the most out of this time.
Best Tips For Setting Up An At-Home Classroom
Create a Dedicated Space
All humans focus better when we’ve set clear paths and patterns for ourselves. With kids, especially, it’s important to create dedicated spaces in your home for studying. This plan doesn’t mean giving up an entire room or letting them have the couch for twelve hours a day but create a space that will instantly make them want to start studying when they sit down. You can partition this area off with curtains if you wish to, to make a study cubicle, or leave it as open and airy as you like. Use this space for studying, completing homework, and attending virtual school. You can even make the space fun by playing learning games like Scrabble or Boggle, and if you get stuck, try an anagram solver! The most important thing to do is to make sure your child knows what space is for.
Choose the Right Technology
Technology requirements vary depending on age and grade; however, it is certain that all children need a good laptop to attend class, participate in discussions, and complete homework assignments. Be sure to check with teachers and other parents to ensure your student is set up for success.
Bring Some Life In
Greenery offers a lot more than we give it credit for! Please help your child take an interest in keeping something alive and well, and let them pick a plant to take care of. You should give them basic guidelines on size, and be careful if you have pets to avoid plants that may be toxic. Live plants reduce stress, increase creativity, and help give your child a sense of purpose if they help clean up after the plant and water it.
Don’t Criticize Wrong Answers.
Incorrect answers are as much a part of learning as correct answers are. Unfortunately, for most students, a wrong answer means admonishment or shaming. There’s nothing product in that. If your child gets a problem wrong, acknowledge it and then work with them to get the correct answer. Be patient, understanding, and help them see why the right answer is correct. This behavior will teach your child how to handle failure and how to find correct answers on their own.
Help Them Understand Reliable Sources
The internet is a vast and uncontrollable place. Although we may think we can recognize if a site is reliable or not, unfortunately, it’s easy to get duped into looking at lousy information. Help your child understand which websites are useful for learning and which are opinion based. Unfortunately, false information is running rampant online, so it’s your job to help your child spot when there’s information they can use.
Steady Protein Snacks To Keep Them Driven
Although kids have more of a sweet tooth than adults do, on average, the go-to snacks throughout your child’s day should be protein-based. Start your kids’ day with some eggs, toast, and fruit, and then throughout the day, keep to a protein like a peanut butter or jerky. Protein helps keep us focused for longer while also pushing aside the urge to snack. Just be sure that you’re even letting your child drink a lot of water, and you’ll avoid the highs and lows that sugar consumption can impart.
Let Them Be Comfortable
Although we’ve all heard about the studies where people work more efficiently when they’re uncomfortable, there’s no need to inflict that on your child. Create a comfortable and safe space for your child to explore and learn. Find the perfect seating that will make them happy without letting them sleep, and work to light the room softly. A comfortable and nurturing space for your child will give them the freedom to think only about their work, instead of focusing on an uncomfortable couch or straining eyes in too-bright light.
Create Safe Online Spaces
As much as being safe fact-checking online is essential, your child’s all together, safety online is vital. As a society, we’ve moved towards accepting the internet as a significant part of our lives, and for many, that makes us far too easy to trust strangers. Teach your children the importance of withholding personal information online. This talk could mean talking to them about privacy and security, but emotional security should also be discussed. You don’t want anything wrong happening to your kid, and unfortunately, the internet can be a portal to the worst of humanity. Help them stay on the better side of things.
Exercise Still Matters
Exercise is paramount when it comes to brain development. Not only do the endorphins from exercise help keep the mind sharp, but they also will help your child keep in high spirits regardless of what they’re learning about. The best idea for kids is at least half an hour of active play a day and three one-hour sessions a week. Most children can easily reach this, but if you notice your child is falling behind or is in a souring mood, take the time to exercise with them! You can go biking, play basketball, or even swim if you have a pool, remember to have fun with them.
Set Goals, Display Them
Make achievable goals with your child! This goal could mean aiming for a specific grade, or it could mean that you reward them when they reach a massive milestone of work completed. When you’ve made these goals, write them on a board, or create a decoration! Seeing the goals every day will help inspire your child and give them something tangible.
Kristina is a stay-at-home blogger. After having kids, she began sharing some of my tips and tricks with people around her community. Now, she writes full articles on lifestyle, family, and home design to help people all over the internet. | <urn:uuid:c028017b-7c7a-468d-b072-f51b9428d5b6> | CC-MAIN-2022-40 | https://defendingdigital.com/tips-for-setting-up-an-at-home-classroom/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030333541.98/warc/CC-MAIN-20220924213650-20220925003650-00756.warc.gz | en | 0.95098 | 1,293 | 2.921875 | 3 |
Do you remember where the term “virus” came from? Yes, I’m talking about biological viruses, after which IT security specialists named the computer programs that insert their own code into other objects to reproduce and propagate themselves.
It is very likely that soon this information technology term will regain its original meaning — researchers from Microsoft and the University of Washington have marked a new milestone in data storage by writing approximately 200MB of data in the form of a synthetic DNA.
You may ask: What’s the connection with biological viruses? The analogy is pretty direct — viruses insert their genetic code into the DNA of infected organisms, causing the DNA to reproduce the viruses instead of synthesizing the right proteins, which are vital.
The most aggressive viruses disrupt normal physiological processes to such an extreme extent that it leads to the death of the cells and, in the end — of the whole organism. Similarly, the most aggressive malware may render the infected information system absolutely useless, or “dead.”
Therefore, now that humankind has begun writing information in the form of the DNA, it may be worth starting to worry about protecting this data at the “hardware level.” But first, let me give you an overview of how this “hardware” works.
DNA, which stands for deoxyribonucleic acid, is the largest molecule in our organism, and a carrier of genetic information. The closest IT analogue is the boot image, which enables the computer to start up and load the operating system. In most cases (with some exceptions I won’t touch in this post), after the operating system has been loaded into memory, the computer launches the executable modules required to support itself and perform the work it’s programmed to do. In the same manner, living cells in most cases use DNA to produce the “executables” — RNA (ribonucleic acids) sequences, which handle protein synthesis to sustain the organism and perform its functions.
All characteristics of the organism, from eye and hair color to any hereditary disorders, are stored in the DNA. They are encoded in a sequence of nucleotides — molecular blocks containing (for most known organisms) only four varieties of nitrogenous bases: adenine, guanine, thymine, and cytosine. These can be called “biological bits.” As you can see, mother nature has used a quaternary numeral system to encode genetic information, unlike human-made computers, which use binary code.
It’s worth mentioning that DNA has a built-in code correction function — most known DNA has two strands of nucleotides, wrapped one around another
like a twisted-pair wire in a double helix.
These two strands are attached one to another with hydrogen bonds that form only between strictly defined pairs of nucleotides — when they complement each other. This ensures that information encoded into a given sequence of nucleotides in one strand corresponds to a similar sequence of complementary nucleotides in the second strand. That’s how this code-correction mechanism works — when decoded or copied, the first DNA strand is used as a source of data and the second is used as a control sequence. This indicates if a sequence of nucleotides, coding some genetic characteristic, has been damaged in one of the strands.
In addition, genetic characteristics are encoded into nucleotide sequences using redundant encoding algorithms. To explain how it works in the simplest case — imagine that every hereditary characteristic, written as a sequence of nucleotides, is accompanied by a checksum.
The sequences of nucleotides coding genetic characteristics, or genes, have been studied extensively in the 50 years since the discovery of DNA. Today you can have your DNA read in many labs or even online — via 23andme or similar services.
How scientists read DNA
Through the past few centuries, scientists have developed methods to determine the structure of minuscule objects, such as X-ray structure analysis, mass spectrometry, and a family of spectroscopy methods. They work quite well for molecules comprising two, three, or four atoms, but understanding the experimental results for larger molecules is much more complicated. The more atoms in the molecule, the harder it is to understand its structure.
Keep in mind that DNA is considered the largest molecule for a good reason: DNA from a haploid human cell contains about 3 billion pairs of bases. The molecular mass of a DNA is a few orders of magnitude higher than the molecular mass of the largest known protein.
In short, it’s a huge heap of atoms, so deciphering experimental data obtained with classical methods, even with today’s supercomputers, can easily take months or even years.
But scientists have come up with a sequencing method that rapidly accelerates the process. The main idea behind it: split the long sequence of bases into many shorter fragments that can be analyzed in parallel.
To do this, biologists use molecular machines: special proteins (enzymes) called polymerases. The core function of these proteins is to copy the DNA by running along the strand and building a replica from bases.
But we don’t need a complete copy of the DNA; instead, we want to split it into fragments, and we do that by adding the so-called primers and markers — compounds that tell the polymerase where to start and where to stop the cloning process, respectively.
Primers contain a given sequence of nucleotides that can attach itself to a DNA strand at a place where it finds a corresponding sequence of complementary bases. Polymerase finds the primer and starts cloning the sequence, taking the building blocks from the solution. Like every living process, all of this happens in a liquid form. Polymerase clones the sequence until it encounters a marker: a modified nucleotide that ends the process of building the strand further.
There is a problem, however. The polymerase, DNA strand, primers, markers, and our building blocks, all are dispersed in the solution. It’s therefore impossible to define the exact location where polymerase will start. We can define only the sequences from which and to which we’re going to copy.
Continuing to the IT analogy, we can illustrate it in the following manner. Imagine that our DNA is a combination of bits: 1101100001010111010010111. If we use 0000 as a primer and 11 as a marker, we will get the following set of fragments, placed in the order of decreasing probability:
0000101011, 00001010111, 0000101011101001011, 00001010111010010111.
Using different primers and markers, we will go through all of the possible shorter sequences, and then infer the longer sequence based on the knowledge of what it is composed of.
That may sound counterintuitive and complicated, but it works. In fact, because we have multiple processes in parallel, this method reaches quite a good speed. That is, a few hours compared with months or years — not very fast from IT perspective, though.
— Eugene Kaspersky (@e_kaspersky) August 24, 2016
DNA and random access
After learning how to read DNA, scientists learned how to synthesize sequences of nucleotides. The Microsoft researchers were not the first to try writing information in the form of artificial DNA. A few years ago, researchers from EMBL-EBI were able to encode 739 kilobytes.
Two things make Microsoft’s work a breakthrough. First, the researchers have greatly increased the stored data volume, to 200MB. That’s not too far from the 750MB of data that is contained in every strand of human DNA.
However, what is really new here is that they have proposed a way of reading part of the DNA, approximately 100 bases (bio-bits) long, in each sequencing operation.
The researchers were able to achieve that by using pairs of primers and markers that enable them to read a certain set of nucleotides with a defined offset from the beginning of the strand. It’s not exactly the random access to a single bit, but the technology is close — block memory access.
Researchers believe that the main niche for such DNA memory could be high-density long-term memory modules. It definitely makes sense: the best known samples of flash memory provide a density of ~1016 bits per cubic centimeter, whereas the estimated density for DNA memory is three orders of magnitude higher: ~1019 bits per cubic centimeter.
At the same time, DNA is quite a stable molecule. Coupled with built-in redundant coding and error-correction schemes, data on it would remain readable years or even centuries after it being written.
Back to viruses
But what does it all mean from an information security standpoint? It means that the integrity of information stored in such a way may be threatened by organisms that have specialized in data corruption for billions of years — viruses.
We’re unlikely to see a boom of genetically modified viruses created to hunt coded synthetic DNA. It will simply be easier — for a long time — to modify data and insert malicious code when the data is digital, before it’s written to DNA.
But it’s an open question, how to protect such data from corruption by existing viruses. For example, polymerase will gladly replicate any DNA in the solution: for example, the DNA of the common flu virus.
So it may be worth noting if anyone was sneezing or coughing while you were writing an important file… | <urn:uuid:d80740bd-9926-4076-aa73-3aec504a293f> | CC-MAIN-2022-40 | https://www.kaspersky.com/blog/dna-storage/13563/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335286.15/warc/CC-MAIN-20220928212030-20220929002030-00756.warc.gz | en | 0.930392 | 1,983 | 3.5 | 4 |
HIPAA Security Rule: What are Physical Safeguards?
Within the HIPAA Security, the second rule that was passed as part of the HIPAA legislation back in early 2005. Alongside a few other safeguards, the Security Rule mandates compliance with certain Physical Safeguards that are intended to ensure the protection of electronic protected health information (ePHI) when it is held in actual, physical form. Now that most organizations handle PHI in a mostly digital format, people may have neglected the importance of paying attention to the physical security of this information. We’ll go through everything that you need to know about Physical Safeguards including what they are, what policies regulate their security & best practices for protecting them.
HIPAA Security Rule Overview
The HIPAA Security Rule requires three kinds of safeguards that organizations must implement: administrative, physical, and technical safeguards. Today we’ll focus on technical safeguards that outline the protections that organizations need to be taking to protect electronic protected health information (ePHI).
Since cybersecurity is a hot topic in the world of HIPAA and the health industry as a whole, that tends to be the aspect of information security that organizations focus on. However, physical security measures are just as important as those cybersecurity measures. Luckily, the HHS has set out clear guidelines and standards that are mandated to be in place for these organizations to prevent any unnecessary risk to the physical copies of PHI.
What are Physical Safeguards?
According to the text of the HIPAA Security Rule, physical safeguards are defined as “the physical measures, policies, and procedures to protect a covered entity’s electronic information systems and related buildings and equipment, from natural and environmental hazards, and unauthorized intrusion.” In terms of evaluating and implementing the proper physical safeguards, it is key that an organization thinks through every potential way for PHI to be accessed physically through their operations.
There are four main physical safeguards that companies should plan for and operate according to. Just as we saw with the Technical Safeguards piece of the Security Rule, some of the standards are considered “necessary” while others are “addressable”. What HIPAA means by an addressable standard is that healthcare organizations should use these security measures and apply them reasonably and appropriately to their specific technologies and company elements. It is important to remember that the addressable safeguards are not optional but instead are customizable by the organization.
Facility Access Controls
The first of these safeguards, facility access controls, set the policies and procedures that limit access to the actual facilities that contain the servers, computers, or other places that hold ePHI. In addition to preventing unauthorized access to these facilities, the controls that are implemented must still allow for authorized access to occur. All four of the specific “facility access controls” are considered “addressable” standards.
- Contingency Operations: Create procedures and plans that can be used to allow facility access and emergency operations in the event of a natural disaster or another emergency.
- Facility Security Plan: This is the facility access standard we typically think of - introducing procedures to prevent unauthorized access, theft, or tampering of the facility or any devices.
- Access Control and Validation Procedures: Generate processes for limiting and controlling individual’s access facilities or software programs based on their position and need. This may include having a visitor access protocol as well.
- Maintenance Records: Maintain protocol for documenting all maintenance, repairs, or changes to the facility as it may relate to security. (ex: locks, doors, hardware, etc..)
Device and Media Controls
Beyond access to the physical facilities of an organization, covered entities and business associates must also control the devices and other mediums that access ePHI. The law defines the device and media controls related to the “removal of hardware and electronic media that contain electronic protected health information, into and out of a facility, and the movement of these items within the facility.” This can refer to hard drives, any transportable digital memory cards, tapes, or disks. Within device and media controls, there are four specific standards - two of these are specifically required and the other two are addressable according to the organization’s specifications.
- Disposal: Maintain procedures for the proper final disposal of ePHI or the devices and hardware that it is stored on.
- Media Re-use: Implement protocols for removing ePHI from any form of media before that media is available for re-use.
- Data Backup and Storage: Create an exact backup copy of ePHI that is separately easily retrievable before ePHI containing equipment is moved.
- Accountability: Keep a clear record of all movements of media or hardware, including location and person in possession.
The next standard revolves around the definition of a workstation as being “an electronic device, for example, a laptop or desktop computer, or any other device that performs similar functions, and electronic media stored in its immediate environment.” Organizations will need to run an analysis of their operations to determine all of the devices that would qualify a workstation for them. Then they must take the necessary steps to then place physical safeguards on each and every workstation in order to prevent unauthorized access to these locations. Both of the standards mentioned underneath workstation security are required, although the recent increase in remote working can present additional challenges.
- Workstation Security: Implement safeguards for all workstations that allow access to ePHI to the correct users but restrict access to all potential unauthorized users.
- Workstation Use: Specify the authorized functions that a certain device is authorized to perform and the websites or actions that can be accessed by users on these organization-owned devices. Since unauthorized use of these workstations can present additional risks, companies must implement this standard.
Each of these standards, specified by the HHS as the Physical Safeguards under the HIPAA Security Rule, are intended to set physical measures and policies to protect Electronic Protected Health Information in all buildings, equipment, and digital forms. When implemented correctly and completely, these standards should protect covered entities and business associates from unauthorized access and data loss in the event of a disaster. More information about each of these standards and implementation specifications can be found in this HHS guide. | <urn:uuid:33d80f73-bfe1-44e7-a432-ff9fefc76339> | CC-MAIN-2022-40 | https://www.accountablehq.com/post/breaking-down-physical-safeguards | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337631.84/warc/CC-MAIN-20221005140739-20221005170739-00756.warc.gz | en | 0.935493 | 1,300 | 2.890625 | 3 |
One of the problems with relying on a cellular phone as the sole source of voice connectivity is spotty coverage indoors and underground. One solution for small buildings is femtocells, small indoor networks that provide better indoor coverage for cellular phones. According to a story on Reuters, ip.access, a UK-based company, says that femtocells will begin hitting the market in greater numbers beginning next year, giving cellular providers a counterweight to dual-mode cellular/WiFi phones and extending the reach of cellular carriers' 3G networks.
Femtocells basically act as small cellular base stations, providing better coverage for both voice and data applications. They can easily integrate with 3G networks, meaning that EVDO and other wireless broadband users will be able to take full advantage of the services in areas where coverage would otherwise be spotty.
Airports and other large buildings currently use microcells to boost cellular coverage, but those are more expensive to deploy than femtocells; they're overkill for houses and other small buildings.
ABI Research thinks that femtocells are poised to take off in the next few years, with 102 million people using over 32 million femtocell access points by 2011. "From a technological standpoint, their better in-building coverage for technologies such as WCDMA and HSDPA is an incredibly important aspect of service delivery," notes ABI Research principal analyst Stuart Carlaw. "On a conceptual basis, femtocells allow carriers to price cellular data services in the home aggressively, with the ultimate goal of shaping consumer behavior."
Whether femtocells have the kind of rosy future envisioned by proponents—at least for home use—remains to be seen. T-Mobile is bringing a dual-mode UMA handset to market this summer, and the phone will be able to transition seamlessly from cellular to WiFi networks, and users will be able to make and receive VoIP calls over an 802.11b/g/n network if there's no cellular signal available or if they want to hoard their minutes. WiFi is nearly ubiquitous, and if dual-mode cellular handsets—or even Skype handsets like the iPhone CIT400—become more popular, it could drastically reduce the demand for femtocells in the home.
Still, WiFi is sometimes locked down, and microcells are expensive. Femtocells will reportedly cost in the neighborhood of $200, and that could make them an inexpensive option for subways and other places where the only alternative would be repeaters or microcells. The ability of femtocells to carry 3G data is another plus. After all, who wouldn't want to surf the Internet while riding the subway? | <urn:uuid:901e5458-df22-4c48-9f09-c95499055a79> | CC-MAIN-2022-40 | https://arstechnica.com/gadgets/2007/05/femtocells-bring-3g-cellular-signals-indoors-and-underground/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334514.38/warc/CC-MAIN-20220925035541-20220925065541-00156.warc.gz | en | 0.943584 | 545 | 2.546875 | 3 |
Nearly 8.2 billion devices are at risk, globally, from remote attack vectors like device take over and man-in-the-middle (MITM), et al. According to researchers from Armis Labs, the Bluetooth vulnerability is on all devices running iOS, Windows, Android, and even Linux processors. Dubbed as BlueBorne, “as it spread through the air (airborne) and attacks devices via Bluetooth. Armis has also disclosed eight related zero-day vulnerabilities, four of which are classified as critical. BlueBorne allows attackers to take control of devices, access corporate data and networks, penetrate secure “air-gapped” networks, and spread malware laterally to adjacent devices. Armis reported these vulnerabilities to the responsible actors, and is working with them as patches are being identified and released,” suggests a statement released from Armis Labs.
The attack works similar to the recently discovered Broadcom Wi-Fi chip by Project Zero and Exodus giving attackers complete access and controls from the beginning. But unlike WiFi, Bluetooth offers a wider attacker surface and thus, contains a lot more vulnerabilities.
What’s worse is that the attack doesn’t require targeted devices to be paired, or even be discoverable. The attack vector subterfuges as a Bluetooth device and exploits weaknesses in the protocol to deploy malicious code. “The BlueBorne attack vector requires no user interaction, is compatible with all software versions, and does not require any preconditions or configurations aside of the Bluetooth is active. Unlike the common misconception, Bluetooth enabled devices are constantly searching for incoming connections from any devices, and not only those they have been paired with. This means a Bluetooth connection can be established without pairing the devices at all. This makes BlueBorne one of the broadest potential attacks found in recent years, and allows an attacker to strike completely undetected.”
iPhones devices running iOS 10 are immune to the attack vector. Microsoft released a patch to fix the bug for all the computers since Windows Vista which was vulnerable to “Bluetooth Pineapple”. Android devices prior to Kit Kat are still vulnerable. Google has issued a patch for Nougat and Marshmallow and has notified its partners.
“Current security measures, including endpoint protection, mobile data management, firewalls, and network security solution are not designed to identify these type of attacks, and related vulnerabilities and exploits, as their main focus is to block attacks that can spread via IP connections,” stated Armis Labs. “New solutions are needed to address the new airborne attack vector, especially those that make air gapping irrelevant. Additionally, there will need to be more attention and research as new protocols are using for consumers and businesses alike. With the large number of desktop, mobile, and IoT devices only increasing, it is critical we can ensure these types of vulnerabilities are not exploited.” | <urn:uuid:3f1e413a-3e14-418e-baaf-ef3e1f59476e> | CC-MAIN-2022-40 | https://cisomag.com/8-2-billion-devices-worldwide-risk-remote-attacks/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334871.54/warc/CC-MAIN-20220926113251-20220926143251-00156.warc.gz | en | 0.947634 | 593 | 2.53125 | 3 |
Software-Defined Networking (SDN) brings many innovation to the Traditional Networks. It provides this with newly defined architecture. So, what will sdn bring? What are these SDN features? These are:
• New architecture that seperate Control Plane and Data Plane,
• Central maintenance mechanism,
• Network devices responsible for only Forwarding,
• General purpose hardwares,
• Network Operating System,
• New Applications instead of some Protocols,
• New Protocols like Open Flow
• Reduce CAPEX and Opex Costs,
• Increased Reliability and Security,
• Better Troubleshooting,
• Fully Controlled Network.
Let’s check these SDN features one by one.
When we ask what will sdn bring, certainly the first answer will be new SDN architecture. First of all SDN uses a new architecture. This new architecture divides network into two as Control Plane and Data Plane. Control Plane is the controller and has the global view of the whole network. This plane is responsible for the management facilities.
Secondly, SDN provides a central maintenance mechanism that you can configure, manage and maintenance your network devices in data plane. The communication between this central mechanism and data plane is done over Open Flow interface with Open Flow protocol. This avoids human errors. SDN has a very dynamic and easy to manage mechanism. This is basically centralized management of multi vendor equipment.
This can be overcomed with Automation too. But, Automation of some parts of the network is not SDN. SDN is an end-to-end solution.
Additionally, in SDN, network devices only used for data plane. Control plane facilities are done above, at the central controller. So, network devices are used for forwarding activities only. | <urn:uuid:fd8a498f-214d-4180-9db9-b17c9906e463> | CC-MAIN-2022-40 | https://ipcisco.com/lesson/what-will-sdn-bring/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335469.40/warc/CC-MAIN-20220930113830-20220930143830-00156.warc.gz | en | 0.886074 | 366 | 2.65625 | 3 |
Distributed cloud is an emerging cloud model where an organization’s cloud strategy and deployment takes into consideration where underpinning infrastructure resources are physically located. Contrastingly, distributed cloud emerged from the original cloud concept that has abstracted away the notion of infrastructure location from the minds of cloud users. In practice, the distributed cloud still has abstracted the cloud idea away from the underlying infrastructure’s location. But now, cloud engineers are able to consider greater flexibility in utilizing infrastructure resources closer to where they are actually needed, in other terms, pushing these resources out to the edge where compute and storage are used and latency can be significantly reduced.
Edge sites are data centers closer to customers—“the edge” refers to the location where devices and local area networks interface with the internet. By placing resources near the edge, particularly where there are more customers and greater usage, CSPs can reduce latency and provide greater quality of service for their users.
By combining multicloud models with distributed cloud, and emphasizing pushing resources to the edge, the concept of substations has also emerged to encompass the idea that CSPs are making available something akin to “shared cloud zones.” These zones, strategically distributed by CSPs, enable companies to customize a distributed cloud deployment aligned with their needs, while importantly retaining the key cloud value proposition, where the CSP assumes infrastructure risk and promises uptime, innovation, and support.
Distributed Cloud Features
Distributed cloud systems offer the same storage features that other cloud solutions provide. Since distributed systems are technical strategies for improving availability, and consistency, they are less of an active concern for consumers who use the cloud to forget about IT in their day-to-day tasks. However, when entering into agreements where availability is critical, cloud consumers may want to ensure that their CSP offers the advantages of distributed cloud systems. Most distributed cloud storage systems have the following features:
Elasticity and Scalability — Elasticity refers to the ability to increase workload by adding or removing hardware, whereas scalability refers to the ability of a system to increase the workload on the currently available system. Elasticity and scalability are the key features in cloud-based systems.
Partitioning— Partitioning allows IT teams to logically divide storage devices, which in turn allows different file systems to be installed on different logical divisions. When many environments are needed, partitioning helps to facilitate a single set of hardware to operate multiple and different operating systems at the same time, another key feature of clouds that enable service to multiple clients with unique IT requirements.
Replication— Replication is an enabling feature for distributed systems. By replicating data across multiple clusters, more users can be served from wider regions. The basic challenge for cloud providers is ensuring replicated sets are consistent with each other so that all users are accessing relevant and timely information.
Fault Tolerance — Systems that are fault-tolerant still suffer errors and system outages but remain available despite issues. These systems use an array of strategies to ensure uptime, including replication, redundant hardware, and additional connectivity.
Distributed Cloud Benefits
The main benefit of distributed cloud is to bring processing and storage capacity closer to the end-user, or device. While this has the primary impact of reducing latency and building fault tolerance, it has also led to new technological innovations in combination with innovative technologies like the Internet of Things. The following benefits directly impact cloud consumers:
Improved Compliance — Data compliance and privacy remain heightened issues in the cloud space. The distributed cloud allows companies to isolate sensitive information, such as Personally Identifiable Information (PII) or Protected Health Information (PHI), onto servers in regions that comply with regulations, while other less sensitive and highly access data can remain on servers closer to users, even if they are in regions outside of compliance.
Increased Uptime — The distributed cloud is a redundancy strategy that improves service failovers, and creates highly dependable services. But, geo-replication brings with it security challenges and complexity in maintaining, deploying, and troubleshooting these systems.
Improved Delivery — For cloud providers, distributed cloud improves content delivery and ultimately the users’ experience for cloud consumers because resources are closer to where they are used.
Improved Scalability — Like public clouds, distributed clouds have the advantage of rapid scaling. With the ease of adding new virtual machines to a deployment, new resources can be provisioned on-demand.
How Distributed Cloud Works
Public cloud deployments allow consumers to offload the risks and costs of maintaining and operating their own IT infrastructure. Most cloud service providers will happily assume that risk under a pay-as-gomodel, provisioning only the required storage and compute resources the consumer needs and charging them for that amount. The CSP and consumer enter into a service level agreement (SLA) that establishes the quality of service that is expected. The responsibility then becomes the CSPs to deliver the agreed-upon quality of service, security, and compliance. For customers that have users in multiple locations, CSPs turn to distributed cloud technologies to fulfill their obligations.
The challenge is to deliver data and services from the cloud reliably and fast to global users. While cloud providers conceal how this is done to the consumer, to abstract away the hardware concerns, the premise is simple, to deliver services reliably and fast, then place a copy of those services and data near where they are being most used. In fact, make multiple copies and place them in multiple regions to serve those closest and build a level of fault tolerance through redundancy. These locations are called points of presence (PoPs), an access point or physical location where two devices or networks can communicate. For instance, an ISP line in a home is a PoP for the ISP and home network, and a cell tower is a PoP for the carrier service and a mobile phone. In the case of the CSP, a local or regional data substation is the PoP for local users of the cloud resources.
The net effect is to extend providers' reach, and make the cloud experience for all users like they were connected directly to the central system.
Difference Between Distributed Cloud And Cloud
Cloud can refer to many different types of deployments, however, they typically are abstracted and categorized by ownership and responsibility. A public cloud is one that is provided by a cloud service provider over the public Internet. It is exposed to all the connectivity and threats in that space. The CSP is responsible for maintaining the cloud infrastructure, and depending on the type of service provided—IaaS, PaaS, or SaaS—the cloud consumer is responsible for their part. A private cloud is owned and maintained by one organization and secured behind its firewall, limited to a particular group, or group within a group.
A distributed cloud is a cloud with the added consideration of where cloud infrastructure resources are situated geographically. While the cloud connotes infinite accessibility and availability physical limitations of technology cannot faithfully deliver on that promise. To overcome real-world limitations, like latency, CSPs and enterprises develop cloud substations, where resources can be added to a cloud fabric but the infrastructure is actually geographically closer to users. The cloud appears the same, but the underlying is more efficiently placed.
Distributed Cloud Storage
Distributed cloud and distributed cloud storage are nearly synonymous in functionality to cloud consumers. The cloud, today, is moving more into a distributed system to improve overall service delivery. One slight way to distinguish distributed cloud storage is to compare it to cloud computing. Though they operate on the same techniques and hardware, cloud computing distributes workload across a data center's servers to be more efficient and redundant, and distributed cloud storage distributes storage and workload across a network of systems, most likely geographically distant from each other, to be more efficient and redundant.
Distributed Cloud And Edge Computing
Edge computing is one of the latest concepts emerging in a cloud context. Though the term may be fresh, the technical idea is not, and pushing compute and storage resources closer to “the edge” of the network has always been a conceptual solution for solving latency. The edge refers to a portion of the distributed system, namely the location where data processing grants the least latency and bandwidth issues, but is not a technology in itself. For Google Distributed Cloud, they make use of the distinction by dividing their offerings into several types of edges where they can run:
Google’s network edge — A global network of sites that consumers can host their cloud.
Operator edge — Working with communication services providers to utilize 5G/LTE services as the edge network.
Customer edge — Supporting customer-owned edge or remote locations whether that be a store location, a plant floor, or branch office.
Customer data centers — Supporting customer-owned data centers and colocation facilities.
Depending on the paradigm, the edge can take many forms.
Distributed Cloud Use Cases
Distributed cloud has several practical use cases, each is intent on managing latency and bandwidth. The power of distributed systems to significantly reduce latency has enabled other technologies and changed how resources are delivered:
Edge and IoT Compute and Storage Capacity — The Internet of Things (IoT) itself is an edge, where data processing is performed by small appliances at the point of use. For instance, in manufacturing industries, line robots connected to edge computing can make quick decisions without needing to ping a central server for an answer. Self-driving cars are another application of edge computing—the safety implications of sending large amounts of sensor data to a central server while driving is too great. Combined with AI and machine learning, distributed systems and edge systems can work together to deliver low-latency services that otherwise, for many limiting reasons, could not.
Content Delivery Optimization — Streaming services are the poster child of content delivery networks (CDNs), and Netflix may arguably be the model. CDNs are collections of servers geographically distributed throughout the world providing content to users from the most available local servers. Netflix traffic volume and user-based reach were growing so much to keep pace they developed their own proprietary CDN called Open Connect. In a smart move to distribute content, Open Connect boxes (which look like Netflix red servers) are issued to partner ISPs in regions throughout the world. These Open Connect boxes connect with Netflix servers and download regionally popular content to serve local users.
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If you’re a cybersecurity professional, chances are that you are familiar with the National Institute for Standards and Technology Cybersecurity Framework (NIST CSF). An understanding of the NIST Cybersecurity Framework (CSF) standard is critical for any company seeking to conduct business with a US Government agency, and increasingly more private-sector entities – and organizations abroad – are leveraging the NIST CSF to build their cybersecurity programs.
So, to start with the basics, what is the NIST CSF?
The NIST CSF (Cybersecurity Framework) is a cybersecurity framework developed by the National Institute of Science and Technology (NIST) to help organizations understand and better manage their cyber risk. NIST CSF is utilized by thousands of organizations around the world, including public-sector and private-sector and non-profit entities.
About the NIST Cybersecurity Framework
More than just another set of rules and regulations, the NIST Cybersecurity Framework is a powerful toolset that helps organizations manage and deal with the threats to their data and networks. While it’s not technically a piece of technology, the NIST Cybersecurity Framework provides a lens through which to view real cybersecurity risk, as well as standards and other rules that can help businesses and organizations identify, protect, detect, respond to and recover from cybersecurity attacks.
Also known as the five core functions or capabilities of the NIST Cybersecurity Framework, these pillars of modern IT security were drafted by the National Institute of Science and Technology (NIST) in the hopes that a standardized approach will be able to help industries, organizations and companies better protect themselves against hacks, data breaches and other cybersecurity threats.
Considered a staple of modern-day cybersecurity, the NIST Cybersecurity Framework is often the foundational component of any cybersecurity program. In fact, cyber risk management software companies often look to the NIST Cybersecurity Framework first when consulting clients on their cybersecurity risk, and even long running cybersecurity programs can benefit from implementing the guidance set forth by the NIST Cybersecurity Framework. Not only does the framework help make sense of the various cybersecurity threats out in the wild, but it can also help act as a security management tool and a way to view cybersecurity threats by the entire organization.
Why Use the NIST Cybersecurity Framework?
According to cybersecurity risk management software providers and other IT security consultants, the NIST Cybersecurity Framework is an essential piece of the cybersecurity puzzle. With it, you’re able to monitor and stay ahead of unseen vulnerabilities and risks, as well as gaining the ability to develop a more keen understanding of the assets you have and the risk levels of each. If you worry about spending time and money on threats that never materialize or on initiatives that don’t really increase your real-world security, the NIST Cybersecurity Framework is for you.
Furthermore, if you’re unsure about where to apply your resources or how to address your cybersecurity risks, the NIST Cybersecurity Framework can help you answer those questions with a clear path to the right tools and implementations that you need to provide an adequate level of protection. For cybersecurity teams that struggle with ownership and a comprehensive accounting of historical and realtime threats, the NIST Cybersecurity Framework helps organizations finally get serious about their cybersecurity risk.
What are the core capabilities of the NIST CSF?
The framework is broken into five central capabilities: Identify, Protect, Detect, Respond, and Recover.
- Identify: Develop an organizational understanding to manage cybersecurity risk to systems, people, assets, data, and capabilities.
- Protect: Develop and implement appropriate safeguards to ensure delivery of critical services.
- Detect: Develop and implement appropriate activities to identify the occurrence of a cybersecurity event.
- Respond: Develop and implement appropriate activities to take action regarding a detected cybersecurity incident.
- Recover: Develop and implement appropriate activities to maintain plans for resilience and to restore any capabilities or services that were impaired due to a cybersecurity incident
Each capability of NIST is an excellent starting point examining the state of your cybersecurity program. In this blog, we’ll focus on the first one: identifying and understanding the risk environment.
Understanding The Business Environment
As the starting point to the NIST CSF, the Identify stage is made up of a number of subcategories, including a cybersecurity assessment of your business environment. A cybersecurity assessment is the best tool for understanding your risk environment and is an even better tool when performed continuously. It allows an organization to determine what NIST controls are already in place and which controls are the most relevant to your organization.
Whether performed internally or contracted to a third party, your cybersecurity assessment depends on your organization’s specific needs. Many organizations work with NIST CSF and have dedicated teams to that conduct internal assessments of the business environment, which helps accelerate the process because an organization’s employees have the benefit of deeper familiarity with the business and the controls that are already in place.
At the same time, third parties or external assessors can bring greater expertise with the variety of frameworks and can also help provide an outside perspective that might make it easier to spot issues that may not be caught by internal assessors. Too many companies look at assessments as something you either pass or fail, a painful and annoying requirement for compliance audits, but approached properly, they are a necessary precursor to building the best cybersecurity strategy for your business environment.
A crucial category of NIST’s CSF “Identify” stage is asset management. Visibility and understanding of your assets are vital because you can’t protect what you don’t know. This step is almost the simplest but can be deceptively complicated in today’s work environment, especially as many companies have cloud-based and on-premises based infrastructures.
A cybersecurity team should continually maintain a list of all the assets that are deployed in the organization, including, but not limited to, employee-issued laptops, corporate servers, networking equipment, and mobile devices, to name a few. Asset management should also extend to virtual machines, both those running on VM hosts in an organization’s data center as well as cloud environments such as Azure, Google Cloud Platform (GCP), and Amazon Web Services (AWS). Additionally, non-corporate owned assets, like employee’s personal mobile devices, pose unique risks to an organization if they are accessing corporate resources from a phone or tablet that is not managed by the IT/Security team; these must also be included in your asset management strategy.
The software running on corporate machines should be included in your asset management strategy for the simple reason that third-party software also holds corporate data. For example, an Enterprise Content Management platform (ECM), like Microsoft SharePoint or Box, is the repository for an organization’s sensitive business documents. Awareness is vital in risk-based planning, and an organization must be aware of its users, the users’ applications, and the devices that run them.
Once the assets are identified, it’s essential to understand their role within your business. Understanding what corporate employees do daily, and how they are using authorized corporate systems, and how that work contributes to your company’s overall mission is critical to building a security strategy that protects and enables the business. In addition, understanding your internal dependencies will help identify critical systems that need more robust protection. Not all servers, for example, are created equal. One may be essential to your company’s ability to deliver goods or services, and even a 24-hour outage could be catastrophic, while other systems could be down for weeks without a material impact on your business’s bottom -line. Risk, therefore, needs to be understood in the context of your business, and this can be one of the most valuable steps in an assessment process.
Governance, Risk Assessments, & Supply Chain Risks
Governance is a key part of asset management and your holistic risk strategy, as it’s important for IT teams to understand the lifecycle management of assets, software, and identities that help comprise an organization’s attack surface. Your governance policies should be continually reviewed and maintained in a central location. Cybersecurity governance rules created by your IT team can be compared against legal and regulatory requirements that might exist based on your industry.
After these details are collected, it’s time for risk assessments. Identify the risks that your asset collection might face and how they would impact business operations. Quantitative analysis strategy plays a huge role in the effectiveness and efficiency of these assessments. Scenarios can be ranked not just by imprecise severity terms (i.e., low, medium, or high) but instead with specific dollar value estimates. Costs can be estimated based on the number of assets that would be impacted by an attack, the steps needed to respond, and the long-term damage that an attack would do.
The final stage in your assessment should be a comprehensive look at your supply chain risks. Analyze the other organizations you depend on to perform operations and how prepared you are for disruption on their side. For example, the recent ransomware attack against NEW Cooperative delayed grain shipments to hundreds if not thousands of chicken producers who relied on them. Ensuring business continuity is a major part of your overall strategy.
At the end of this assessment process, identifying and creating the risk management strategy becomes a much simpler task. You will understand how your organization works in more detail, the critical assets that require the most protection, and what mitigation strategies will provide the most significant return on investment. Finally, you might identify some potential scenarios where it is simply not feasible to build an in-house mitigation strategy; those are where you should look for insurance-based solutions to protect the organization. Ultimately the goal is to minimize the corporate attack surface, and following the NIST cybersecurity framework is an indispensable building block towards your approach to risk and ever-changing threats. | <urn:uuid:e7d0144a-c82b-4af7-b514-2cae6888df86> | CC-MAIN-2022-40 | https://axio.com/insights/getting-started-nist-cybersecurity-framework/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337668.62/warc/CC-MAIN-20221005203530-20221005233530-00156.warc.gz | en | 0.940518 | 2,041 | 2.921875 | 3 |
ABB Drive Assistant
For ABB Drives, particularly the ACS355 Series, the Drive Assistant provides a convenient method to program and control the ABB Drive and electric motors. There are two version, the Basic with a one-line display and the Advanced with a three line display.
In an AC synchronous motor, a squirrel-cage winding embedded near the outer surface of the rotor assembly. Because DC is applied to the rotor field of the AC synchronous motor for synchronization at running speed, the motor cannot be started with the DC-field voltage applied (too much slip). Instead, it must be started as a squirrel-cage induction motor: the amortisseur winding is used for starting purposes only.
A type of transformer that is void of isolation in which one winding serves for both the primary and secondary circuits. When used as a step-down transformer, the primary circuit is connected across the full winding, and the secondary circuit is tap-connected between part of the winding and one end that is common with the primary circuit. When used as a step-up transformer, the secondary circuit is connected across the full winding, and the primary circuit is tap-connected between part of the winding and one end that is common with the secondary circuit. | <urn:uuid:86936f19-c549-4ea3-acaf-f9d37f8ea242> | CC-MAIN-2022-40 | https://electricala2z.com/glossary/electrical-engineering-terms-2/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337668.62/warc/CC-MAIN-20221005203530-20221005233530-00156.warc.gz | en | 0.933208 | 270 | 2.5625 | 3 |
The accessibility of high-end GPUs and rapid development of machine learning software frameworks (Tensorflow, Pytorch, Caffe) have enabled recent success in the deployment of deep learning applications on the cloud. Applications in video analytics, audio processing, natural language processing (NLP) are becoming popular as consumers benefit from the new user experience, driven by the power of AI.
What’s Driving AI from the Cloud to the Edge?
Now, issues in data privacy, communication bandwidth, and processing latency are driving AI from the cloud to the edge. However, the same AI technology that brought considerable advancement in cloud computing, primarily through the accessibility of GPUs for training and running large neural networks, are not suitable for edge AI. Edge AI devices operate with tight resource budgets such as memory, power and computing horsepower.
Training complex deep neural networks (DNN) is already a complex process, and training for edge targets can be infinitely more difficult. Traditional approaches in training AI for the edge are limiting because they are based on the notion that the processing for the inference is statically defined during training. These static approaches include post-training quantization and pruning, and they do not consider how deep networks may need to operate differently at runtime.
Compared to the static approaches above, Adaptive AI is a fundamental shift in the way AI is trained and how current and future computing needs are determined.
The three main tenets of Adaptive AI are robustness, efficiency, and agility. Robustness is the ability to achieve high algorithmic accuracy. Efficiency is the ability to achieve low resource utilization (e.g. compute, memory, and power). Agility deals with the ability to alter operational conditions based on current needs. Together, these three tenets of Adaptive AI formulate the key metrics toward ultra-efficient AI inference for edge devices.
At Latent AI, we use the Adaptive AI approach to adjust AI computing needs. Operational efficiency is determined during runtime in the context of what algorithmic performance is required and what computing resources are available. Edge AI systems that can dynamically adjust their computing needs are the best approach to lowering compute and memory resources needs.
How Latent AI Brings Adaptive AI to Developers
Latent AI Efficient Inference Platform™ (LEIP) is an AI training framework supporting the tenets of Adaptive AI. Our first developer tool is LEIP Compress™, a new quantization optimizer for edge AI devices. LEIP Compress supports the first two tenets: robustness and efficiency through post-training and training aware quantization that achieves high algorithm accuracy while reducing memory footprint and computing needs.
The Latent AI Efficient Inference Platform includes:
- Joint optimization of both AI algorithm accuracy and hardware constraints such as memory footprint
- Elimination of floating-point multiplications by encoding DNN parameters to integer powers of two.
- Arbitrary bit-precision levels for each DNN layer
With LEIP Compress, AI developers have a newfound tool that automates the exploration of low bit-precision AI training. As shown in the example histogram of DNN parameter weights, LEIP Compress provides the means to “shape” the necessary distribution of bits in a manner that supports compression, encoding, and sparsity that are hardware-beneficial (e.g. multiplication free, power-of-two weights). Such a capability opens up the design space for high performance and efficient AI on the edge.
In summary, Latent AI aims to democratize AI training for all developers by supporting a new workflow with hardware targets in mind. We open up new application development with robust and efficient edge AI in mind. Look for upcoming LEIP frameworks that include support for agile edge inference to integrate all tenets of Adaptive AI.
Sek Chai, Co-Founder, and CTO, Latent AI, Inc.
Parajuli, S., Raghavan, A., & Chai, S. (2018). Generalized Ternary Connect: End-to-End Learning and Compression of Multiplication-Free Deep Neural Networks. arXiv preprint arXiv:1811.04985. | <urn:uuid:a75643bc-0e44-4d22-97c3-96d466433adb> | CC-MAIN-2022-40 | https://latentai.com/the-next-wave-in-ai-and-machine-learning-development/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337971.74/warc/CC-MAIN-20221007045521-20221007075521-00156.warc.gz | en | 0.901813 | 860 | 2.65625 | 3 |
Written by Amer Owaida, Security Writer at ESET
As many as 15% of Brits use their pets’ names as passwords to “protect” their online accounts, according to the United Kingdom’s National Cyber Security Center (NCSC). The agency cited figures from a survey that revealed how a worrying number of Brits leave themselves wide open to account takeover and other attacks.
As many as 14% use family members’ names as part of their passwords. Another 13% use a date that is important to them, with 6% integrating the name of their favorite sports club or team into their passwords. Also, 6% admitted that they use “password” as the whole or part of their password.
In all these cases, cybercriminals could easily break into the accounts. Indeed, the results of the survey aren’t too dissimilar from a similar study three years ago. “We may be a nation of animal lovers, but using your pet’s name as a password could make you an easy target for callous cybercriminals,” said Nicola Hudson, NCSC Director of Policy and Communications.
The agency also urged people to use proper password-creation techniques in lieu of resorting to easy-to-remember passwords. “I would urge everybody to visit cyberaware.gov.uk and follow our guidance on setting secure passwords which recommend using passwords made up of three random words,” Hudson said.
It’s worth noting that poor password choices affect people the world over and aren’t limited to just the United Kingdom; the latest annual list of the most commonly used passwords shows an abundance of such examples. NCSC also urged everybody to avoid another common password mistake – recycling the same password over and over again.
Instead, you should use a unique and strong password or passphrase for each of your accounts, especially the valuable ones, and whenever possible, couple it with an added later of protection – multi-factor authentication. To avoid the hassle of remembering all those credentials, you should also consider using a password manager.
The survey also revealed that people are creating more and more online accounts, with 27% of those quizzed saying that they have at least four more new accounts compared to the same time last year. Meanwhile, 6% reported they have added more than 10 new accounts over the past 12 months. | <urn:uuid:759bbfaf-e8e7-4f6d-8572-8d611b23c377> | CC-MAIN-2022-40 | http://arabianreseller.com/2021/04/22/one-in-six-people-use-pets-name-as-password-says-eset/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334515.14/warc/CC-MAIN-20220925070216-20220925100216-00356.warc.gz | en | 0.952143 | 488 | 2.53125 | 3 |
Let us first answer the main question. Who benefits from it? Why have computers, networks, and mobile phones become carriers of not only useful information, but also a “habitat” for different malicious programs? It is not difficult to answer this question. All (or almost all) inventions, mass use technologies have, sooner or later, become a tool of hooligans, swindlers, blackmailers and other criminals. As soon as there is an opportunity to misuse something, somebody will definitely find new technologies and use them in a way that was not intended by the inventors, but in an altogether different way – for their own interests or to assert themselves to the detriment of others. Unfortunately, computers, mobile phones, computer and mobile networks have not escaped this fate. As soon as these technologies started being used by the masses, the bad guys stepped in. However, the criminalization of these innovations was a gradual process.
- Computer vandalism
- Petty theft
- “Grey” business
- Computer vandalism
In the past the majority of viruses and Trojans were created by students who had just mastered a programming language and wanted to try it out, but failed to find a better platform for their skills. Up to present time writers such viruses were seeking only one thing – to raise self-esteem. Fortunately, a large part of such viruses have not been distributed (by their authors) and shortly viruses “died away” together with the storage disks or authors of viruses sent them only to anti-virus companies with a note that the virus would not be further transferred.
The second group viruses-writers also includes young people (often – students), who have not yet fully mastered the art of programming. Inferiority complex is the only reason prompting them to write viruses, which is compensated by computer hooliganism. Such “craftsmen” often produce primitive viruses with numerous mistakes (the so-called “student viruses”). Life of such virus-writers has become much simpler with the development of Internet and emergence of numerous websites training how to write a computer virus. Web-resources of this kind give detailed recommendations on how to intrude into the system, conceal from anti-virus programs and offer ways of further distribution of a virus. Often ready original texts are provided, which require only minimal “author” changes and compilation as recommended.
When older and more experienced, many virus-writers fall into the third and most dangerous group, creating professional viruses and lets them out to the world. These elaborate and smoothly running programs are created by professionals, not infrequently very talented programmers. These viruses often intrude into data system domains in very unusual ways, use mistakes of security systems of operating environments’, social engineering and other tricks. | <urn:uuid:94aa4de3-a0f3-4673-b0bc-a378bb1a2010> | CC-MAIN-2022-40 | https://encyclopedia.kaspersky.com/knowledge/who-creates-malware-and-why/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335491.4/warc/CC-MAIN-20220930145518-20220930175518-00356.warc.gz | en | 0.969939 | 575 | 2.984375 | 3 |
agsandrew - Fotolia
Data released by West Midlands Fire Service appears to show the city of Birmingham has too many fire stations, with 15 compared with neighbouring Solihull’s two. The service’s online map of attendance times shows many parts of Solihull, a suburban and rural area, have to wait much longer for firefighters to arrive. Even on the...
basis of relative population sizes, Solihull looks under-served.
But other data mapped by the service reveals why urban Birmingham has numerous stations: “If you look at where the incidents are, you’ll be able to see very clearly there’s a strong justification,” says Jason Davies, a data analyst for the service’s strategic hub. There are proportionally more fires in areas of Birmingham, including Aston, Handsworth, Ladywood and Highgate.
The service also uses data analysis to target fire safety advice, and has found correlations between high risks of accidental home fires and single-person households, social renting, unemployment, smoking and black and Afro-Caribbean ethnicity. Davies says some factors may directly contribute: unemployed people are more likely to be at home, making it more likely someone will accidentally start a fire.
However, “you have to be careful before you jump to conclusions,” says Davies. “The correlations alone are enough to inform our service delivery model. We don’t need to understand the exact causes.”
It’s not hard to make a case for using data to focus fire service resources on the households most at risk, particularly when that data is openly available. But many organisations use data to make decisions in a far less transparent way, and the increasing use of machine learning or artificial intelligence (AI), where computers use such data to adjust decision-making algorithms, has worried Sir Tim Berners-Lee, the inventor of the world wide web.
“When AI starts to make decisions such as who gets a mortgage, that’s a big one,” Berners-Lee told an event in April 2017, going on to imagine AI-based systems creating their own companies.
“So you have survival of the fittest going on between these AI companies until you reach the point where you wonder if it becomes possible to understand how to ensure they are being fair, and how do you describe to a computer what that means anyway?”
AI gives stiff sentence
Some people’s lives have already been severely affected by secret algorithms. In the US, in 2013, Eric Loomis was sentenced to six years in prison by a Wisconsin judge. Loomis pleaded guilty to eluding a police officer, but the issue was the length of his sentence, which the judge partly decided based on a “Compas score”.
Compas [Correctional Offender Management Profiling for Alternative Sanctions] scores assess the risk that someone will commit a further crime, using an algorithm developed by US criminal justice IT company Northpointe.
Northpointe did not release its workings when Loomis challenged the length of his sentence. The US Supreme Court recently declined to review the Wisconsin supreme court’s ruling in favour of Compas’ use in Loomis’ case, although the Electronic Privacy Information Centre is involved in several other legal challenges it calls a lack of algorithmic transparency. Many US states use similar algorithms, and Durham Constabulary in the UK is preparing to use a similar system to decide whether or not to release people arrested from custody.
Christopher Markou, a doctoral candidate at University of Cambridge’s law faculty, says the results of such algorithms can be beneficial in supporting human decisions – the problem is when they replace them. “I’m old fashioned in that I believe the justice system is a human system,” he says. “By trying to get systems like Compas to replicate portions of the justice system, there is an implicit concession that we are not good enough at this.”
There are particular problems when algorithms are secret: “That’s a pretty fundamental challenge to how we’ve thought the justice system has worked, which is equality of arms – you have to disclose your case proactively to the defence counsel so a robust defence can be mounted,” he says.
There is a further risk that algorithmic opinions are seen as untainted by human bias and therefore risky to challenge: “It’s easier to blame something else, other than yourself,” says Markou.
Read more about the limitations of AI
- Watson Analytics is a strong player in a formidable field that includes Google and Adobe. It does perform as advertised – but IBM's AI-driven analytics technology leaves a lot to be desired.
- Modern AI tools fall short of true artificial intelligence, and this could have implications for how the technology is used by enterprises in the near future.
The problem is that algorithmic decisions are very often based on an archive of human ones, along with all the biases that archive contains. US public interest publisher ProPublica last year analysed Compas risk assessments for 7,000 people arrested in Florida and found that as well as being “remarkably unreliable in forecasting violent crime” the scores wrongly rated black defendants as likely to become criminals almost twice as often as white ones. Northpointe disputed the analysis.
The legal world has a technophobic history: courts initially resisted the use of photocopying and a 1950s paper by a US law professor worried about ham radio hooking up prostitutes to truck drivers. However, there is something different about machine learning: “It can reprogramme itself, at least in deep learning applications,” he says. This means such a system could produce different results from the same data for no apparent reason.
Those managing projects that make decisions with data need to think about how to protect it, says Joanna Bryson, a cognitive scientist at the universities of Bath and Princeton. “People talk about data as the new oil,” she says. “It does have value, but oil is something you have to be careful with. It’s explosive – it’s something you don’t want to store everywhere and not think about.”
Bias in data-driven decisions
Bryson has researched bias in data-driven decisions and sees three main ways to tackle it. The first is to recognise that biases exist: “The reason machine learning is working so well is it is leveraging human culture. It’s getting the bad with the good,” she says. This may particularly affect data on decisions made over several decades, but only using recent data can increase random bias.
The second is to test data for biases in obvious areas such as ethnicity, location, age and gender. This may come more naturally to a diverse IT workforce as individuals are more likely to consider the impact on themselves, but Bryson says this is not guaranteed: “As a woman who used to be a programmer, you’re often absorbed into the dominant group you’re in.”
Third, Bryson says those using data and algorithms should get used to auditing and surveillance. “There may very well become bodies like the FDA for AI and tech more generally,” she says, referring to the US’s powerful Federal Drug Administration. The EU’s General Data Protection Regulation, which comes into force in May 2018 and which the UK looks set to retain after Brexit, includes a specific right to challenge automated decisions. “In advance of that, for your own benefit, you can make sure you have internal processes,” she says.
Such auditing can help board members and other managers to check what is going on. “A lot of programmers are sloppy,” says Bryson. “They’re used to not having to do a lot of tests, although big organisations have got better at expecting to do tests. But you do get people that are almost deliberately obfuscating – ‘if we’re using machine learning we don’t have to do these tests because no-one can check machine learning’. Well, that’s not true.”
Pneumonia less likely to carry off asthmatics?
An increasing number of experts are looking at how to make data-driven decisions, including those that involve machine learning, fairer. In the 1990s, Rich Caruana, then a graduate student at Carnegie Mellon University, worked on training a neural net machine learning system to predict the probability of death for pneumonia patients.
A parallel rule-based model came up with the surprising rule that patients with asthma were less likely to die from pneumonia as those without asthma. “You don’t need much background in healthcare to question whether that would make sense,” says Caruana, now a senior researcher at Microsoft Research.
The data was biased, but for good reasons: patients with asthma were more likely to see a doctor quickly for new breathing problems, doctors were more likely to take these seriously and hospitals were more likely to treat them urgently. The actions of patients and professionals, based on the medical reality that pneumonia is more dangerous for those with asthma, made the data suggest the reverse was true.
As a result, Caruana and his colleagues did not use the neural net, a black-box model which does not disclose why it makes the predictions it does. More recent research found this data similarly suggested that chest pain and heart disease patients were less vulnerable to pneumonia.
Identifying and adjusting for biases
Caruana has helped develop a generalised additive model known as GA2M that is as accurate as a neural net but allows users to see how predictions are made, allowing them to spot anomalies. “With this new kind of model, you absolutely include all the variables you are most terrified about,” he says, so biases can be identified and adjusted for.
This is a better option than removing variables, as bias is likely to affect correlated data as well. He will be discussing his work at the Fairness, Accountability and Transparency in Machine Learning event in Halifax in Canada on 14 August.
“Every complex dataset has these landmines buried in it,” says Caruana. “The most important thing, it turns out, is just knowing you have a problem.” In some applications, the problems will not matter: the pneumonia probability of death data would be fine for insurers looking to calculate survival rates. “The data is not right or wrong, the model hasn’t learnt something that’s right or wrong,” says Caruana – but applications of it can be.
Data can be used to make decisions well if processes are transparent, data is tested for problems and users recognise perfect, unbiased data is usually not available. In theory, a clinical trial could determine the true risk to asthma patients from pneumonia by sending half of them home to see if more of them died than those treated in hospital – but for obvious reasons, this would be unethical.
“It’s illegal to have the data you want, and it should be illegal,” says Caruana. That is why it makes sense to learn how to use the data you have. | <urn:uuid:bcb81e58-283e-4066-9a2b-e292f2e8a8f9> | CC-MAIN-2022-40 | https://www.computerweekly.com/feature/Automated-decision-making-shows-worrying-signs-of-limitation | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335491.4/warc/CC-MAIN-20220930145518-20220930175518-00356.warc.gz | en | 0.964923 | 2,337 | 2.765625 | 3 |
The smallest things we do can give away our biggest secrets.
According to researchers at the University of Padova in Italy, how a person moves a mouse when answering questions on a computer may reveal whether or not they’re lying.
The finding has the potential to identify everything from fake online reviews and fraudulent insurance claims to pedophiles and terrorists, the team suggests.
The researchers used an artificial intelligence algorithm trained to make decisions based on data.
The computer system was presented labeled examples from individuals answering questions honestly and those providing false answers.
With experience, the algorithm began to identify the differences in mouse movements between an honest and dishonest answer.
During the study, which involved 60 students at the University of Padova, participants answered a series of questions — some of which were unexpected.
Half were told to assume a false identity and given time to practice it.
The truthful individuals slid their mouse directly to an answer.
The dishonest individual took a longer, indirect path to their answer.
“Our brain is built to respond truthfully.”
“When we lie, we usually suppress the first response and substitute it with a faked response,” said Giuseppe Sartori, lead researcher and a University of Padova professor.
The study was published recently in the online journal Plos One.
Sartori envisions the technology helping authorities identify terrorists who are entering European countries under false identities.
Sartori’s technique does not require a person to know certain information, such as an accurate birthday or address, to determine if they are lying.
Instead, authorities could detect lies by the manner in which specific questions were answered.
Sartori said the technology could also be used to identify a pedophile who signed up for an online service with a false age.
A well-coached individual could learn to lie convincingly with quick responses to questions.
But they might stumble on tangential questions, such as stating their zodiac sign or a cross street near their home address.
However, there are limitations to the approach — artificial intelligence is only as good as the data it’s trained on.
Sartori said more subjects need to be studied to ensure the results accurately reflect all human behavior.
The team’s next step is to examine the differences between how honest and dishonest individuals type on a keyboard when answering questions. | <urn:uuid:521395cc-5337-4628-9fa7-6544c983bce2> | CC-MAIN-2022-40 | https://americansecuritytoday.com/move-computer-mouse-may-reveal-youre-lying/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337404.30/warc/CC-MAIN-20221003070342-20221003100342-00356.warc.gz | en | 0.95608 | 491 | 3.015625 | 3 |
Organizations are increasingly seeing the value of microservices—the architectural style—to develop new applications and distill monolithic, legacy applications, and systems. These systems are unwieldy and difficult to maintain, manage, and quickly scale, not to mention they can become a liability and roadblock to progress.
Microservices are architecture and a mechanism considering an architectural pattern in which complex applications are composed of small, independent processes that communicate with each other using language-agnostic APIs. At its essence, service-oriented computing decomposes the application down to the functional primitive and builds it as a set of services that can be leveraged by other applications or the application itself.
Microservices Cloud-native apps can be built as connected containers through a service mesh that runs reliably across environments. Compared to monolithic applications, microservice ecosystems are competently suited for continuous integration and deployment, enabling better, faster, and more dynamic iterating. Complex workloads can be brought into the cloud, then refactored and efficiently broken down by leveraging microservices running on containers (like Docker and Kubernetes). When microservices are built using a container infrastructure, it can run anywhere with virtually unrestricted processing power.
The benefits—primarily portability, modularity, and velocity—are achieved more rapidly. Containerized microservices also improve operations by isolating services that are easy to deploy, identify, monitor, and fix if something goes wrong.
With CMI, microservices and its pipeline can be up and running in a fraction of time compared to new design and development, helping organizations bring value to its digital transformation mission 65% faster, saving time and money.
ArdentMC a NITAAC CIO-SP3 Small Business Contract Holder developed a solution to address these various challenges. This solution is called the Common Microservice Initializer or CMI. CMI was developed for use by a component of the Department of Homeland Security (DHS) to help quickly generate clean structured, fully functional CI/CD pipelines that adheres to DHS’s security guidelines and best practices. Let’s find out more!
Youtube Link: https://www.youtube.com/watch?v=ffZw7cm4LHs | <urn:uuid:e8b0e7a9-8de8-4155-b079-05ece54cf574> | CC-MAIN-2022-40 | https://wwwdev.ardentmc.com/2022/01/05/test-page/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337680.35/warc/CC-MAIN-20221005234659-20221006024659-00356.warc.gz | en | 0.933415 | 457 | 2.609375 | 3 |
2021 has been a year of many things, one of them being extreme weather. When you sit back and think about it, there have been extreme weather incidents all over the country for many years, and we’ve come to expect something with these – power outages. Why do we expect them? And why do they even happen? Let’s take a closer look at what happens to the power grid during some of these incidents.
The Great Texas Power Outage of 2021
The Texas incident in 2021 is really a unique case – after all, Texas is not exactly known for its freezing temperatures. However, freeze it did, and with it bringing massive power outage and large amounts of people without power across the state.
Because Texas isn’t used to freezing, things are a bit different there, especially when it comes to power. Texas uses quite a great deal of wind power, and wind turbines simply froze and didn’t work. Along with that came issues with the natural gas power plants. If you’re from someplace that’s used to freezing weather, you know what an issue it can be if your water pipes freeze. The cold also impacted natural gas plants by freezing supply lines, rendering them basically useless.
If you don’t know much about the power capabilities of Texas, let me give you a quick lesson. First of all, Texas is abundant in one natural resource, which is oil. Oil is refined and used in natural gas power plants. Since Texas has this in abundance, they are unique in the sense that they generate much of their own power, and are mostly an isolated power grid, versus buying power from neighboring states like many other states do.
Coupled with the generation issues were an increased usage because you guessed it, it was cold out. If you’ve ever used an electric heater, you know they have a big impact on your energy bill. This increased demand and lack of generation created the perfect storm, excuse the pun.
Generation and Supply Issues Are Common
This massive outage in Texas was a great way to showcase all of the different things that can go wrong during a storm. The demand for power increased, and the output decreased, which of course, we all know won’t end well. Modern power systems have a number of fail safes built into them. For example, if power generating devices and distribution devices cannot keep up with their requests, they will simply shut down. Power is one of those tricky things, and it generally involves quite a bit of heat, which we all know from our time in the the data center can be a very disruptive force.
Energy providers were forced to attempt to get ahead of this, and actually turned off distribution selectively. This is called a rolling blackout. This selectively turns off portions of the grid, so that the energy draw will decrease and the rest of the grid will be able to continue operating instead of shutting down. The rolling part is that these portions of the grid are cycled through. After a determined period of time, a new section of the grid will be turned off, so that the part that was off can come back on.
There are many different thoughts out there on why things happened the way they did, especially since this isn’t the first time Texas has seen major cold weather induced power outages. The fact of the matter is is that power generation companies performed activities that we’re all used to when they decided what steps should be taken to prevent this sort of thing from happening.
They likely started with a business impact analysis. What would be the cost and impact of a major power outage due to severe weather? Based on that outcome, they likely decided how much they would invest (or would not invest) to mitigate the extreme weather risk. This was the basis of the operational plans that were in place.
When the cold weather actually hit, and the implemented controls failed, it quickly turned into what we in the IT world recognize as a disaster recovery exercise. How could they mitigate the damage as much as possible, and bring systems online as quickly as possible. Because of the nature of this event, there was another layer of ensuring things didn’t get worse and more services were not lost.
Power Outages and preparedness
While what happened in Texas was an extreme case, the basics apply when we see power outages during other storms in events. When power distribution or generating equipment is damaged, there are issues supplying power to homes and businesses. These can of course be damaged by storms. When events that create more demand for power happen, whether it be extreme heat or extreme cold, both power distribution and generation systems need to be able to keep up with the extreme load, or fail safe mechanisms will kick in, leading to disruption of service. Likewise, outages may manually be triggered by power companies to try to lessen the load across a grid so more cascading failures do not happen.
Read more from Melissa here now. | <urn:uuid:69d5c923-7596-42ee-b784-b09eba2031a1> | CC-MAIN-2022-40 | https://24x7itconnection.com/2021/04/13/why-we-still-see-power-outages-in-2021/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338001.99/warc/CC-MAIN-20221007080917-20221007110917-00356.warc.gz | en | 0.97199 | 1,016 | 2.5625 | 3 |
Very often, there’s an indispensable need for users to access multiple applications, which are hosted by several organizations directly involved in the project. This need is almost always present irrespective of the size or criticality of the project. With multiple security domains comes the greater pain of having to remember the different credentials for each and every one of them.
The need to remember all those credentials and use them frequently is loathed for obvious reasons. The concept of federated login aims to simplify a time-consuming and highly repetitive login process. Since this is obviously a good thing and worth discussing, this post will explain the concept of federated login, where it works best, and its pros and cons.
How Security Worked Before Federated Login
In the days of yesteryear, users’ login identities were dispersed across the different websites that they visited. As a result, you had to create a new username and password every time you tried to log in to a new site. And these sites stored your credentials. Every time you revisited a site, you had to re-enter them. This made sense when there wasn’t a single parent organization to manage those sites. But even if a single organization did own multiple sites, each time you tried to access those sites, you still had to log in separately.
What Is Federated Login
Federated login enables users to use a single authentication ticket/token to obtain access across all the networks of the different IT systems. As a result, once the identity provider’s authentication is complete, they now also have access to the other federated domains. The users don’t have to perform any other separate login processes.
Federated identity is all about assigning the task of authentication to an external identity provider. Federated identity management (FIM) is an umbrella term that encompasses the federated identity concepts, the policies, agreements, standards, and the other factors that affect the implementation of the service.
How Federated Login Works
The identity provider saves the login credentials of the users, and they log in directly to this identity provider. Typically, that’s the parent organization. When users want access to another connected domain, they don’t have to provide credentials to the corresponding service providers. Instead, when there’s a login attempt, that application sends a request to the user’s identity provider. It approves the request, after which the login happens. The user’s identity provider thus provides the authorization, and the remote applications trust it.
Scenarios Where Federated Login Works Best
Federated login implementation doesn’t work well with all IT environments—although, when implemented right, it usually goes hand in hand with most of them. This section lists out examples of the best environments for federated login.
Federated Login Within an Enterprise
Here, the applications are hosted in the cloud, which doesn’t fall under an organization’s security perimeter. Implementing federated login is a good idea in such a scenario. When done right, the process workflow is the same as accessing on-premise applications. That is, once users successfully sign into a corporate network, they can then also access all the other applications in the network without having to sign in again.
Federated Login With Multiple Organizations
Users can realize the benefits of federated login to its fullest in this scenario. A use case is when users from multiple organizations want access to the resources that are exclusive to a single organization. The problem that arises when you don’t have federated login is that other users wouldn’t have an account in the corporate directory. When you do implement federated login, even other users can have access to resources by signing in only once to their identity provider.
Federated Login for Software as a Service (SaaS) Applications
In this scenario, multiple parties sign in with different sets of accounts. Independent software vendors (ISVs) provide a service used by multiple clients. Implementing federated login in this environment would enable different types of users to sign in with different identity providers. For instance, the employees of an organization will use their corporate credentials to sign in. On the other hand, their clients might use any of their social network credentials.
Advantages of Federated Login
Federated login could be your answer to the rapidly evolving scope of identity management systems. Read on for some benefits that it brings to the table.
Reduced Administrative Overheads
Why do users prefer to remember the fewest number of usernames/passwords possible? For an IT administrator, the fewer user identities across multiple applications, the less the headache. Federated login’s single sign-on (SSO) mechanism calls for the user to have only a single set of login credentials, thus directly reducing the administrative efforts needed. SSO is a win-win for both the users and the IT administrators. Thus, federated login has a direct impact and minimizes the resources in the form of manpower and cost deployed for addressing users’ login issues.
Minimized Security Risks
One of the inherent benefits of federated login over most other cloud-based SSO products is that the login credentials are stored on-premises, protected by the home organization’s firewall. Besides, it significantly reduces the number of passwords involved in an organization’s overall security pipeline. Having multiple login credentials invites various security threats. It might also have a psychological impact on the users and weaken password strengths. Federated login helps organizations overcome this obstacle, and it minimizes security risks.
Enhanced User Experience
Users want seamless access to resources they need without any high-demand processes. The last thing they want is to work in an environment that requires them to remember 10 different passwords to access 10 different applications every single day. You don’t want them to spend a large chunk of their time just trying to access your resources, either. And you have the opportunity to delight them since federated login can utilize their credentials from social media sites for account registration—they can log into your services on the go.
Federated login does come with some drawbacks, though. Here are a few of them.
High Initial Setup Costs
Federated login demands massive upfront costs. That’s due to the architectural modifications that your current applications/systems have to go through to be federated. Naturally, that makes things difficult for low to mid-level IT decision-makers.
SSO Becomes Critical
The most crucial element in the whole federated login concept is the SSO, and it becomes extremely business critical. Any issues in the SSO account will also affect all the federated accounts under its authentication. This also means that it’ll present itself as a single point of target for the hackers.
The different organizations in a single federated domain must mutually trust each other. Ownership issues may arise if there are conflicts regarding data mismatch of various identities. For that reason, it’s vital to create policies that don’t violate the security requirements of all the participating members. But different organizations have different rules and requirements, and it complicates the process.
Should You Implement Federated Login?
Federated login offers an extensive array of benefits that are hard to ignore, but it also comes with its own risks and complications. It’s definitely not a silver bullet, but in the environments where you can implement it successfully, it’s certainly worth going through the hardships to ultimately reap bigger rewards in the long run.
The results of implementing federated login are promising enough for you to start thinking more about why you haven’t embraced it yet rather than the reasons why you should implement it!
Author: Mark Robinson | <urn:uuid:348e97dc-f797-463a-9799-ef071c887c87> | CC-MAIN-2022-40 | https://carvesystems.com/news/what-does-federated-login-mean-a-simple-detailed-answer/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338001.99/warc/CC-MAIN-20221007080917-20221007110917-00356.warc.gz | en | 0.930903 | 1,605 | 2.6875 | 3 |
What is a Spear Phishing?
Spear phishing is a deceptive communication technique in which a victim is lured via e-mail, text or tweet by an attacker to click or download a malicious link or file. The common objective of this technique is to compromise the victim machine by stealthily inserting a backdoor which seeks to obtain unauthorized access to confidential data remotely. These attempts are more likely to be conducted by attackers seeking financial gain, trade secrets or sensitive information. Popular Techniques used for the Spear Phishing attack comprise of mixture of social engineering, client side attacks, and requests via social networking sites etc. What is difference between a Phishing and Spear Phishing attack?
Phishing messages appear to come from large well-known company or web site having a large user base such as Facebook, Twitter, Amazon, Paypal, BestBuy or eBay. However, in spear phishing, the apparent source of the e-mail is likely to be an individual generally in a position of authority within the organization.
Most people are conditioned to ignore suspicious looking email asking for confidential information. They simply delete such phishing mails or set filters to do so on automatic basis once they recognize the pattern. Spear phishing is more dangerous than normal phishing because the message seems to originate from a known trusted source, there is information in message supporting its validity, and the request appears to form a logical basis.
Necessary factors for successful spear phishing attack:
- The message should come from a known source or ideally from trusted “highly placed” authoritative figure in organization.
- The message must complement the context in what is being said and the contained information supplements its validity.
- The recipient can draw a “firm need” or a logical reason for the request made by sender.
NII can help you to simulate Spear Phishing attacks on selected email ID’s of your employees. We do this by executing this as a part of our Penetration 2.0 Testing which effectively demonstrates how robust your information security awareness is inside your organization. By planning thoroughly, we make sure that Spear Phishing Testing is done in tightly controlled manner. We are then able to provide a fairly accurate picture of your organization staff’s potential susceptibility to such lucrative attacks which may entice even a reasonably educated user to fall for it. To know more, write to us for more details on our Spear Phishing Testing Methodology. | <urn:uuid:ebc6af1b-f7d6-4399-aaf6-93e32e2f086a> | CC-MAIN-2022-40 | https://www.niiconsulting.com/services/security-assessment/spear-phishing.php | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335059.43/warc/CC-MAIN-20220928020513-20220928050513-00556.warc.gz | en | 0.945267 | 494 | 2.6875 | 3 |
By now, we’re all well used to cloud computing, and recognise the many ways in which cloud computing benefits businesses and makes our everyday lives easier. Could edge computing have a similar impact?
What is edge computing?
Edge computing refers to the processing of data on devices such as smartphones. Unlike in cloud computing, where the data is processed in remote, far-off data centres, edge computing gives devices the ability to carry out some or all of the data processing right then and there, at the point at which the data is collected.
This is all possible because devices are getting more and more powerful (in part thanks to AI), meaning they can handle more data processing tasks. In other words, the device no longer has to send every little piece of data – whether it’s useful or not – to the cloud.
Think of all the data an office security camera gathers in the course of a night. Hours and hours of footage, with the vast majority of that footage showing empty corridors and rooms. Sending all of that data, which probably has little or no value, is a waste of bandwidth. But an AI-equipped security camera, which has the ability to analyse images right then and there, would be able to detect unusual activity and prioritise that data.
Key benefits of edge computing
Let’s look at the biggest advantages edge computing brings:
1. Saving bandwidth
The proliferation of smart devices means we’re creating an extraordinary amount of data. But not all of that data is critical. Revisiting our security camera example, if you have multiple cameras on a site, and each one is constantly streaming data to the cloud, then that’s using a lot of bandwidth for potentially not very useful data. But if the cameras are intelligent enough to process the data at its source, they can stream only the most important footage to the cloud, while discarding the rest.
2. Reducing latency
Another advantage of devices being able to sort critical data from the not-so-critical data is a reduction in latency (i.e., the time it takes to send data and receive a reply). With cloud computing, the device may be sending information to a data centre on the other side of the world for processing, and this often results in a brief delay. This doesn’t always matter; for example, most of us don’t mind that it typically takes Alexa a few seconds to reply to our question about today’s weather.
But that lag time is far less acceptable in the context of, say, a self-driving vehicle out on the road. If another car runs a stop sign, do you really want your autonomous vehicle to have to send that sensor and visual data to the cloud, then wait for a decision on what to do next? Not so much. With edge computing, critical data – data that’s absolutely vital to real-time decisions – can be processed on the spot, resulting in faster decisions—the closer the processing, the quicker the response time, essentially. Meanwhile, the data that’s not so time-critical (for example, fuel performance data) can be sent to the cloud for later analysis.
3. Enhancing security and privacy
Edge computing reduces the amount of data that has to travel over a network, which is an obvious bonus from a security perspective. There’s also the fact that data is distributed (in this case, located on multiple user devices) as opposed to being stored in one place. This is all good news, providing manufacturers of smart products make securing that local data a key priority.
What about privacy? In theory, with less data being uploaded to the cloud and more data being processed on the device, users of smart devices will have greater control over their data. Imagine, if your Amazon Echo speaker is able to process and respond to your weather forecast request without that data being sent to a central Amazon server, then that’s one less bit of data the company has about you. That’s the idaea, anyway. In reality, companies are unlikely to give up their vice-like grip on something as valuable as user data. But as edge computing evolves, we may (if we’re lucky) see more options for opting out of sending our data to the cloud.
A potential pitfall to be aware of
That’s the positives taken care of. What about the negatives? In my mind, there’s one potential downside to edge computing: namely, that important data could end up being overlooked and discarded in the quest to save bandwidth and reduce latency.
Data that isn’t vital for real-time decisions may have other uses. For example, if an autonomous vehicle is travelling along an otherwise empty road, it may seem like that visual and sensor data is pointless. What can be learnt from an empty road? Quite a lot, potentially. That seemingly useless data could still provide information on road conditions and how the vehicle behaves under those conditions – and this can help regulate other autonomous vehicles travelling the same route in the future. A balance is needed between maximising the opportunities provided by edge computing while still recognising the value of data. | <urn:uuid:77b4db45-f2d4-46fb-81de-7cacc0551ce9> | CC-MAIN-2022-40 | https://bernardmarr.com/3-advantages-and-1-disadvantage-of-edge-computing/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337415.12/warc/CC-MAIN-20221003101805-20221003131805-00556.warc.gz | en | 0.93399 | 1,062 | 3.25 | 3 |
“Artificial intelligence” (AI) may evoke fears of robots writing their own software code and not taking orders from humans.
The real AI, at least in present form, is already delivering results in the business world. Technology companies are using powerful computers and advanced statistical models to accelerate product development. Most do not call these efforts AI but machine learning, however. As a form of AI, machine learning is making it possible to quickly find relevant patterns in data captured by Internet of Things (IoT) devices and sensors, explains Adam Kahn, vice president of fleets for Netradyne, which has a vision-based fleet safety system, Driveri (“driver eye”).
Ten years ago, fleet safety managers had to interpret critical events reported from telematics systems, Kahn says. A “hard brake” event may not be a symptom of distracted or aggressive driving behaviors. The driver might have hit the brakes when a car suddenly him cut off in traffic. Video-based safety systems have given fleets context for hard braking and other safety-critical events. With machine learning, these systems are now automating the review process of video and data by identifying complex patterns of risk.
New technologies are giving drivers visual and audible tones and feedback to deter risky behaviors like fatigue and distraction. In many cases, this direct-to-driver coaching model can eliminate the need for managers to schedule face-to-face meetings with drivers. Other applications using AI are instantly solving difficult transportation problems beyond the realm of safety.
Moving to the edge
The foundation of machine learning and artificial intelligence is precision of data and accuracy of statistical learning models, Kahn says. Data precision comes from vehicle and engine electronics, cameras, sensors and IoT devices in vehicles. With precision, technology suppliers are able to apply machine learning models to accurately identify relevant patterns. The patterns are detected by algorithms uploaded to servers in the cloud and to “edge” computing devices with the processing power to support advanced mobile applications. Some edge devices use teraflop processors similar to those in the Xbox gaming system. The processing power enables computer vision to detect complex patterns of risk from high-definition video, Kahn says. Patterns for driver fatigue, like yawning, and distraction can be instantly detected as can other behaviors like following distances that are unsafe given current speeds, road and traffic conditions. […] | <urn:uuid:0b78c009-5d61-46b6-8952-8163688fd737> | CC-MAIN-2022-40 | https://swisscognitive.ch/2018/07/12/the-road-ahead-will-artificial-intelligence-replace-fleet-management/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337415.12/warc/CC-MAIN-20221003101805-20221003131805-00556.warc.gz | en | 0.937756 | 480 | 2.828125 | 3 |
The educational system and many of its elements are targets for cybercriminals on a regular basis. While education is a fundamental human right recognized by the United Nations, the financial means of many schools and other entities in the global educational system are often limited.
These limited budgets often result in weak or less-than-adequate protection against cyberthreats. Unfortunately, organizations in this industry are forced to economize and cut the costs of security.
Schools by nature have a lot of personal data on record—not only about their students, but in most cases, they also have records of the parents, legal guardians, and other caretakers of the children they educate. And the nature of the data—grades, health information, and social security numbers, for example—makes them extremely valuable for phishing and other social engineering attacks.
Ransomware can also have a devastating effect on educational institutions, as some of the information, like grades for example, may not be recorded anywhere else. If they are destroyed or held for ransom without the availability of backups, the results can be disastrous.
Organizations in the education industry have some special circumstances to deal with when trying to protect their data and networks:
- Many schools use special software that allows their students to log in both on premise and remotely so they can view their grades and homework assignments. These applications occasionally get hacked by students.
- Growing networks enlarge the attack surface. Modern education requires children of young ages to learn computer skills, so many students are connected to the institution’s network at once.
- If a tech-savvy student wants a day off, claims that he couldn’t access his homework assignments, or simply wants to brag, what’s to stop him from organizing or paying for a DDoS attack? Kids will be kids.
- Schools often also harbor a mix of IoT and BYOD devices, which each come with their own potential problems. Some schools have noticed a spike in malware detections after holiday breaks, when infected devices get introduced back into the school environment.
The sensitive nature of the data and having an open platform for students at the same time creates a difficult situation for many educational institutions. After all, it is easy to kick in a door that is already half open— especially if there is a wealth of personally identifiable Information (PII) behind it.
The current situation
An analysis in December 2018 by SecurityScorecard ranked education as the worst in cybersecurity of 17 major industries. According to the study, the main areas of cybersecurity weaknesses in education are application security, endpoint security, patching cadence, and network security.
In our 2019 State of Malware report, we found education to be consistently in the top 10 industries targeted by cybercriminals. Looking only at Trojans and more sophisticated ransomware attacks, schools were even higher on the list, ranking as number one and number two, respectively.
So, it shouldn’t come as a surprise that according to a 2016 study entitled: The Rising Face of Cyber Crime: Ransomware, 13 percent of education organizations fall victim to ransomware attacks.
Malware strikes hard
Like many other organizations, educational institutions are under attack by the most active malware families, such as Emotet, TrickBot, and Ryuk, which wreaked havoc on organizations for the better part of the 2018–2019 school year.
Last May, the Coventry school district in Ohio had to send home its 2,000 students and close its doors for the duration of one day. The cause was probably a TrickBot infection, but the FBI is still busy with an ongoing investigation.
In February 2019, the Sylvan Union School District in California discovered a malware attack that made staff and teachers lose their connection to cloud-based data, networks, and educational platforms. Reportedly, they had to spend US$475,700 to clean up their networks.
On May 13, 2019, attackers infected the computer network of Oklahoma City Public Schools with ransomware, forcing the school district to shut down its network.
But it’s not just malware that educational institutions need to worry about. Scott County Schools in Kentucky paid US$3.7 million out to a phishing scam that posed as one of their vendors.
Unfortunately, that's money many school districts, especially those in impoverished communities, cannot afford to pay out. So when can they do to get ahead of malware attacks before valuable data and funding fly out the bus window?
Recommended reading: What K–12 schools need to shore up cybersecurity
Given the complex situation and sensitive data most educational organizations have to deal with, there are a host of measures that should be taken to lower the risk of a costly incident. Recognizing that many schools must divert public funding to core curriculum, our recommendations represent a baseline level of protection districts should strive toward with limited resources.
- Separate educational and organizational networks, with grades and curriculum in one place, and personal data in another. By using this infrastructure, it will be harder for cybercriminals to access personal data by using leaked or breached student and teacher accounts.
- DDoS protection. DDoS attacks are so cheap ($10/hour) nowadays, that anyone with a grudge can have an unprotected server taken down for a few days without spending a fortune. The possible scope of DDoS attacks has been increased significantly, now that attackers have started using Memcached-enabled servers. To put a stop to outrageously-large DDoS attacks, those servers should not be Internet-facing.
- Educate staff and students about the dangers they are facing and the possible consequences of not paying enough attention. Teachers can absorb cybersecurity education into reading comprehension lessons, and staff could benefit from awareness training during professional development days.
- Lay out clear and concise regulations for the use of devices that belong to the organization and the way private devices are allowed to be used on the grounds.
- Backups should be up-to-date and easy to deploy. Ransomware demands are high and even when you pay them, there is always the chance the decryption may fail—or never existed in the first place.
- Investing in layered protection may seem costly, but compared to falling victim to malware or fraud, the investments is worth it.
In fact, all of these measures will cost money and we realize that will need to come out of a tight budget. But funding, or the lack thereof, can not be an excuse for weak security. Cybercrime is one of the biggest chunks of the modern economy. And guess who’s paying for most of that? Those who didn’t invest enough in security.
What a strange paradox that one of the best weapons against cybercrime is education, but that organizations in education have the biggest problems with security. We at Malwarebytes, with the help of educational leaders, aim to change that.
Stay safe, everyone! | <urn:uuid:80fe7717-9987-4d24-8b49-a21ca96563c0> | CC-MAIN-2022-40 | https://www.malwarebytes.com/blog/news/2019/07/vital-infrastructure-education | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337524.47/warc/CC-MAIN-20221004184523-20221004214523-00556.warc.gz | en | 0.959189 | 1,422 | 2.9375 | 3 |
Malicious software used to perpetually block access to a computer system or specific data until a ransom is paid or indefinitely. Attackers often use ransomware to lock systems and then threaten to publish the victim’s data.
What is Ransomware?
Ransomware is malicious software used to perpetually block access to a computer system or specific data until a ransom is paid or indefinitely. Attackers often use ransomware to lock systems and then threaten to publish the victim’s data.
The most common ransomware infections use encryption technology to lock up data until a ransom is paid. Once encrypted, all access to the file or folder becomes impossible unless the user pays the ransom.
Threats of further damage usually accompany the demand for ransom payments if the victim does not pay. Criminal activity via ransomware has become a significant threat to businesses and individuals alike. Ransomware attacks are increasing in frequency and severity. In 2017, ransomware attacks cost businesses $5 billion globally.
In addition, more than 200 million users were affected worldwide. This article will provide an overview of ransomware, how it works, and why you should be concerned about this growing problem.
How Does Ransomware Work?
Ransomware attackers utilize a type of malicious software that locks your files and demands payment to unlock them. It's usually spread via a spam email attachment or links to websites that contain malware. Once installed, ransomware encrypts your data and displays an image of a locked padlock on your desktop.
Can Ransomware delete files?
Ransomware may also delete files, block access to your computer, or make it impossible for you to use your computer.
Ransomware can be used by criminals to extort money from users. If you pay the ransom demand, the criminals may unlock your files by sending you a decryption tool. However, if you don't pay the ransom, they could keep your files locked until you pay.
What can I do if my organization has been hit with ransomware?
Backup your files and data before you do anything else. Malware can cause irreparable damage to your system, so get rid of it by resetting your computer back to its factory settings. You may also want to consider external backup options if you're worried about losing everything.
Contact law enforcement and file a police report after a ransomware attack.
Paying the ransom is a bad idea. You may get your data back, but you risk losing your data forever. And paying the ransom encourages other criminals to engage in similar crimes.
While a ransom is demanded, there's no guarantee your data will be restored if you pay it.
How to Protect your Business and Network from a Ransomware Attack
Ransomware attacks are becoming more common, with businesses being targeted by criminals who demand money in return for unlocking data. Hackers that use ransomware will hold data hostage until they receive payment, so it's essential that you take steps to prevent this from happening to your company.
Cybersecurity experts agree that you want to prevent ransomware, not react to it, and you certainly want to avoid paying the ransom at all costs. This will only encourage cyber criminals to keep targeting your business.
Always make sure you patch and update your software and systems. This is a vital step when it comes to protecting your business data better. Ransomware will take advantage of any vulnerabilities, so be sure to keep an eye on updates. Educating your staff and clients about ransomware and how to detect phishing and social engineering schemes is another critical step. This will save your business time, money, and resources in the long run and help mitigate attacks before they even happen.
Make sure your organization has a suitable Business Continuity and Disaster Recovery (BCDR) plan in place to minimize any downtime, downtime event, or disruptions associated with ransomware attacks. A BCDR solution is still the best protection against the impact of ransomware. Building a successful BCDR plan takes time, effort, and resources but will serve you well in the long run. A good plan will enable your employees to continue to work throughout any disaster, connecting to recovered business systems from any location. Your data will be recoverable as you will have taken multiple backups to ensure you can go back to any point before your data becomes compromised. Finally, you will have peace of mind knowing you can get your client's businesses back up and running with minimal downtime or impact.
Although ransomware attacks are continuing to increase, they can be avoided with adequate protection.
Have solid cyber threat intelligence
Have daily backup files sent to a cloud or off-site location
Install anti-virus software
Patch as soon as updates are available
Use strong passwords
Be vigilant about attachments
Avoid Phishing Scams
Have security software that is proven to protect from major ransomware attacks
It’s important to keep in mind that reducing ransomware attacks starts with advanced cyber threat intelligence products and services.
Intel 471’s TITAN provides you with a global intelligence capability for human cybersecurity teams and machines. Whether scaling your cybersecurity presence or just starting to build your team, these tools and services can help you fight cyber threats.
For your IT / SOC / DevSecOps team, you can deploy Intel 471 Intelligence to gain up-to-the-moment threat coverage and analysis across Adversary, Malware, Vulnerability, and Credentials to gain better cybersecurity intelligence insights than you've ever had before. | <urn:uuid:7f1fe15a-0955-44f0-830c-15b3e66e7194> | CC-MAIN-2022-40 | https://intel471.com/glossary/ransomware | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338073.68/warc/CC-MAIN-20221007112411-20221007142411-00556.warc.gz | en | 0.930929 | 1,117 | 2.96875 | 3 |
Ever wonder why a CCTV camera has LED lights? What is their purpose in the recording process? And are there different types of LED lights for camera?
Cameras are just as blind as us. Therefore, they need a way to illuminate their surroundings when it is dark, so cameras are like our eyes!
During the day, we use sunlight to see, however, if we did not have light bulbs and electricity we would be left in the dark.
A CCTV camera has LED lights as their own light bulbs to be able to see and record footage in the dark.
Meaning, most cameras nowadays are able to record footage in a pitch-black room! Which can be useful for various situations.
However, a lot goes into how these LED lights that surround a camera work.
How they work
Cameras are great at capturing details in high quality and even helping authority identify suspects.
However, what happens when the sun goes down? Can security cameras see in the dark?
To begin the LED lights are called infrared lights and are used for security purposes. This is because infrared light is invisible to the naked eye.
Therefore, we cannot see it, however, it allows cameras to see us, which can be especially helpful when catching burglars and thieves on camera.
Since infrared lights are silent and invisible, they can be very discrete in filming and do not need a large lamp to provide light.
These infrared lights illuminate the camera's surroundings, therefore allowing it to make out objects and people in a gray scale.
This is possible because the light that bounces off objects then reflects back to the camera is recorded.
This makes recording footage at night easy as cameras automatically turn their infrared lights on when they need better lighting to record.
The infrared lights are not achieved with any normal LED that you find around your home, they are called IR LED. And can be found around the lens of the camera.
Their placement is specifically to make sure that the rim of the lens is illuminated, therefore capturing good footage.
These IR LEDs give off the infrared light only when needed and turn off during the day when light is available and can be used by the camera to record.
LEDs are also superior to other solutions such as attachable light sources. Additionally, they also consume less energy, therefore being more Eco-friendly too!
Why is infrared light used?
Security cameras are usually used to monitor a place from being robbed or to guard someone against stealing something.
Criminals usually steal and rob at night. There are fewer chances of someone seeing them, cars passing by, etc.
Therefore, having your camera being able to see at night can be quite helpful.
This invisible light that allows the camera to capture footage at night is very helpful in catching criminals as it makes the area clear enough for details to come through.
The only thing is that the images could not be in color at night as the light is not as powerful as the sunlight.
If the color is important to you, some sort of external light can be installed to enable the camera to now see the color around
Cameras that see in the dark can be installed in multiple places such as inside a bank vault that never gets sunlight.
Stores, offices, and companies have cameras both inside and outside. Some of the cameras get light during the day, others might get it at all.
Advantages of using infrared light
A CCTV camera has LED lights for the simple reason of illumination of the area when there is a lack of light. However, there is more to it than that.
For instance, these lights help minimize pollution and are the most Eco-friendly choice to illuminate the surroundings to record with cameras.
Apart from that, the infrared lights are also very powerful. They can cover long distances and illuminate them very well.
Additionally, these lights that are found in cameras allow authorities to enter scenes without being blinded, and the subtle red color that the lights give off lets them know the cameras can be checked as evidence.
Keep in mind that the closer objects and people are, the more detail they will have as they are next to the light source of the camera.
However, Infrared lights are not the only option that is found around a camera lens these days. So, what else could you invest in?
Keep in mind that the placement of the camera can seriously affect the footage. Pay close attention to the position and reach the camera has.
You should be aware that the camera can only illuminate the area for a set distance, therefore, you should buy a camera depending on the distance you're hoping to cover.
The further objects are from the camera, the less detail will appear. Therefore, the position of the camera is fairly important.
Meaning, if you want to monitor an area, place the camera in a position in which the area is close to the camera, so it is illuminated by the lights.
Have you ever heard that angles are everything when it comes to pictures? Well, it is the same with surveillance cameras.
A CCTV camera has LED lights for illumination, but to properly light up the area, the camera must be positioned at a good angle.
For instance, do not pick a narrow-angle. This will cause a spotlight in the middle of the area, therefore not giving you a good quality image.
There are additional features that you should keep in mind when choosing which lighting id right for you. Such as instant start.
This allows your camera to quickly switch to recording with the LEDs on as soon as you turn off the lights. Keeping you from missing anything that happens.
You should also pay close attention to whether the LEDs will resist different climates. These are usually found in higher-end products.
Other features include superior quality illumination. Which evenly spreads the light around the area. Therefore, gets rid of dark/ bright spots.
It should also not consume that much power. Some cameras are known for lower power consumption. But overall LED lighting is the perfect solution to illuminate an area.
Infrared LED lights
There are many advantages to picking Infrared lights. For example, they provide a greater distance, are invisible to the human eyes, and are very Eco-friendly.
Additionally, they are the most commonly used LED lights for cameras and they do not contribute to light pollution, which is very crucial.
They are great to keep intruders from realizing they are being recorded. And allow you to capture vivid and clear images with great details. Therefore, optimizing camera performance.
You can also install Infrared Illuminators next to regular cameras to use them at night. These can be bought inexpensively in sites like Amazon.
The white light illuminates the path for pedestrians are mostly used outside the residential area. They can also deter intruders when detected.
Also, provide images in color thanks to the strong LEDs. Images come out with high-quality and are visibly clear.
Additionally, they optimize color camera performance. and work 24/7, making it a powerful feature to have.
These LEDs can also be equipped with motion sensors and have amazing illumination capabilities. As well as avoiding bright and dark spots.
You might not want to invest in a camera with LEDs as you prefer to leave the lights on regardless. Do not worry, you can use one of the following:
Though their light is not ideal, they illuminate the area, therefore allowing it to record day or night. As long as you leave it on, there should not be an issue.
For CCTV purposes, these live too short of a life. Therefore making them a bit inefficient as they must be changed frequently.
Additionally, they are usually expensive to keep running and maintaining. Typically 500 watts to run and around 3 bulb changes per year.
The bottom line
In short, there are two main types of LEDs that can be used to record at night. A CCTV camera has LED lights to illuminate its surroundings.
This allows the camera to "see in the dark" and monitor 24 hours straight. Keep in mind there are many night/ day cameras in the market out there.
What do you prefer? Infrared or white light LEDs? Let us know down below. | <urn:uuid:03303470-7824-4151-9304-438df93fb82c> | CC-MAIN-2022-40 | https://learncctv.com/leds-around-a-cctv-camera/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338073.68/warc/CC-MAIN-20221007112411-20221007142411-00556.warc.gz | en | 0.96354 | 1,712 | 2.796875 | 3 |
Creating or Defining Data¶
This section is a general overview of how to define views or relations, which constitute the global schema of Virtual DataPort. All the tasks involved in the creation and administration of schemas will be described in detail in subsequent sections of this document.
To retrieve data from the different types of data sources, you need to:
Define a data source, which holds information about how to connect to a certain source: a relational database, a Web service, etc.
A wrapper, which extracts data from an element of a data source. For example, they can retrieve data from a table of a database or invoke an operation of a Web service.
A base view, which represent the data obtained by the wrapper.
After defining one or more base views, they can be combined, creating more views. Then, users can query these new views, obtaining data which are a combination of data obtained from different sources.
The following subsections describe these operations: | <urn:uuid:28ad7f54-d05c-4ca9-aa47-23c3f5b66fc5> | CC-MAIN-2022-40 | https://community.denodo.com/docs/html/browse/latest/en/vdp/vql/general_overview_of_virtual_dataport/creating_or_defining_data/creating_or_defining_data | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337287.87/warc/CC-MAIN-20221002052710-20221002082710-00756.warc.gz | en | 0.869893 | 199 | 2.6875 | 3 |
Technology is evolving so fast that it can be hard to stay on top of, and protect against, every type of potential threat. Hackers know this. That’s why they’re constantly creating new threats that are unknown to most anti-virus software.
Zero-Day Threats are cyberattacks that exploit weaknesses that are unknown to an IT team prior to the attack. This category of threats earns their name because there are “zero days” to plan ahead for them. This category of threats poses a unique set of challenges for organizations. Because these threats exploit weaknesses that IT teams aren’t aware of, they can often be hard to detect. Once the weakness is discovered, a patch may still be a long way off. From there, it could be even longer to deploy a solution, depending on an organization’s capabilities.
As cybersecurity continues to improve, zero-day threats are on the rise, as hackers look for new ways to circumvent your security system.
Zero-day threats, like other cybersecurity breaches, can cost your organization in a variety of ways. Your information could be stolen, both hurting your business and your reputation. Additionally, zero-day threats can damage your IT infrastructure and ultimately result in you needing to take your operation completely offline for a period of time.
Mitigating zero-day cyberattacks may seem like a challenge. After all, how can you protect against something if you don’t know that it’s there? Luckily, the right plan and software can go a long way toward keeping your organization free of a breach.
Preventing Zero-Day Threats
Preventing zero-day threats, like any other form of cyberattack, starts with strong software and education for your employees. Ensure that everyone on your team is using safe computer habits. Give them information on the kind of links that they should be wary of when they are online. Your operation’s internet browser is one of the most vulnerable spots for a zero-day breach to occur.
Make sure you have a layered protection system that is made to handle a variety of threats. This should include a firewall and scanners on your internet and individual machines. A firewall is a filter between your network and computer that will block known viruses from internet pages. A firewall can vary in size and can cover anything from a personal desktop to a whole local network system.
Security scans are another tool in the IT arsenal to keep out zero-day threats and other issues. These scans can be run on either your web browser or computer system and search for suspicious code. Scans won’t be able to catch many of the more complex zero-day threats, because the attacks are designed to not be similar to previous breaches.
While firewalls and scans can go a long way, the best method to stop a zero-day threat in its tracks is something called application control. Application control prevents all unauthorized programs, even ones that weren’t flagged as a threat by your firewall or are known to your system, from launching. This process is called whitelisting, because it involves only naming the applications you want to run, rather than all the ones that you don’t, like in blacklisting. The intense security of application control delivered by products like Faronics Deep Freeze should stop any zero-day threats since it makes the malware’s lack of negative identification irrelevant.
Employing consistent application control may be difficult for some organizations, however. Your organization may depend on a wide variety of applications to function at full capability, and blocking all of them at once may be unrealistic.
What To Do Once A Threat is Discovered
Even if you do all of the right things, sometimes a threat can still occur. If it does, the key is to do all that you can to mitigate the damage. Ensuring that you have detection services in place will be key. Otherwise, a breach may exist for an extended period of time before you catch it.
Once a threat is detected, be sure to uninstall any software that isn’t completely essential to your operation. This will help to stop the spread of any viruses. In more extreme circumstances, taking your operation completely offline or putting your website in maintenance mode may be necessary. These moves will give you time to work on a patch without allowing the issue to spread, preventing extra harm to your system. While going offline may be inconvenient, and may hurt financially, it can also save you headaches down the road.
Software That You Can Trust
Ultimately, taking preventative measures against zero-day threats, while challenging, is extremely worthwhile. Software from Faronics can be a large part of the solution. Deep Freeze’s instant restore functions not only are a great way to cut down on IT tickets, it can be an essential piece of your security strategy. The software functions as whitelist by bringing your computers back to the settings that you specify with the click of a button. Deep Freeze has capabilities that range from a single desktop to thousand of work stations. That means that whatever the size of your operation, protection from zero-day threats is possible. | <urn:uuid:239ebf4a-12a7-4511-89aa-38ea32c4b6fe> | CC-MAIN-2022-40 | https://www.faronics.com/news/blog/an-it-admins-guide-to-securing-systems-against-zero-day-threats | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337421.33/warc/CC-MAIN-20221003133425-20221003163425-00756.warc.gz | en | 0.941893 | 1,047 | 2.6875 | 3 |
Written by Guest Contributor: Carla Lopez
The internet makes life easier in many ways. From online shopping to remote learning and working from home, all kinds of tasks are simplified when you can get online. However, the internet also opens people up to new threats. IP Services provides cybersecurity services and resources to help individuals and business owners protect their data from cybercriminals. The below guide provides a quick introduction to cybersecurity for beginners.
What Cybersecurity Means For You
Many people assume that cybersecurity is only an issue for major corporations and big businesses. In fact, everyday individuals and smaller companies are frequent targets of cyber attacks. This is precisely because they tend to be less concerned with cybersecurity and don’t exercise proper precautions, making them easy targets. Cybersecurity measures can help you prevent theft and damage of data, personal information, and more.
The first step in combating cybersecurity in your home or business is understanding the risks. Frequent sources of risk include malware, emotet, denial of service, SQL injection, and phishing. This guide from Online Degrees explains what the terms mean and how to recognize them. For example, phishing attacks usually come in the form of fake communications like emails that seek to steal your data, like credit card information.
Steps You Can Take To Stay Safe Online
As an individual, the small steps you take in your everyday online and technology habits can help protect you against cybersecurity risks. Start by making sure your WiFi network for your home or business is secured with a strong password. Also, change the password every few months for added safety. You may also want to add a personal firewall. PCMag explains that this adds another layer of protection to your WiFi network.
When selecting a password for your WiFI, make it a strong one. Steer clear of easy-to-guess codes that incorporate readily available data like your name or address. Also, make sure your passwords incorporate letters, numbers, and symbols. You can use these rules of thumb when setting passwords for your technological tools like phones and laptops as well. They are also applicable when setting passwords for online accounts.
You can further protect your devices by always updating them. Most operating systems will send you a notification when it’s time for an update. While it can be tempting to ignore those alerts and move on with your day, this is a recipe for disaster. These updates often contain modifications to address security concerns, so it’s important to take advantage of them. Failing to do so opens you up to predators.
Additional Considerations For Business Owners
Business owners have additional considerations when it comes to cybersecurity. A data breach can cause significant damage to your brand, for example, if sensitive company data or customer details are leaked. You may also lose productivity, money, and valuable time, as you have to recover data. ZenBusiness explains that you may even be held liable in case of security leaks that impact your customers.
In addition to following the above cybersecurity tips, communicate best practices to your employees. Provide IT guidance on things like setting passwords to ensure everyone is aware. Further, small businesses are advised to have a disaster recovery plan. This is a set plan you can execute to recover data and minimize risk if your business is the subject of a cyber attack. For example, it could cover points like how you backup your documents.
Finally, keep the cost of cybersecurity solutions in mind. Hiring and training an internal team is a huge expense. Because digital threats and the solutions for combating them (like artificial intelligence programs) are constantly evolving, businesses spend a lot of money keeping their internal experts up to date. Typically, small companies should look externally for companies that specialize in cybersecurity and that bear the burden of these ongoing costs themselves.
The digital world is full of possibilities and makes everyday life easier in many ways. However, it can also present risks. Educating yourself about potential threats is the first step in protecting yourself. The above guide can help.
For more tips and tricks for exercising good cybersecurity practices, check out the IP Services blog. You’ll find useful content for individuals and businesses alike. | <urn:uuid:fdb7f882-2e48-448c-b716-dab22a5b260b> | CC-MAIN-2022-40 | https://ipservices.com/2022/02/23/a-beginners-guide-to-cybersecurity/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337529.69/warc/CC-MAIN-20221004215917-20221005005917-00756.warc.gz | en | 0.936235 | 839 | 3.28125 | 3 |
You are probably accustomed to using what is called decimal- the numbering system you’ve been learning since kindergarten. In networking we use three primary numbering systems: binary, decimal, and hexadecimal. It is direly important to know what each numbering system is for, and more specifically how to convert from one system to another. But don’t worry; it’s easier than you might think.
An Introduction to Binary
Binary is short for binary digit. If you know your prefixes well, you know that bi simply means two. The best part of binary is that it only has two numbers in it: one and zero. This is what we call machine code, since it is the language that powers most hardware and computers.
The premise of binary is simple: we arrange 1’s and 0’s in a row to make any number we please. Each one or zero is called a bit, and are commonly arranged in groups of 4 (called a nibble) or 8 (called a byte).
So why use 1’s and 0’s instead of real numbers? The answer is simple: computers are dumb devices. To understand and process data, they use electrical signals. A binary 1 (usually) indicates that there is a high voltage level, and a binary 0 (usually) indicates a low voltage level. This is how computers can send and receive data- although however crude it may be.
Thus, the thought is burning in your mind: how do you make a decimal equivalent of 45 with 1’s and 0’s? Binary works on a rather different numbering system than you are probably used to. Each position in a byte corresponds to a number.
If you haven’t noticed, each position in a byte is double the value of the position before it. This way, we can make any number up to 255 with each byte. If you wanted to know the function to find the value in decimal, with the given position in the byte, you can use 2^n (where n is the position). Note that the position count starts with zero. So if the position was the second right hand number, the equation would be 2^1.
To get 45 in particular, we need to review one last concept. Consider each 0 as a “no” and each 1 as a “yes.” For every binary 1 (or yes) you get, you write down the corresponding decimal number. For each binary 0 (or no) you get, you don’t write down anything. Now add up all the decimal numbers you got, and you have the decimal equivalent of a binary number.
When you are instead converting a decimal number to binary, it is generally quickest to ask “What’s the biggest number I could take out of 101?” In our case, it is 64. So likewise, we start with 64 and continue our way down with “What’s the biggest number I can take out of 37? (101 – 64)” This is done until the number required is obtained. For every decimal number we wrote down, we consider its position a binary 1. If the number wasn’t used, we consider the position a binary 0.
Keep in mind that Cisco makes a note of describing a byte as a single addressable data storage location. And by all means, this is completely true- expect to see it on Cisco exams.
Now that you know how to convert decimal to binary (and binary to decimal), we can move on to the wonderful world of hexadecimal!
An Introduction to Hexadecimal
Whereas decimal is a base 10 numbering system (since it has 10 total numbers 0-9), and binary is base 2, hexadecimal is base 16. But, you might ask, how is it possible if there are only 10 numbers? Easy- we use letters A through F to make up for the 7 missing numbers.
Remember how we used bytes to work with binary and decimal numbers? This time around we will use nibbles when working with hexadecimal. The numbering scheme is actually quite easy once you get the hang of it.
To convert a hexadecimal value to binary, remember that we are dealing with nibbles, not bytes. Each number (or letter) corresponds to a nibble. Therefore, the hexadecimal number AF converts to a 10 and a 15. The result, in binary, would be 1010 1111 (consult the diagram above).Now we can finally convert the byte into a decimal number. When we add all the digits up, the binary number 10101111 becomes 175 in decimal. Note that since hexadecimal numbers can easily be confused with decimal numbers, you will more than likely see a 0x before a hex number. In our previous example, it would be 0xAF.
If we want to instead convert a binary number into hexadecimal, we do the opposite. Break the byte into two nibbles, and then find the value of each nibble. Convert the value of each nibble into hexadecimal, and you get your final result. The binary number 1111 0001, for instance, would be the equivalent of F1 in hex (or otherwise known as 0xF1). Then of course, we could add the binary digits up and get 241 for the decimal equivalent.
Now, you’re probably thinking, “When will I ever use hexadecimal? I’ve never heard of it before!” Chances are, you’ve already come into contact with it. HTML and CSS both use hexadecimal numbers for color codes. The network interface card you are using to view this webpage right now has a physical address coded in hexadecimal. And if you have a funny bone, there are some clever jokes associated with hexadecimal. Can you see the logical flaw in the diagram below?
Most mathematicians would say a zero multiplied by anything is zero. That’s true, but the deception here is that it isn’t a zero at all! It’s actually the beginning of the hex value of 12, which is the equivalent of 18 in decimal.
And if you were wondering if there were any binary jokes, rejoice. The phrase “There are only 10 kinds of people in the world; those who understand binary and those who don’t” confuses the reader with a decimal 10, only it is actually a binary 2. Clever, isn’t it?
You now have what it takes to be the world’s next network mathematician. We covered a lot, however, so practice converting to and from all of the above numbering systems is quite necessary. Expect to see this type of math not only in your future networking studies, but on Cisco exams as well. | <urn:uuid:f2f831bf-2ef3-4e6e-af3f-cdc20b3699f3> | CC-MAIN-2022-40 | https://www.itprc.com/guide-to-network-math/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338213.55/warc/CC-MAIN-20221007143842-20221007173842-00756.warc.gz | en | 0.911636 | 1,431 | 4.46875 | 4 |
SQL injection is the code injection techniques to gain access to the database(MySQL, MSSQL, Oracle etc).Owasp 2018 Release still describes this injection as A1 or Level 1 injection which is most dangerous attack over all the time.
SANS Top 25(Most Dangerous Software Errors) describes SQL injection as Improper Neutralization of Special Elements used in an SQL Command (‘SQL Injection’) as Rank 1 of Injection.
The automation of this injection can be performed with a large number of tools available on the internet.Better than tools Human have creative thinking and decision making to understanding the target, so I preferred to go with manual penetration.
NOTE: Scope of this SQL injection only for backend MySQL database.If you test the same with Oracle or some other databases it never works.
SQL Injection ONLINE LAB:
- Beginners can use this website to practice skills for SQL injection
- To Access the LAB Click Here
- Above Screenshot will be your successful welcome screen.
STEP 1: Breaking the Query
- Visting the website http://leettime.net/sqlninja.com/tasks/basic_ch1.php?id=1
- Let us add & check single quote to existing URL to check whether the website is vulnerable to SQL Injection by adding http://leettime.net/sqlninja.com/tasks/basic_ch1.php?id=1′
- After adding single quote If the website shows error statement “You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near ”1”’ at line 1
- That’s Great !!! It is Vulnerable to SQL Injection
- This Illustrates you have successfully Broken the query & Backend Database is interacting to Hacker with error messages.
STEP 2: Copying the Error Statement
- Copy and Paste the SQL Error statement into Notepad.
- After copying Perform actions to error statements as mentioned in below screenshot
- Above figure Illlustes that Highlighted single quote is breaking the backend database
- Now Imagine yourself as DEVELOPER and Guess the SQL statement in Database.
- Hope everyone has Guessed the backend query looks like this Select username, Password from table where id =’1′
- When we add single quote which is mismatching the query like this Select username, Password from table where id =’1”
- This is called as Single quote error based string injection.
STEP 3: Joining the Query
- Let us add –+ to join the query http://leettime.net/sqlninja.com/tasks/basic_ch1.php?id=1′ –+
- Above figure illustrates SQL errors are fixed with –+
- Whatever malicious code placed will talk with database and as of now you have successfully broken the query, joined the query and finally found out it is Single quote error based string injection.
STEP 4: Finding the Backend Columns
- It is time to have a conversation with the database to find the number of columns.To enumerate columns we can use order by command.
So above figure illustrates with no SQL errors, meaning there is 1 column in the database.
- Let me check with rest of columns with order by 2, order by 3 etc.
So above figure illustrates with no SQL errors, this shows still 3 columns are present in the database.
- Let me check with one more column with order by 4
Above Figure shows Database with error statement Unknown column ‘4’ in ‘order clause and this error statement says as “There are only 3 columns in database”.Hope you understand how to talk with a database with errors.
STEP 5: Finding the Backend Tables
- SQL backend may contain more Tables names with empty data also.Therefore You should first able to find out which table names are present in this 3 columns.
- Now we can select all 3 columns with union all select to existing URL http://leettime.net/sqlninja.com/tasks/basic_ch1.php?id=-1′ union all select 1,2,3 –+
- Above Illustrated Figure shows Username is: 2 as the value which represents table names is present in the 2nd column of the database. Now we have successfully found out the table location in Database.
STEP 6: Finding the Backend Table Names
- We already knew the location of table path, so will directly ask database name, version etc
- Above Illustrated Figure shows Backend Database reveals its database name:leettime_761wHole
- Let us do the same to check out database version details with version()
- Above Illustrated Figure shows Backend Database version: 5.6.36-cll-lve
STEP 7: Dumping Database Tables
- Group_concat() is the function returns a string with the concatenated non-NULL value from a group.
- So we can use this Function to list all Tables from the database.
- In Addition, we can use Information_Schema to view metadata about the objects within a database.
- The Above Figure shows the dump of all tables as testtable1, user logs, users.
STEP 8: Dumping all Data in Columns of Tables
- Here I will dump for users in table.
- The Above Figure shows the dump of all columns of tables contains id, username, password,user_type,sec_code
- Here Usernames and Passwords are most confidential one.so let us dump !!!
STEP 9: Dumping all Usernames
- Here we can dump all usernames in the database.
- The Above Figure shows the dump of all usernames injector, decompiler, devil hunter, Zen, Zenodermus, grayhat, khan, admin
- If I get the credential for admin account that will be great!
STEP 10: Dumping all Passwords
- Now we can use the group_concat function to call password from users.
- The Above Figure shows the dump of all passwords for users : Khan,hacktract,dante,sec-idiots,security-i, hacker, haxor, sadmin
- We got the admin accounts password as sadmin ! Happy Hacking !!! | <urn:uuid:2eceebc3-c625-4645-ab88-ef396598b48a> | CC-MAIN-2022-40 | https://gbhackers.com/manual-sql-injection/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334596.27/warc/CC-MAIN-20220925193816-20220925223816-00156.warc.gz | en | 0.820697 | 1,342 | 3.140625 | 3 |
XChaCha20 Encryption vs AES-256: What’s the Difference?
Encryption is the foundation of online data security. It closes off confidential information from outsiders and ensures that only the owner and intended recipient can see it. This article will give you a glimpse into two leading encryption algorithms - XChaCha20 and AES-256. Read on to learn how they work, how they differ, and which is better.
What is AES Encryption?
AES is a type of symmetric encryption (meaning that a single encryption key is used to encrypt and decrypt the data). It has become the most popular type of encryption used even by the US government.
How Does AES Encryption Work?
AES uses a block cipher to encrypt data. It divides a given set of information into blocks of 128 bits (or 16 bytes) and encrypts each block separately. While the block size is always the same, the key length varies. Currently, AES comes in 128, 192, or 256 bit encryption. The more bits, the more possible key combinations and, therefore, the more secure the encryption.
One round of encryption consists of 4 steps, and each data block goes through several rounds of encryption. For instance, AES 256-bit encrypted text goes through 14 rounds of encryption. Once the encryption process is done, it can be securely sent over the web, and only those who have access to the encryption key will be able to decrypt and access the data. Otherwise, the encrypted data is completely useless.
What is XChaCha20 Encryption?
XChaCha20 is a 256-bit stream encryption type. Like AES, it is symmetric and uses a single key to scramble and unscramble data. (Although there’s also an asymmetric version of it).
So what exactly does “stream” encryption mean? Well, instead of dividing data into blocks, XChaCha20 ciphers each bit of data separately. This makes the process much quicker and less complex than with AES. Some argue that this makes XChaCha20 a better choice than AES, but let’s take a closer look at the two in the following section.
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Difference Between XChaCha20 Encryption and AES
In the table below, you can see a breakdown of the differences between the two types of encryption:
For the sake of simplicity, we’ll compare the 256-bit versions of both encryption algorithms. The long encryption keys no doubt make both of these very sturdy sets of encryption. They’re both better in terms of security than any of their counterparts that use shorter encryption keys. However, there’s much more to encryption than key length.
The main difference between AES-256 and XChaCha20 encryption is that AES-256 is a block cipher, whereas XChaCha20 is a stream cipher. Also, AES encryption has built up quite a reputation (hence why it’s called the “advanced encryption standard”), while XChaCha20 is still fairly new.
However, the process of AES-256 encryption is a bit more complex than that of XChaCha20, which comes with several drawbacks:
The more complex the algorithm, the more likely someone is to mess the process up and put data at risk.
AES-256 requires special hardware acceleration to run smoothly, while XChaCha20 runs perfectly fine on software. For instance, Intel, AMD and newer generations of ARM processors support AES. Whereas, older generation processors usually installed on entry-level Android devices such as Android Go phones, smart TVs, smartwatches don't have built-in hardware acceleration support for AES encryption.
Without special hardware, AES-256 can be several times slower than XChaCha20.
Which is better?
Well, both have their pros and cons. However, the speed and simplicity of XChaCha20 and the fact that it doesn’t need any hardware to run smoothly are swaying more and more companies (even Google!) to choose it over AES.
Here at NordPass, we recognize the need to stay ahead of the market and offer our customers only the best technological solutions. That’s why we’ve chosen to use XChaCha20 encryption for our password manager. It’s more than likely that even more companies will follow suit in the future.
Both AES-256 and XChaCha20 do a great job at ciphering and securing data. However, XChaCha20 clearly has its advantages over AES in terms of simplicity and speed.
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Get the latest news and tips from NordPass straight to your inbox. | <urn:uuid:974afac4-dc04-4f49-b76d-791d48e04a53> | CC-MAIN-2022-40 | https://nordpass.com/blog/xchacha20-encryption-vs-aes-256/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334987.39/warc/CC-MAIN-20220927033539-20220927063539-00156.warc.gz | en | 0.933808 | 1,007 | 3.0625 | 3 |
Network management questions around WAN optimization are answered in this article presented on Webopedia. Ideally, a WAN solution will allow you to prioritize traffic and guarantee a certain amount of available bandwidth for mission critical applications. A complete WAN optimization solution allows a business to block unwanted traffic, give priority to certain hosts, and provide lower latency and higher throughput for the most critical applications.
“One optimization technology, VPN tunneling or Virtual Private Networks (VPNs) and Multiprotocol Label Switching (MPLS), is used to avoid packet delivery issues in shared WAN environments. This technology enables one network to send its data via another network’s connections. Tunneling works by encapsulating a network protocol within packets carried by the second network. This WAN optimization technique is important for any business that transmits business-critical data over a public network.” | <urn:uuid:878da62c-3560-4c21-a7c9-be57c90bc057> | CC-MAIN-2022-40 | https://www.enterprisenetworkingplanet.com/news/understanding-wan-optimization/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335530.56/warc/CC-MAIN-20221001035148-20221001065148-00156.warc.gz | en | 0.876693 | 178 | 2.640625 | 3 |
When we hear about data centers “going green” and implementing sustainability measures, we usually think about reducing carbon emissions – and for good reason. Data centers use massive amounts of electricity, and the indirect carbon footprint involved with building and equipping them is impacted through the consumption and fabrication of raw materials throughout the entire upstream supply chain. According to the US Department of Energy, data centers account for roughly 2% of energy consumption in the US, and just over 1% of energy consumption globally. Although data centers have made progress in moving to renewable forms of energy, a substantial portion is still generated from burning fossil fuels. According to SuperMicro’s 2021 Data Centers and the Environment report, data centers are responsible for 2% of the world’s greenhouse gas emissions.
As important as reducing carbon emissions in data centers is, it is not the only sustainability issue that warrants attention. Another environmental factor that often gets overlooked when it comes to data centers’ ecological impact is gratuitous water usage.
Using Energy Means Consuming Water
Data centers use a lot of water. In 2015, it was estimated that a 15MW data center consumed roughly 130 million liters of water per year, roughly the same amount as a hospital with three buildings or a 100-acre almond orchard. And that’s just one data center. Multiply that by thousands of data centers all over the world, and you’re looking at billions of liters of water used to reject IT heat load, every year. According to some estimates, data centers consumed over 660 billion liters of water in 2020 alone.
Most of the water consumed by data centers is used to generate the electricity upon which these facilities depend. We all know that the majority of electricity we use is generated by fossil fuels. But few seem to realize that power plants use these fossil fuels to heat water, generating steam to turn the turbines that ultimately create the power. In other words, if you are using a significant amount of electricity, you are also de facto using a significant amount of water.
Power Usage Effectiveness
Data centers need power to operate. But not all of the power they use goes to running servers and other IT equipment. In fact, up to 40% of that power goes to cooling the data center. Servers generate heat and stop working when they get too hot, or when there are rapid temperature or humidity swings. Data centers therefore have to invest a lot of money and resources towards keeping servers cool enough to function. The most common type of cooling is air cooling, which relies on large air conditioning units that continuously blow cold air near the servers. (Otherwise known as the “Cold Aisle”.)
Needless to say, this is a very ineffective cooling method when you consider the environmental impact. To put this in perspective, a data center’s energy efficiency is calculated in Power Usage Effectiveness (PUE), which is a comparison of the amount of energy used by both the IT equipment and the facility, divided by the IT consumption figure. So, a PUE of 1 means that, in essence, no energy is wasted; all the energy goes to the IT equipment, none to the facility.
Air-cooled facilities can have a PUE as high 2 or even higher. This means that 50% of the energy used by the data center is wasted – that is, it goes to the facility itself, not IT services. Due to improvements in air cooling design and best practices, the average data center PUE is now 1.59 according to the Uptime Institute’s 2020 report. As we mentioned before, the electricity used to run these air cooling systems comes from power plants that not only emit a lot of CO2, but also use a significant amount of H2O.
Water Cooling Methods
Many data centers use chilled water as a cooling method. Data center owners and operators long ago turned to water for cooling because it is more efficient at heat removal than mechanical air conditioning. Water is used to cool servers by pumping it through cooling coils located adjacent, above, behind or near IT racks. Although in this case water is the heat transfer fluid, the heat exchange is still air-to-air.
Water can also be used to cool IT gear by pumping it through highly customized liquid cold plates that are mounted onto each microprocessor chip. This is known as direct liquid cooling (DLC). Using liquid cold plates to reject the heat generated by the dominant heat loads on the IT circuit board can successfully remove up to 70% of that heat. However, traditional air cooling is left to deal with the balance, which still burns a lot of carbon, consumes a lot of water, and leaves you with a complex series of piping, manifolds and tubing to deal with.
2-Phase Immersion Cooling Reduces Water Usage
Air and water cooling are both common methods of cooling in data centers, but they are far from ideal and are hitting the limits of their efficacy. The exponentially growing demand for data streaming brought on by the COVID-19 pandemic, combined with new data-intense technologies such as artificial intelligence (AI), IoT, 5G, high performance computing and cryptocurrency mining, require cooling capabilities that reach beyond the limits of air cooling and direct liquid cooling methods.
Simply put, above 300 watts per chip, air cooling becomes not only challenging but highly impractical and inefficient. There are GPU servers still being cooled with air, however these boxes can tower up to 10U high due to the extreme size of the heat sinks and fans required to reject the heat from the server. Further, a 10-12kW GPU server often sits isolated in its own rack with 80% of the other rack space units occupied by blanking panels and sometimes with an empty rack standing adjacent – this is known as “load spreading.” Most data centers are designed to cool with air at just 8-9kW per rack. A high-powered GPU server can necessitate limiting the IT load nearby, otherwise the air cooling system just can’t keep up with the demand.
2-phase immersion cooling is a game-changing technology that provides the cooling capability necessary to enable the use of advanced, data-heavy technologies while drastically reducing power consumption and, by extension, water usage.
With 2-phase immersion cooling, servers are immersed in a dielectric (nonconductive) fluid. The fluid absorbs the heat generated by the servers until it reaches its boiling point. The transition from liquid to gas is called a phase change, hence “phase one” of the process. This is a powerful mechanism because, as more heat energy enters the system, rather than raising the temperature of the fluid, it instead converts the fluid to gas. As a result, the electronics and surrounding fluid remain at a fairly constant temperature and the heat from the electronics can be transferred to an outside liquid loop without consuming appreciable amounts of energy.
The second phase change in 2-phase liquid immersion cooling is that of the gas changing back into a liquid thanks to a condensing coil placed just above the fluid. Condensed fluid collects on the coil then falls back into the tank, where the cycle is repeated continuously. No additional coolant pumps are required because the process is self-contained, and the fluid itself rarely has to be maintained or replaced. If IT gear is removed from the DataTanks™, the fluid evaporates quickly and cleanly, making the IT equipment very easy to service. While this is a concern with regard to potential fluid loss, LiquidStack has developed patented technology to drastically minimize this risk.
Another factor in water savings is that dry coolers, as the name implies, do not need to evaporate water to reject heat. A dry cooler is a closed-loop outside heat rejection system consisting of radiator coils and fans. Because 2-phase immersion cooling keeps primary loop fluid temperatures of 53°C or higher, dry coolers are able to easily and efficiently reject that IT heat load with free cooling even in the warmest, most humid, most challenging ambient environments in the world.
When data centers no longer rely on air conditioning or chilled water to cool their servers, they can operate at a much lower PUE. For example, by using 2-phase immersion cooling, data centers constructed in Hong Kong, the Republic of Georgia and Azerbaijan, some of the warmest climates in the world, operate at PUEs of 1.02 to 1.03, an order of magnitude better than a majority of air-cooled data centers.
In addition to limiting or eliminating direct water usage, 2-phase immersion cooling further saves on indirect water usage by reducing overall data center energy consumption. Reducing the consumption of local water resources also has a beneficial impact on local ecologies and communities.
Inadequate water supplies can lead to reduced food supplies and rising food costs. The need for fresh water is always increasing due to population growth, and using less of it reduces the potential effects of droughts and water shortages. Conserving water reduces the energy required to process and deliver it to homes, farms, and other businesses, further reducing carbon emissions and conserving fuel resources.
While the headline may be that 2-phase immersion cooling drastically reduces greenhouse gases, the reduction in water usage is also a valuable benefit to the planet and to any organization’s bottom line. | <urn:uuid:b5d15138-4fe0-4bd7-91cd-a46a2bae3a74> | CC-MAIN-2022-40 | https://liquidstack.com/blog/immersion-cooling-results-in-tremendous-water-savings | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337322.29/warc/CC-MAIN-20221002115028-20221002145028-00156.warc.gz | en | 0.945885 | 1,911 | 3.65625 | 4 |
Tokenization and encryption are two of the most popular data security methods. And while they are often used in conjunction because they disguise personal and sensitive card data and reduce data exposure, they are not interchangeable terms.
When choosing between the two security techniques to protect your data, you have to consider specific factors. Below, we’ll explore tokenization vs. encryption in more detail, as well as outline the differences to help you pick the right data security method for securing sensitive data.
What Is Tokenization?
Tokenization is the process of turning a meaningful piece of data into a random string of characters known as tokens.
A token has no meaningful value and only serves as a substitute for the actual data. What’s more, tokenization doesn’t use a cryptographic method to transform sensitive information into ciphertext, meaning you cannot use the token to guess the original data in case of a data breach.
Imagine an online business accepting payment from a customer using a third-party site like PayPal or Stripe. In this case, the third-party site can disguise the credit card number with other characters (tokens) to protect the customer’s card information. As a result, the business will only see that tokenized information and won’t have access to the actual card number.
Advantages of Tokenization
According to Statista, 540 data breaches alone took place within the first half of 2020. When you collect consumer data, you’re responsible for ensuring its protection. But when you use tokenization software, data gets stored in a third-party database, reducing your in-house responsibility of managing sensitive data. You also aren’t required to maintain the staff and resources needed to protect the collected data, nor are you as likely to reveal that data if you suffer a breach.
Tokenization is a time- and money-saving method, too. While it doesn’t eliminate Payment Card Industry Data Security Standards (PCI DSS) and other compliance requirements, converting the form of vulnerable data effectively reduces your team’s need to prove compliance. As you work with simple software tools and tasks to ensure compliance, you end up saving a lot of valuable time and money.
Disadvantages of Tokenization
Implementing tokenization does certainly add a layer of complexity to your IT structure, with processing transactions becoming more complicated and comprehensive.
It also doesn’t eliminate all security risks. When choosing a vendor to store data, you need to be very careful and ensure they have the appropriate systems in place to protect your data.
Moreover, only a limited number of payment processors support tokenization, which means you’ll either have to change your systems to accommodate this method or opt for a payment processing tool that may not be your first choice.
What Is Encryption?
Encryption is the process that uses mathematical algorithms to transform plain text information or sensitive data into unreadable information called ciphertext, which is generated using an encryption key. To make the text readable again, you would require an algorithm and a description key.
Suppose a company collects personal information like phone numbers, email IDs, and mailing addresses of its customers. It can use ciphertext to protect all information, so it’s only accessible by using an encryption key.
Advantages of Encryption
Through encryption, you can protect a variety of data types, including credit card information, files or emails, and Social Security numbers. While tokenization is more suitable for smaller pieces of data, you can safeguard full documents by encrypting the stored information.
The encryption process uses algorithms to secure data, which makes it faster. Tokenization takes much longer because each character or number is changed into a random character.
Encryption also allows you to share decryption keys with others or access files remotely—all without having to worry about security vulnerabilities. With tokenization, you would have to find a secure way to share your original information for the receiving party to decipher the token. However, with encryption, all they will need is the decryption key.
Disadvantages of Encryption
All data is encrypted using a single key in encryption, so if hackers gain access to that key, everything encrypted using the key becomes vulnerable. This can be an entire database or a single file, depending on whether the encryption is full disk or file-based. Regardless, this can be a significant blow to your IT security.
The other disadvantage is that encryption also hinders software functionality.
It’s possible for the ciphertext used to encrypt data to not be compatible with other software tools, hindering the functionality and value of those applications. You may also have a limited number of vendors to serve your software requirements.
Tokenization vs. Encryption: Exploring the Main Differences
Now that you have a clear understanding of what both terms mean, let’s explore the main differences between the two concepts.
Encryption scrambles your data using a process that’s reversible—provided you have the correct decryption key. You can encrypt your plaintext into ciphertext, which is then transmitted to the recipient, who can decrypt the ciphertext back into plaintext.
Under tokenization, two distinct databases are created: one having the actual data and the other with tokens mapped to each character of the presented data. A tokenization software randomly generates a token value for plain text and stores the mapping in the database. While the process is closely related to encryption, tokenization is irreversible.
Encryption has two primary approaches: symmetric and asymmetric. Symmetric key encryption involves using a single key to encrypt and decrypt data. If the key gets compromised, it will unlock all the hidden data. On the other hand, asymmetric key data uses two different keys—one for encryption and another for decryption. This way, multiple parties can exchange encrypted data without managing the same encryption key.
Tokenization uses tokens to disguise sensitive data or information by replacing the token value with the actual data to allow users to access the original data. The tokens authorize the user or the program to ask for the data, pull the correct token from the token database, and recall the actual data from the database before presenting it to the user or program.
Encryption is a reliable component of payment processing. Without a key to decrypt data, accessing encoded information will always fail. However, you must regularly rotate keys to protect payment information.
On the other hand, a token is a substitute for the information it represents, where participants don’t have to handle credit card information directly. A device-specific or merchant-specific token creates an additional security layer, and it’s possible to deactivate a compromised token in real-time with little to no impact on the customer.
The good thing about encryption is it can provide adequate support for scalability by encrypting large data volumes via mathematical algorithms.
On the contrary, tokenization can present considerable difficulties in disguising data at scale. If you try to tokenize large files or pieces of data, it’ll likely create latency issues, rendering the whole process ineffective.
PCI compliance warrants the safety of payment information as it mandates organizations to apply strict payment industry standards.
Meeting PCI encryption standards can take up a lot of resources and increase operating costs significantly. Contrarily, tokenization reduces the associated cost of PCI compliance as merchants don’t have to handle payment information directly.
Note: Although the tokenization process isn’t a PCI compliance requirement, it’s still considered an established practice in payment processing.
Without encryption, sharing payment information over exposed networks and storing card information is very dangerous. For instance, an ATM may not safely communicate with remote systems and validate card information, creating vulnerabilities.
It’s also widely used to protect communication from individuals and organizations from malicious hackers, as well as safeguard information stored on mobile devices.
Besides protecting payment card data, bank account numbers, email numbers, and so on, you can use tokens to simplify checkouts to drive sales. Customers can use their tokenized data to make purchases without entering their personal data or using their credit cards. Here are a few examples:
- In-app payments: Customers can use mobile apps to pay without closing or exiting the app.
- Digital wallet: Customers can create a token and use their mobile device or wearable to pay for services or goods.
- Recurring payments: E-commerce platforms and merchants commonly store customer tokens to initiate recurring payments without accessing or storing the customer’s card information.
- Pay buttons: Merchants can add pay buttons to their websites to allow customers to pay using previous tokens.
The above examples highlight how tokens make payment processing easy and convenient. In turn, this makes it more likely for customers to go through with their orders.
Tokenization vs. Encryption: What’s the Best for Your Business?
To decide between the two data security techniques, you have to answer a few critical questions:
- Which type of industry are you in, and is your company always prone to data breaches and hacking attempts?
- Are you looking to protect numbers like credit cards and account numbers (tokenization) or entire databases (encryption)?
- Which option would make it easier for you to comply with data security policies?
- Which option would be more feasible based on your budget?
- Based on your company size and customer base, how would tokenization or encryption benefit your company?
While the above are excellent guiding questions, we would recommend using both techniques together— tokenization and encryption—whenever possible. As both the methods are not mutually exclusive, you can employ them together to cover the other’s drawbacks and enhance your company‘s overall data security levels. | <urn:uuid:de7c38a0-5c5c-4bdc-b926-3e31eafa3730> | CC-MAIN-2022-40 | https://nira.com/tokenization-vs-encryption/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337322.29/warc/CC-MAIN-20221002115028-20221002145028-00156.warc.gz | en | 0.905077 | 2,021 | 2.890625 | 3 |
As the COVID-19 pandemic set in and students and telecommuters were forced to work from home, suddenly the lack of access to affordable and reliable high-speed internet — one component of the digital divide –became more apparent. Given the heightened focus on those who did not have access to high-speed internet, in 2020 several states and cities began using American Rescue Plan Act (ARPA) funds to increase broadband access.
Aimed at addressing the digital divide, in late 2020 and early 2021 the City of Dallas used data and about $5M in ARPA funds to build 20 community Wi-Fi networks to serve approximately 3,400 households with the lowest access to the internet. While each of the City of Dallas’ community Wi-Fi networks, which provide similar internet access as the City of Dallas’ libraries, used a nearby City facility as a hub, 10 of the networks used solar-powered utility poles to support radio equipment that served as wireless access points (WAPs). However, where crime data drove the decision to install and use streetlights to build out 10 of the 20 community Wi-Fi networks and to help curb crime in those neighborhoods, the networks required telecommunications fiber to be run and installed from nearby City facilities.
Innovation and Smart Cities Technologies
Learning from the development, installation, and operation of the 20 community Wi-Fi networks, since early 2021, City of Dallas, cross-departmental teams have continued to explore ways to leverage technology to move Dallas towards becoming a smart city to increase the quality of life for its residents and visitors. In mid-2021, vendors shared with City staff many possible applications for the use of artificial intelligence (AI) in processes such as pavement condition assessment, traffic counts, and parking availability. In addition to the collection of infrastructure and transportation data, AI processes allow for computers to learn to detect public safety concerns such as illegal dumping and intersection takeovers by cars doing stunts.
During the AI discussions in mid-2021, and stemming from the success of using streetlights as WAPs as part of a community Wi-Fi network, City teams began exploring combination WAPs and AI-enabled cameras that could be attached to streetlights. Ultimately, the City of Dallas decided to work with a vendor to develop and implement a pilot project to address lack of access to the internet, increase public safety, and to monitor air quality.
Convergence of Data, Innovation, and Infrastructure Needs
Resulting from the 2021 discussions of combination WAPs and AI-enabled cameras to be attached to streetlights (equipment draws power from the streetlight as it plugs directly into the 7-pin NEMA socket), City of Dallas teams replicated the process of using data to identify residents with low access to the internet and overlaid that information with crime data. However, in this next iteration of project planning, City teams not only identified communities with low access to the internet and higher crime rates but also for neighborhoods that needed infrastructure improvements. The convergence of data, indicating low access to the internet, high crime, and needed infrastructure improvements, led to the development of the Red Cloud Smart Cities Pilot Project.
Planned to be operational by the end of September 2022, the Red Cloud Smart Cities Pilot Project will be Dallas’ first smart community in which all streets, alleys, and sidewalks will be replaced, new light emitting diode (LED) lights will be installed, WAPs will be installed on each of the new streetlights to provide community Wi-Fi to the neighborhood’s almost 190 homes, an environmental monitor will be installed on one of the new LED streetlights, and select WAPs within the neighborhood will also include AI-enabled cameras. As the streets, alleys, sidewalks, and streetlights have been upgraded, once the community Wi-Fi network, AI-enabled cameras, and environmental monitor are fully operational and City teams have had the opportunity to learn and test the capabilities of the new technology, the Red Cloud Neighborhood will hopefully serve as a model to replicate and scale across the City of Dallas.
Lessons Learned for Future Smart Communities
While the community and City of Dallas teams eagerly await the new technologies to become operational, looking back at the planning and implementation of projects in the Red Cloud Neighborhood, a major lesson learned included being deliberate in planning smart cities technologies as part of capital projects. Deliberate planning for the technology needs to support the smart cities applications within the Red Cloud Smart Cities Pilot Project meant, that when completing the sidewalk replacements, construction teams took advantage of the excavated sidewalk area to lay conduit to be used for the installation of telecommunications fiber to connect the community Wi-Fi network. Along the lines of deliberate planning for the technology needs in the Red Cloud project, City teams also ensured that while the new LED streetlights were constructed to meet lighting requirements, they were also designed and strategically placed to provide the mesh community Wi-Fi network.
Aside from being deliberate in the planning and implementation of smart cities technologies in capital projects, City of Dallas teams are working on other use cases for AI-enabled cameras in residential areas with speeding concerns, planning on how to meet community Wi-Fi needs in the City’s parks, and evaluating options for combination 5G poles with electrical vehicle (EV) charging stations. Although deliberate planning and implementation is vital, the most important lesson learned from implementing smart cities technologies in the City of Dallas has been to consistently encourage and empower forward-thinking team members to pursue innovative technologies and processes that continuously raise the service delivery bar.
Dr. Robert M. Perez serves as an Assistant City Manager for the City of Dallas. Robert has gained over 20 years of municipal government experience while working for the City of Dallas and the City of San Antonio and holds a Doctor of Philosophy in education with a concentration in organizational leadership, a Master of Public Administration, and a Bachelor of Arts in English with a minor in political science. | <urn:uuid:c6509592-6673-42c0-960c-92807214d0ec> | CC-MAIN-2022-40 | https://iconoutlook.com/data-innovation-and-infrastructure-lessons-learned-fromimplementing-smart-cities-technologies-in-the-city-of-dallas/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337537.25/warc/CC-MAIN-20221005042446-20221005072446-00156.warc.gz | en | 0.946456 | 1,209 | 2.75 | 3 |
NetFlow is a protocol used to collect metadata on IP traffic flows traversing a network device.
Developed by Cisco Systems, NetFlow is used to record metadata about IP traffic flows traversing a network device such as a router, switch, or host. A NetFlow-enabled device generates metadata at the interface level and sends flow data information to a flow collector, where the flow records are stored to enable network traffic analytics and management. A network operator can use NetFlow data to determine network throughput, packet loss, and traffic congestion at a specific interface level. NetFlow data also supports other network-level monitoring use cases such as DDoS detection and BGP peering.
The History of NetFlow and Versions Over Time
Netflow was initially developed by Cisco in 1995 to monitor and record all network traffic coming through their network devices. Over time, they realized that the network flow data was incredibly useful and it led to an entire branch of network monitoring that several other platforms have copied and rebranded. Now, a version of NetFlow protocols have become industry standard for optimizing network performance. This ongoing evolution of NetFlow has led to several versions over the years with different features.
While the term “NetFlow” is commonly used to refer to all types of flow records and datagrams, there are actually three important variants in regular use within live production networks:
NetFlow is the technology and term used exclusively by Cisco Systems.
IPFIX is an IETF standard flow record format that is very similar in approach and structure to NetFlow v9 (see more on NetFlow version numbering below). It is sometimes called “NetFlow v10” since IPFIX plays a key role in coalescing all NetFlow variants and equivalents as the standards process evolves the IPFIX specifications over time.
sFlow is a similar but importantly different type of flow protocol and data record standard introduced and promoted by InMon Corp. sFlow does not sample all packets like NetFlow does, nor does it timestamp traffic flows. It relies on accurate and reliable statistical sampling methods for documenting flows, thereby reducing the amount of flow information that ultimately needs processing and analysis.
Other vendor-specific flow record formats that are similar in nature to one of three most common variants listed above (in most cases these are either substitutions or very close adaptations) include:
– J-Flow from Juniper Networks, which essentially conforms to NetFlow v5;
– NetStream from 3Com/Huawei.
xFlow, while not a variant, is the generic term often used to refer collectively to all flow record variants (NetFlow, sFlow, IPFIX, J-Flow, etc.).
The fields that make up a NetFlow flow record depend on the version of NetFlow supported by the NetFlow exporter. Since the protocol was first introduced by Cisco in 1996 it has been updated numerous times in a series of backward-compatible versions, the most commonly used of which are versions 5 and 9:
v1: First implementation, now obsolete, and restricted to IPv4 (without IP mask and AS Numbers).
v2: Cisco internal version, never released.
v3: Cisco internal version, never released.
v4: Cisco internal version, never released.
v5: First commonly deployed version, available (as of 2009) on many routers from different brands, but restricted to IPv4 flows.
v6: No longer supported by Cisco.
v7: Like version 5 with a source router field.
v8: Several aggregation forms, but only for information that is already present in version 5 records
v9: Template based, available (as of 2009) on some recent routers. Mostly used to report flows like IPv6, MPLS, or even plain IPv4 with BGP nexthop. Includes added fields for security and traffic analysis use cases
Flow exporter: A NetFlow-enabled device that generates flow records and periodically exports them to a flow collector.
Flow collector: A program running on a server that is responsible for receiving, storing, and pre-processing flow records received from NetFlow-enabled devices.
Flow analyzer: An analysis application that processes flow records collected by the flow collector into reports, alerts, and other interpreted results.
Flow Records and Data
A NetFlow exporter (NetFlow-enabled device) identifies a flow as a unidirectional stream of packets having in common (at least) the following:
Input interface port
IP source address
IP destination address
Source port number
Destination port number
Layer 3 protocol field
Type of service
These same attributes that define a given set of IP packets as a flow make up the core metadata (information about the flow rather than the information that’s actually in the packets) that is included in the NetFlow “flow record” for that flow. Each time a new unidirectional IP traffic flow starts traversing a device a new NetFlow flow record is created and tracked in the device’s on-board NetFlow cache. And of course, the function of NetFlow is to export this network flow data to a NetFlow collector for storage and analysis.
A flow record is ready for export when one of the following is true about the corresponding flow:
The flow is inactive (no new packets received) for a duration defined in a timer. Timers are configurable but defaults are typically used.
The flow is long-lived (active) but lasts for longer than the active timer (e.g., a long FTP download).
A TCP flag (i.e., FIN, RST) indicates that the flow is terminated.
At export, the flow record is encapsulated in a UDP datagram and sent to a NetFlow collector that is typically external to a NetFlow-enabled device. The collector collects and stores the flow metadata in a record format that is defined by the protocol. The data points found in a NetFlow record typically include:
Source and destination IP address
Source and destination TCP/User Datagram Protocol (UDP) ports
Type of service (ToS)
Packet and byte counts
Start and end timestamps
Input and output interface numbers
TCP flags and encapsulated protocol (TCP/UDP)
BGP routing information (next-hop address, source autonomous system (AS) number, destination AS number, source prefix mask, destination prefix mask)
After the flow collector receives this flow record, it’s sent to the flow analyzer to extract the data for insights. Network admins use these insights to identify security threats and traffic patterns such as application performance and bandwidth usage that serve to improve the overall performance of a network.
Why use NetFlow: Key Benefits and Capabilities
By now it should be obvious that organizations can utilize flow-based analysis techniques with NetFlow to visualize traffic patterns for complete network visibility. This makes the responsibilities of the network admins considerably easier in many ways.
Some of the key benefits include:
Optimized bandwidth usage and capacity planning
Deeper network visibility
Enabling of root cause analytics for application performance slowdowns
Identification and investigation of security threats on the network
In addition, it has multiple use cases for network monitoring: | <urn:uuid:5a3de261-d0c0-4921-b2ae-79ce1261b5b5> | CC-MAIN-2022-40 | https://www.kentik.com/kentipedia/what-is-netflow-overview/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337836.93/warc/CC-MAIN-20221006124156-20221006154156-00156.warc.gz | en | 0.914953 | 1,498 | 3.03125 | 3 |
The Importance of Securing Your Website
As your organization is working to secure your infrastructure, one component that can fall through the cracks is your company’s website.
While it might not be top of mind, there are impacts of not having a secure website. A website that is not secured:
- Allows for the possibility of multiple vulnerabilities and misconfigurations to exist, which can be the entry point hackers need to infiltrate your IT systems. These attacks can cause a loss of customer trust and a diminished brand reputation.
- Lowers the ability of clients and prospects to find your website as when delivering search results Google and other search engines prioritize sites that are secure. This translates to lost business opportunities.
- Delivers a poor brand impression with the display of a warning in search engine results. This notification alerts site potential site visitors that the website they are considering opening is not secure.
- Hinders your ability to partner and do business with government entities. When working with the government in any capacity, it’s even more important to have secure systems, including your website.
How do you determine if you have a secure website – and what does that mean?
The easiest way to know if your site is secure is to look at the URL of your website. If it begins with “https” instead of “http” it means the site is secured using an SSL (Secure Sockets Layer) Certificate.
SSL is a networking protocol designed for securing connections between web clients and web servers over an insecure network, such as the internet. As the standard security technology, it ensures that all data passed between the web server and browser remain private.
How else can you secure your website?
- Produce more secure code – and make certain that your web applications minimize these risks. For your developers, that means following the Open Web Application Security Project (OWASP) guidelines. The OWASP Top 10 outlines the most critical security risks to web applications and, consequently, to your website. Being proactive and protecting your organization against these threats, is effective in changing the software development culture within your organization. Learn more
- Conduct penetration testing of your website. Pen testing can be used to test the vulnerabilities of your website. In this case, a pen test would be performed by attempting to exploit your organization’s website to determine if its protective controls can be bypassed. As threats to your IT infrastructure and your website are constantly evolving. pen testing can help your organization gain a fresh perspective with a third party looking at your security from the viewpoint of an attacker. Learn more
Take steps to secure your website now and reap the benefits including:
- Protecting the privacy of web visitors
- Improving user experience
- Elevating search engine presence
- Safeguarding your brand reputation
As you work to secure your web applications, give us a call. As penetration testing experts we can help identify flaws and misconfigurations within your internal and external infrastructure as well as other valuable assets. | <urn:uuid:ef78bfe5-82d1-44d2-be7a-d0a751e89684> | CC-MAIN-2022-40 | https://cybersheath.com/the-importance-of-securing-your-website/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338280.51/warc/CC-MAIN-20221007210452-20221008000452-00156.warc.gz | en | 0.931844 | 613 | 2.515625 | 3 |
A Brief History of the Zero Trust Model
Established back in 2010 by industry analyst John Kindervag, the “Zero Trust model” is centered on the belief that organizations should not automatically trust anything inside or outside its perimeters; instead, it must verify anything and everything trying to connect to its systems before granting access. To quote the infamous Marxist dictator Joseph Stalin, “I trust no one, not even myself.” Essentially, the same rules apply to this concept.
In the wake of the U.S. Office of Personnel Management (OPM) breach, the House of Representatives strongly recommended government agencies adopt a Zero Trust framework to protect their most sensitive networks from similar attacks. Market research shows Zero Trust models, and the technologies that support them, are becoming more mainstream and readily adopted by enterprise-level organizations worldwide. When organizations like Google create and implement their own flavor of Zero Trust, BeyondCorp, people start to pay attention.
This two-part blog will first focus on how perimeter security has changed over time and how the importance of securing privileged access has increased in line with this change. The second installment will highlight five critical considerations for modern architectures.
The (D)evolution of the Perimeter
In the beginning, maintaining a high-level of protection from cyber threats was very much focused on securing the perimeter. This was the golden age of firewalls, VPNs and DMZs (Figure 1.) Trust was, essentially, established and defined by the perimeter. At this point in time, the lifeblood of the company existed almost exclusively within the physical walls of the organization. The belief was that if you’re connected to the network, then you are trusted. If you’re an employee of the company, then you can’t go rogue. In these early days, organizations focused on perimeter security to prevent things like network intrusion, malware, phishing, denial of service and zero day attacks. This is all well and good, but this traditional “Tootsie Pop” model (remember those commercials?) featured a strong exterior where the focus was placed almost exclusively on the perceived threat from the outside, but completely ignored the soft, chocolaty goodness directly in the middle.
Over time, we ultimately punctured this traditional security bubble – effectively bringing the problems inside, which meant redefining our sense of trust and appropriate controls. First, users transformed into digital nomads, abandoning their corporate or branch locations to become fully remote employees. We then opened up our networks to consumers so that they could use our applications, leading to extranets and moving another layer of the concentric circles in Figure 1 to the outside. For example, with VPN connections, organizations often allow half of the traffic to go directly outside and half through the VPN to access the organization’s applications. This VPN connection inherently trusts the user’s machine and, by connecting to those machines, potentially subjects itself to malware, which can then spread itself through the network.
Next, the adoption of SaaS applications took hold as businesses looked to scale their applications across multiple end user PCs, without filling up too much of the (at the time) expensive hardware and storage space.
Naturally, then we find our data and workloads moving to the cloud. Our files, documents and emails are on Office365 and our usage of public data sources (and within SaaS) increases. Lastly, infrastructure extends to hybrid architectures via Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform, which is how many organizations are architected today (Figure 2).
Throughout this evolutionary process, the perimeter had become so fluid and dynamic in nature that the boundaries, in the traditional sense, ultimately disappeared. The perimeter is no longer a static entity; it’s been made permeable by the disruption of things like cloud, digital transformation, the Internet of Things (IoT), mobile access and an increasingly geo-distributed workforce.
Within these modernized architectures and with an expanded attack surface, the privileged access pathway creates significantly more risk (Figure 3). Let’s differentiate the two access pathways: the standard user ultimately has very basic, low-level access limited to just the application layer; the privileged user, essentially, has unfettered access to the application layer, sensitive data and the mission critical Tier 0 assets. This inherently carries a much higher-level of risk if left unmanaged and unsecured, given the decentralized nature of this model.
Zero Trust is not just limited to human users, but to non-human users as well, e.g. applications interacting with operating systems via service accounts and business (and robotic) automation processes where software bots are connecting, storing and accessing sensitive data and applications. As the security layers slip through the fingers of the organization, securing important data becomes a much bigger challenge.
Let’s highlight a standardized workflow for the privileged user. Let’s assume a privileged user is working abroad while on a business trip and he or she is trying to configure and run a cloud service hosted in an AWS instance, which requires pulling a database running on a Unix box racked in an existing mainframe. Ensuring that there’s a consistent point of trust throughout this workflow is a challenge that needs to be addressed; the user remotely connects to different islands of systems, databases and applications (both on-premises and in the cloud) creating many potential points of entry for an attacker.
This evolutionary process of the security model not only aligns to the basis by which the principles of Zero Trust were established, it reaffirms the importance of securing privileged access. The foundation of Zero Trust is, arguably, the same as the foundation for why CyberArk and the privileged management space exists. Now, while most enterprises may not be willing to fully abandon firewalls and perimeter security, they, certainly, should be placing their focus on tightening security from the inside to mitigate risk of an advanced attack.
In the next installment, we discuss the evolution of trust and make recommendations for building out modern architectures that align to Zero Trust frameworks.
To learn more, watch the Implementing Privileged Access Security into Zero Trust Models and Architectures webinar.
Continue reading in part 2. | <urn:uuid:9c5bece7-f3d6-4b30-8151-b16795c54808> | CC-MAIN-2022-40 | https://www.cyberark.com/resources/blog/zero-trust-part-i-the-evolution-of-perimeter-security | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030331677.90/warc/CC-MAIN-20220924151538-20220924181538-00357.warc.gz | en | 0.931964 | 1,272 | 2.640625 | 3 |
It is common for security flaws to appear that affect operating systems, applications and devices in general. Sometimes they can also compromise the data of many users who use an online service and data of all kinds can be leaked. In this case, a zero-day error that affects Twitter and has left millions of accounts exposed. We are going to explain what it is and how it can affect your security.
Data from millions of Twitter accounts leaked
Whenever such an error appears, user data can end up in the wrong hands. This includes names and surnames, email account, mobile number.. We must bear in mind that we can put very varied information on social networks, so all of this could end up on the Dark Web.
Twitter has confirmed that there has been a zero-day vulnerability that has exposed data from 5.4 million accounts. This data includes phone numbers and emails linked to the account. However, there is no information on whether the access codes have been compromised.
But how did we get to this situation? The vulnerability appeared a year ago, after a code change was introduced. But it was not until a few months ago, in early 2022, that Twitter, through its bug bounty program, became aware of this security vulnerability.
Once they learned of the problem, Twitter quickly went to work to find a solution. Today this problem is solved. Although at first there was no evidence to indicate that someone could have exploited this vulnerability , it now seems that it did happen and several million accounts could have been compromised.
From the social network they indicate that they will contact each of the affected users. Therefore, if you do not receive anything from Twitter, it means that your account is not one of those that have been compromised, unless there is evidence of it.
Tips to avoid data breach in social networks
We have seen that the chaos of Twitter basically consists of a leak of personal data, such as the phone number or email account. It is a failure that does not depend so much on the users, although we can take general measures to reduce the probability of attacks and ensure that the accounts are more protected. This is something that you can apply on any platform you use.
An interesting piece of advice is to avoid making certain data public. For example, do not publish your phone number and even do not link it to social networks. In this way, in case there was a problem, it would not be exposed so that hackers could steal them and end up for sale on the Dark Web.
It’s also a good idea to avoid posting general information. For example, place of residence, where you work or study, etc. All this, although it may be harmless, could end up in the wrong hands and create campaigns aimed at stealing passwords or infecting you with malware. Therefore, the less information you give, the better.
Of course, one more piece of advice is to protect the accounts very well. For this you need to use a password that is strong and secure, but it is also a good idea to activate the two-factor authentication of Twitter and other platforms that you use. This will prevent a possible intruder from gaining access without your permission.
He is a cyber security and malware researcher. He studied Computer Science and started working as a cyber security analyst in 2006. He is actively working as an cyber security investigator. He also worked for different security companies. His everyday job includes researching about new cyber security incidents. Also he has deep level of knowledge in enterprise security implementation. | <urn:uuid:cde11565-9d6f-40e7-950e-cb8724b01da0> | CC-MAIN-2022-40 | https://www.exploitone.com/vulnerabilities/your-twitter-account-password-could-have-be-exposed-by-this-zero-day-vulnerability/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334992.20/warc/CC-MAIN-20220927064738-20220927094738-00357.warc.gz | en | 0.966981 | 710 | 2.734375 | 3 |
A SIEM alert is a tool most commonly used by SOCs to protect an organization. SOCs entrust the reliability of the processes on their IT systems to this kind of automated technology, which reports any issue that may occur.
Ah, but what is a SIEM, you ask?
Security Information and Event Management (SIEM) is a software solution that aggregates and analyzes activity from many different resources across your entire IT infrastructure. A SIEM collects security data from network devices, servers, domain controllers, and more. SIEMs store, normalize, aggregate, and apply analytics to that data to discover trends, detect threats, and enable organizations to investigate any alerts. Gartner predicts spending on SIEM technology will reach nearly $3.4 billion this year alone.
SIEM tools analyze the state of the processes that are occurring on the IT system and classify thousands of events to evaluate their behavior and detect possible anomalies that could lead to a cyberattack. And should an attack happen, this kind of alert scours the system in order to analyze the possible causes of the attack and how to stop it.
Keep in mind, though SIEM alerts are one of the most commonly used tools does not mean that they are everything you need to keep your network secure. One of the difficulties with checking SIEM data for values is there is no standardized format for information that is contained in these messages. Therefore, the data needs to be normalized into a standard model. From this, alert rules can be created, which check for correlation and aggregation across multiple devices or apps. Additionally, the standardized data model also helps with noticing specific occurrences of value on particular devices or apps. Also, SIEMs are based on searches for threats that they already know, but not for unknown threats. These unknown threats will be at the mercy of customized alerts. Customizing alerts to discover new threats is an insurmountable task for most organizations, since many SOCs do not have enough professionals to update search criteria frequently.
SIEM alerts can evaluate many events individually, but when an event occurs with others, they may fall short. One of the constant challenges when writing alerts is balancing the goals of reducing false positives and preventing inundation while still alerting on all suspicious events. Security teams are constantly looking for opportunities to improve alerts to reduce the false positive rate. With a SIEM, an alert taken in isolation could be a threat, but when run with other events, is not dangerous. This causes an increase in false positives detected.
As a rule, SIEM alerts should not be used alone, but in conjunction with a proactive security approach and strategy, which constantly hunts for previously unknown threats, and which acts autonomously to detect and classify them.
Cofense Intelligence delivers threat intelligence in multiple forms:
- Machine-readable threat intelligence (MRTI) follows industry standards for quick integration with your existing security devices, like a SIEM.
- Analysis reports in PDF and HTML format are optimized for threat analysts and incident response teams.
- Published threat intelligence that shows how individual elements of an attack are related and the relationships between seemingly disparate attacks.
Our proactive approach enables you to prime your existing security infrastructure to disrupt these potentially dangerous attacks. Tactics used to penetrate your network are also exposed along with the relationships between phishing campaigns and Indicators of Compromise (IOCs). The combination of actionable threat intelligence and understanding the correlation between phishing attacks and their motivators helps your team prioritize, investigate, and respond.
Cofense Intelligence key benefits:
Integrates with existing security solutions to speed phishing threat response
Provides timely, accurate, and actionable phishing threat intelligence
Expert threat analysts to help operationalize threat intelligence and provide guidance
Attack analysis and context to help make rapid, informed decisions
To see what how Cofense Intelligence works, try it free for 3 months. Our high-fidelity phishing alerts and threat intelligence make it easy for you to track emerging phishing trends, research active threats, and supplement your active investigations. | <urn:uuid:32ca5220-9da4-4aa0-bde0-8f19524fe4eb> | CC-MAIN-2022-40 | https://cofense.com/what-is-a-siem-alert/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335396.92/warc/CC-MAIN-20220929225326-20220930015326-00357.warc.gz | en | 0.93014 | 825 | 2.859375 | 3 |
Climbing in the Bird-Tower Environment
On Thursday, March 28 at 10:00 a.m. CDT, Marco Restani, Professor Emeritus and Senior Raptor Scientist for Cell Tower Osprey Management, conducted a live NATE webinar entitled Climbing in the Bird-Tower Environment.
Many birds such as ospreys and bald eagles are increasingly using cellular communications towers for nest sites, which creates conflicts with industry because birds, eggs, and nests are protected by law. Therefore, climbing towers to maintain, repair, or upgrade equipment may be restricted when nesting birds are present. Not only should tower owners and communications providers know how to cope with nesting birds, tower climbers should also become familiar with bird behavior to ensure personal safety and the welfare of the birds.
This webinar provided an overview of:
1) why and where this problem is increasing,
2) the legal protections afforded birds,
3) suggestions to climb safely in the bird-tower environment,
4) the biology of nesting birds, and
5) the role of government agency and consulting biologists.
Preventing birds from nesting on towers is a long-term goal supported by both wildlife biologists and industry. Installing excluders to prevent ospreys from nesting on towers has been very effective but keeping towers nest-free of all species that use them remains an ongoing challenge.
Click here to view the PowerPoint.
Click here to view the Climbing in the Bird-Tower Environment webinar. | <urn:uuid:ed9e536e-e834-4a90-b1aa-f8bbeaab2f97> | CC-MAIN-2022-40 | https://natehome.com/safety-education/nate-webinars/register-for-live-nate-webinar/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337446.8/warc/CC-MAIN-20221003231906-20221004021906-00357.warc.gz | en | 0.928917 | 310 | 2.78125 | 3 |
The Australian government will spend $64.4 million on a new supercomputer in Perth to process and analyze data from the Square Kilometre Array (SKA) radio telescope.
The world’s largest public science data project, the SKA will be huge in scope, cost, and output. Receiving stations will extend at least 3,000 kilometers (1,900 mi) from a concentrated core, and span across both Australia and South Africa.
Initial construction began in 2018, but observations from the fully completed array are not expected until 2027 - with a history of delays suggesting that that could be pushed back.
All those sensors will produce enormous quantities of data - more than all of the Internet back in 2013. This causes issues for real-time processing, transfer, storage, and compute. To cope, a multifaceted computing initiative is underway to build systems capable of handling the extreme quantities of data.
Understanding the history of the universe requires a lot of compute
Australia's upcoming supercomputer will help form a core part of that computational infrastructure. The system will work with another in Cape Town, with the two together known as the Science Data Processor. The combined SDP will be capable of 250 petaflops of peak performance.
Precursor telescopes MWA and ASKAP already use a 546 teraflops supercomputer at Pawsey, while a 50 petaflops system launching next year will be used for the telescopes as well as wider scientific workloads. After processing, the data will also be shared with supercomputers from the 14 nations that are part of the SKA, as well as potentially those of the US - which left the project in 2011 after 20 years of involvement.
While the full SKA is not set to go live for at least another six years, 131,072 low-frequency Christmas tree-shaped antennas (pictured) are expected to be installed by the end of this year in Australia, along with another 197 mid-frequency dish-shaped antennas in Karoo.
“When the telescope is switched on, it will open the floodgates to a massive amount of data, as signals from all over the Universe pour in — it’s an enormous and very exciting challenge for us,” AusSRC director, Dr. Karen Lee-Waddell said.
After extensive on-site processing to compress data, "the flow of data will be roughly 100,000 times faster than your average home broadband speed. Each year, we’ll store around 600 petabytes coming from the SKA telescopes for astronomers and astrophysicists from all over the world to access and analyze." | <urn:uuid:e93e58da-efa0-4c20-a4aa-6115c0c25b05> | CC-MAIN-2022-40 | https://www.datacenterdynamics.com/en/news/australian-gov-to-spend-64m-on-pawsey-square-kilometre-array-supercomputer/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337853.66/warc/CC-MAIN-20221006155805-20221006185805-00357.warc.gz | en | 0.925848 | 544 | 2.953125 | 3 |
It has been reported that the Girl Scouts of America is now offering girls as young as five a badge in cybersecurity. It’s part of a drive to get more girls involved in science, technology engineering and mathematics from a young age. An event in Silicon Valley gave scouts an opportunity to earn the first patch in the activity.
Girl Scouts of America is now offering girls from the age of five a badge in cyber-security! What a great, fun way to encourage girls to get more involved in #STEM subjects from a young age. https://t.co/7gGm8o1hvc
#education #cybersecurity #Technology #thisgirlcan
— eShore Ltd (@eShoreLtd) January 21, 2019
Cristina Roa, VP International at Securonix:
“The Girl Scouts initiative is an investment in the future of cybersecurity, and it will help to boost interest and participation in an industry in which women are not only traditionally underrepresented but an industry that is also facing a severe skills shortage.
The initiative offers girls the chance to learn about data privacy, online safety, coding and even how to become a white hat hacker. It is immensely important that initiatives, such as this one, continue to gain funding and support from the cybersecurity industry and governments. This will help drive awareness around cybersecurity, encourage more females to get into the industry and ensure that we have the resources in the future to combat an exponentially growing problem.” | <urn:uuid:aaec0d90-de98-4154-9e70-927c1c0658f5> | CC-MAIN-2022-40 | https://informationsecuritybuzz.com/expert-comments/girl-scouts-of-america-offering-cybersecurity-badges/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334644.42/warc/CC-MAIN-20220926020051-20220926050051-00557.warc.gz | en | 0.949501 | 304 | 2.75 | 3 |
Cloud In Developing Countries
The ability of cloud computing in processing, transmitting, and storing data makes it increasingly significant in the delivery of public and private services. Cloud computing as a disruptive technology with major implications for markets, economies and societies is becoming increasingly important for countries at all levels of development. However, the level of cloud adoption for organizations in developing countries looks very different from those in developed countries.
According to Kshetri’s report (2010), “the market for the cloud in developing countries is small but expanding rapidly”. Developing countries are attractive markets for cloud services and this technology has applications in a wide range of areas, including E-education, E-health, E-commerce, E-business, and supply chain. In reality, there are very few companies in developing countries which are actually using cloud computing. It would seem that cloud computing in developing countries is in its early stages.
(Image Source: IEEE Computer Society)
Many scholars believe that cloud computing has the potential to offer users in developing countries access to unique resources of computing power and storage. It is clear that the adoption of cloud computing is of great significance for businesses and organizations. Cost savings in hardware, software and personnel, as one of the main advantages of cloud computing, are most frequently cited in the literature. Cloud service customers can pay for the use of data storage capacity and application software rather than buying the hardware and software. Furthermore, software on the cloud can be easily installed, maintained, and updated. Although companies that use of cloud facilities extensively need competent personnel to manage IT functions, obtain cloud services, and manage their relationship with cloud providers; cloud computing generally leads to lower IT staff costs.
Flexible access to processing and storage capacity is another benefit of cloud computing. In addition, a global study on 400 government executives in 10 developed and developing countries indicated that cost savings (See image), the nature of government activity, administrative advantages (e.g. easier software access, rapid deployment and reduced system administration) are the most significant advantages of cloud adoption.
Recent studies in developing countries indicate that cloud adoption in these countries is low and majority of developing countries encounter significant obstacles to participate effectively in the cloud economy. Barriers affecting cloud adoption in developing countries differ significantly depending on a country’s level of development and business and communications environments. These barriers can be divided into two main categories: internal and external barriers. Attitudes towards cloud computing, concerns and anxieties among managers about data privacy and security in the cloud, the location of data and reliability of services, concerns related to the non-availability of suitable terminal devices, concerns related to the migration of data and upgradability, lack of knowledge and skills to manage cloud resources, and finally lack of awareness of what cloud computing actually involves and its implications are main internal barriers. External barriers to adoption include inadequate infrastructure (lack of reliable power and broadband connectivity), lack of adequate legal and regulatory frameworks for electronic commerce and cybersecurity, and lack of skills to make effective use of ICTs.
Like other new innovations, successful implementation of cloud computing in developing countries needs organizational change which takes time and requires new investment. Policy makers in developing countries should research and analyse the level of cloud readiness and potential implications of cloud adoption. In addition, policies should recognize the diversity of business models and services within the cloud, the diversity of customers of cloud services and the complexity of the cloud economy ecosystem. Then, an effective cloud strategy (which address the areas such as infrastructure, legal and regulatory issues, the supply side of the cloud economy ecosystem, human resources, Government cloud use and financial implications) should be designed for a successful implementation of cloud computing.
By Mojgan Afshari
Mojgan Afshari is a senior lecturer in the Department of Educational Management, Planning and Policy at the University of Malaya. She earned a Bachelor of Science in Industrial Applied Chemistry from Tehran, Iran. Then, she completed her Master’s degree in Educational Administration. After living in Malaysia for a few years, she pursued her PhD in Educational Administration with a focus on ICT use in education from the University Putra Malaysia. She currently teaches courses in managing change and creativity and statistics in education at the graduate level. | <urn:uuid:1c63e54d-0194-4589-a589-5ca48258d9be> | CC-MAIN-2022-40 | https://cloudtweaks.com/2014/06/technology-developing-countries/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335004.95/warc/CC-MAIN-20220927100008-20220927130008-00557.warc.gz | en | 0.942735 | 859 | 2.671875 | 3 |
The UK government has recently announced the new Data Protection Bill, which is designed to replace the current, out-dated, Data Protection Act (DPA). The new bill was published on 14 September 2017, although it has not been specified when it will officially come into effect.
What is the reason for the new Data Protection Bill?
As of 25 May 2018, the EU GDPR (General Data Protection Regulation) will come into force. Since the UK has voted to leave the European Union, our current data protection laws must be updated to reflect those of the GDPR, in order to ensure that there are no disruptions to the way data is transferred between Britain and the rest of Europe. However, certain updates, such as the way social media companies store personal data belonging to those under the age of 18, have been added on.
How does the new Data Protection Bill differ from the existing DPA?
Included in the new bill are the following updates/improvements:
Right to be forgotten
The “right to be forgotten” is designed to give individuals more control over how their information is stored and removed. While the “right to be forgotten” is already included in the forthcoming GDPR, the Data Protection Bill has extended the law by requiring social media companies to delete any information that was posted by an individual when they were under the age of 18, should the individual choose to make such a request. This may prove a challenge for some organisations whose data archives are stored in a manner that is difficult to search and sort.
Due to concerns that companies are using browsing records to target individuals, the definition of personal data will be updated to reflect news types of data that were not covered by the DPA. These new types of personal data include; IP addresses, cookies and DNA.
It is often the case where companies use automated “profiling” of data relating to a person’s health, personal preferences, financial status, behaviour etc. Under the new law, individuals can demand that such profiling is performed by a person, and not by an algorithm.
The new Data Protection Bill will make it easier for individuals to move data between companies (i.e. move photos between cloud storage companies).
New fines and criminal offences
As with the GDPR, the penalties associated with non-compliance will be significantly bolstered under the new bill. Fines of up to £17m, or 4 per cent of a company’s global turnover, may be issued should a company fail to comply. This is a significant increase from the maximum fine of £500,000 associated with the DPA. As you can imagine, companies like Facebook and Google could face potential fines that amount to billions of pounds. There are also two new criminal offences outlined by the Data Protection Bill: The first relates to the re-identification of people from anonymous data. This would involve piecing together bits of anonymous data in an attempt to identify a particular users behaviour. The second offense relates to the tampering of personal data in some way. The fines for breaching these laws are potentially unlimited.
Complying with these new regulations may pose a significant challenge to many organisations; however, there are solutions available that can help to ease the burden. For example, Lepide Data Security Platform enables you to keep track of your sensitive data by helping you determine who has access to what data, when the data is being accessed and where the data is located. It also enables you to generate various custom reports and alerts which can be used to satisfy regulatory requirements. | <urn:uuid:99ae2b0c-268e-4478-aba4-62f6eca7bd40> | CC-MAIN-2022-40 | https://www.lepide.com/blog/how-will-the-new-data-protection-bill-affect-your-company/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335276.85/warc/CC-MAIN-20220928180732-20220928210732-00557.warc.gz | en | 0.953476 | 799 | 2.65625 | 3 |
While coding academies and training programmes provide opportunities for individuals to gain skills that hold value in the marketplace, a change in culture is needed to bring more diversity and inclusion to IT, say women leaders involved in tech education.
Training initiatives can contribute towards solving the problem but this approach is not a silver bullet, according to Baratang Miya, CEO and founder of GirlHYPE, a South African non-profit organization that teaches women and girls how to code and encourages them to pursue tech careers.
For Miya, it’s not a matter of upskilling more diverse candidates, it’s a matter of making sure that tech environments are more open and accepting of people who don’t look and think like everyone else.
“You cannot be what you can’t see. It’s really hard for a young girl to see herself working in the tech industry one day if she looks at the most successful tech leaders and none of them look or sound like her,” she says. “If there are so few examples of successful women in tech jobs, it’s tough for a young women to believe that she can do it, especially when society still tells her that some careers are more suitable for men and some are more suitable for women.”
Progress toward diversity is slow
The tech industry’s diversity and inclusion problem is no secret. Back in 2014, some of the industries bigwigs — including Google, Facebook and Apple — revealed their workforce demographics and the numbers left much to be desired. At the time, they promised to diversify their teams so that they included more people from underrepresented backgrounds in the future. Fast-forward a few years and, while some gains have been made, the improvements are marginal at best.
So, what actually needs to be done to reduce tech’s persistent diversity gap? The Harvard Business Review suggests that to reduce tech’s persistent diversity gap, industry must follow the talent, and transform how they recruit. With this in mind, many tech leaders support coding academies and training programmes that target women and minorities to provide them with the skills they need to secure a seat at the tech table.
But diversity and inclusion needs to be approached with a more holistic lens, says Emma Dicks, a co-founder of CodeSpace, a Cape Town-based academy that offers full-time and part-time coding courses. It is not just about teaching loads of people how to code.
There’s little value in teaching people how to code if these coding skills aren’t applied effectively, she says: Learning to code must increase their earnings, improve their life and enable them to have a positive impact on their workplace and community. When this is the case both the students and the industry stand to benefit.
Making changes from the top down
Simply equipping people with skills is not enough, agrees Natasha Reuben, head of transformation at Dell Technologies South Africa.
Women and minorities need to be empowered to succeed. For example, if you teach a woman to code and then you help her to start her own business using the skills she’s gained, Reuben says, you’re setting her up to act as a role model for future generations, to introduce new, fresh perspectives to the industry. You’re also putting her in the perfect position to innovate because she will approach problems in new ways and all of this is a great way to showcase what women are really capable of.
We need to be intentional in dismantling the structural barriers to entry that exist across the tech space, says Nyari Samushonga, WeThinkCode_ CEO. If the same voices get to speak all the time and the ideas keep coming from the same places, it shows us that new people aren’t being given the room to make a mark. Some of the inherent behaviours that drive exclusion are deeply imprinted in organisational culture. It takes courageous leadership to look out for and dismantle them.
Businesses that only hire for “team fit,” for instance, will develop a cohesive company culture by only employing people who fit a certain mould, but they’re only making themselves less innovative and more homogenous, says Dell’s Reuben. “From exclusionary language in job postings to culturally prescribed notions of what ‘male’ and ‘female’ positions entail, unconscious bias works in subtle ways.”
Real, tangible commitment is key
Dicks, the co-founder of CodeSpace, wants the industry to question if they are rewarding women and minorities for the diversity they bring and encouraging them to challenge how things are done, or whether they are rewarding them for assimilating to the status quo.
In order to open the door to women and minorities, companies must set concrete goals around diversity and inclusion, Dell’s Reuben adds. In addition to this, they need to create an internal culture that builds an understanding of unconscious biases and puts measures in place to overcomes gender stereotypes. Reuben believes that leaders need to be held accountable for achieving the targets they set and any progress, or lack thereof, needs to be publicly shared.
Under-represented groups have high attrition
High rates of attrition among women and under-represented groups is also a cause for concern, says Lindiwe Matlali, founder and CEO of Africa Teen Geeks, an NGO that aims to improve diversity in STEM by teaching kids how to code. “All too often when women and minorities do get into tech spaces, the culture is so hostile that they don’t stay for very long and they pursue careers in other industries,” Matlali says. “We need to be honest about what’s actually happening in tech. Right now, there’s not even one tech company that I respect when it comes to what they are doing to improve this situation. They keep saying the same things and then failing to follow through. In 2021, being a woman or minority in STEM shouldn’t be a cross to bear.”
If women and minority groups aren’t staying in the industry for very long, there’s little chance that they will ever find their way into senior positions, which means that they’ll never be the people who make the key decisions, Matlali notes.
The industry must make a concerted effort to acknowledge and promote the success stories of women and minorities and to shine a spotlight on the positive contributions these individuals have made, Matlali says: “I’m talking about Dr Marian Croak, a black female who was involved in the development of Voice over IP (VoIP) and is currently a VP of engineering at Google or Lisa Seacat DeLuca, one of IBM’s most prolific inventors, who has over 500 patents to her name.”
But Reuben believes that a commitment needs to come from both sides. For the women and minorities who have found success, it’s equally important to that they bring the process full circle. Those who have succeeded need to invest time in helping others to do the same.
“Studies show that diverse teams consistently outperform homogenous ones. It’s not just the morally correct thing to do, it’s also good business,” concludes Samushonga, of WeThinkCode. “Inclusion is a choice. I believe the question shouldn’t be whether or not we can solve the diversity problem, it is clear that we can. The true question is whether or not we want to.”
Continue reading for free
Create your free Insider account or sign in to continue reading. Learn more | <urn:uuid:05e93fc6-8a0f-44d8-acf6-043c777f277b> | CC-MAIN-2022-40 | https://www.cio.com/article/191360/coding-training-alone-wont-boost-diversity-sa-women-tech-leaders-say.html | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335424.32/warc/CC-MAIN-20220930020521-20220930050521-00557.warc.gz | en | 0.947985 | 1,583 | 2.53125 | 3 |
Most modern software and applications automatically update themselves, including the operating systems that provide basic functionality. Hackers find flaws in software which allows them access to your computer. Regularly updating software and operating systems is necessary to fix these vulnerabilities and keep your internet enabled devices as secure as possible. If you are interested in seeing an up to date list of vulnerabilities in outdated software you can find it here and here.
The most important things to keep updated are:
- operating systems, for example Windows, Windows Phone, Mac OS, iOS
- virus scanners and security software
- browsers, for example Internet Explorer, Firefox, Chrome
- web plugins, for example Adobe Flash, Reader, Skype, Apple Quicktime, iTunes, Java, ActiveX
- some other types of applications, for example Microsoft Office
But as you can see from this 2016 list in the table below and hosted here there are vulnerabilities across almost all software platforms that can be exploited by bad actors.
Here is an example that outlines what happens if you don’t have updated Adobe Flash.
Updates for Windows
Microsoft provides regular automatic updates for Windows. Older versions of Windows are unsupported, and users of these should consider upgrading.
Automatic updates for Windows (PC)
Windows Update is free and provides the latest security and other important updates from Microsoft automatically.
Setting up Windows Update is simple. If you have automatic updates turned on, Windows Update in Control Panel will open and show your update status. If it is not yet turned on, you will be guided through the steps to do so. After that, all the latest security and performance improvements will be installed on your PC automatically.
Updates for Apple
Apple generally provides updates for the latest and immediately previous versions of their operating software, but not for older versions.
For detailed information, search the internet or the Apple website:
Often, good internet search engines will find information more efficiently than searching a specific website
Updating anti-virus software and plugins
Anti-virus software and plugins require regular updates to remain effective and secure. Manufacturers of these products provide information about how to update them on their webpages, however most applications will default to installing updates automatically.
If you want to check the update settings of these types of software, search for the settings in your system.
Be cautious using online tools or software that claim to check if your software is up-to-date. Some legitimate tools exist, but often its malware in disguise.
Here is a good article from Kaspersky on why its necessary to keep your virus software up to date.
Updating security software
Viruses, spyware and other malicious software (malware) can stop your computer working properly, delete or corrupt your files or allow others to access your computer and your personal or business information.
Your computer can be infected a number of ways including:
- clicking on bogus website links
- downloading infected apps from the internet, or
- opening infected email attachments.
In some cases you don’t even have to click on a link, the exploit may be hiding in a nefarious advertisement that just displays on a popular website. Here is an example of how that happened at Yahoo.
Anti-virus software monitors and protects computers and other devices (smartphones, tablets) from infection. Anti-virus software must be updated regularly in order to recognize recent viruses, and most software does this automatically.
When you first install anti-virus software on a device, run a 'full scan' of the system to ensure there are no pre-existing virus infections, then follow the supplier's recommendations for regular scanning.
Anti-virus solutions differ in efficacy and the range of malware types they cover. Anti-virus software should provide:
- adware and spyware coverage
- comprehensive anti-virus scanning.
Some anti-virus products may include:
- a 'site advisor – your browser alerts you when visiting a suspicious or dangerous website
- malware protection with an integrated firewall (more on Windows firewall)
Do not use multiple products to perform the same function (for example two anti-virus packages) as it will unnecessarily slow your system, and they may conflict and cause problems.
If you are installing an anti-virus product with firewall functionality, you may need to disable your operating system's inbuilt firewall. The anti-virus and operating system vendors have instructions and information on their support websites about whether this is necessary.
Before choosing an anti-virus product, consider reviews on reputable websites or in magazines, or look at test results from the website AV Test. | <urn:uuid:1a6d1a74-cfe9-45a4-bcbf-c03431c093bc> | CC-MAIN-2022-40 | https://support.netwatcher.com/hc/en-us/articles/236352488-Why-You-Need-To-Keep-Software-Up-to-Date | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335609.53/warc/CC-MAIN-20221001101652-20221001131652-00557.warc.gz | en | 0.888851 | 953 | 2.90625 | 3 |
Here’s the problem with most programs aimed at killing malicious software: They need someone to tell them something’s malicious.
What if, however, the programs had the smarts to identify bad code on their own? That’s what a company calledDeep Instinct says its security solution, launched last week, can do.
The offering works its magic with a technology called “deep learning.”
“Deep learning draws its inspiration from the human mind. It organizes itself into a structure of synthetic neurons,” explained Bruce Daley, principal analyst atTractica.
“It’s another term for neural networks,” he told TechNewsWorld. “It was rebranded because there was so little progress with neural nets.”
Better Brain Emulation
Deep learning applications will be a hot commodity in the future, becoming a $10 billion market by 2024, Tractica forecasts.
A fertile area for those apps may be security, which is what Deep Instinct is counting on.
Classical neural networks in the 1980s and ’90s had one or two layers of several hundred neurons.
“Nice results, but nothing spectacular,” observed Deep Instinct CTO Eli David.
Now with advances in hardware, processing power and algorithms, deep neural networks that are more than 10 layers deep with hundreds of millions of neurons can be created. That kind of power can be harnessed to approach software development in a different way.
Chess Master vs. Chess Program
“With traditional programming, as you code, you have to anticipate all the situations that arise that you have to deal with. What deep learning does is take the data and build a model from what it finds in the data that’s statistically relevant,” Tractica’s Daley said.
“So you don’t have to anticipate all the relationships the program will encounter,” he added. “It turns the process into something like making beer or making bread.”
For example, computer chess programs play the game by brute forcing every move. They use massive processing power to figure out every possible move after a piece is moved on the board.
A person can’t do that. Yet chess masters have more than held their own against computer programs. With deep learning, a program approaches a problem more like the chess master than chess program.
In classic machine learning, a facial-recognition program contains information about a face, distance between pupils, shape of the face and so forth, Deep Instinct’s David explained. “With deep learning, you just feed it raw input and it learns the features itself.”
Cats From Cat’s Tail
That kind of “thinking” can be very important in a security app. What makes malware difficult to detect through traditional programming methods is that the slightest change in malicious code can fool a program.
“It’s as if I show you the picture of a cat, then I modify a few pixels, and you can’t recognize it’s a cat,” David said.
“With deep leaning, you can show just the tail of the cat, and it will return with high confidence that it’s a cat. It is extremely resilient to variance and modification,” he continued.
Deep Instinct’s security solution has a small agent — it takes up about 10 MB of memory — installed on each endpoint — laptop, mobile device or server — with deep learning technology in it.
“Most of the time this agent does nothing. When it detects a new file — any type of file — it passes it through the deep learning module on the device. If the file is malware, it will remove it or quarantines it,” David said.
“We compared our solution to 61 other solutions, and in all the benchmarks we conducted, we have 98 to 99 percent detection,” he noted. The best solution out of the 61 solutions is 79 percent. [*Correction – Nov. 11, 2015]
The solution requires a network appliance. It’s used for collecting information so a network administrator can have a bird’s-eye view of a network down to the individual user. It’s also used to upgrade the agents on the endpoints.
Deep Instinct is marketing its security solution to Fortune 500 companies.
On the drawing board is a version for network monitoring, the company said. That version will be able to detect malicious traffic faster than current solutions because it can look at fewer packets before identifying that traffic.
Better Sharing Needed
Security pros recognize that sharing information with others is important to the security of all, but they acknowledge that barriers remain preventing effective sharing from taking place.
Nearly half the respondents (47 percent) said their organizations had suffered a material security breach. Nearly two-thirds of those respondents (65 percent) said they could have prevented or minimized the impact of attacks if they’d had the right threat intelligence.
Liability and trust remain major barriers to sharing, the researchers found. More than half the organizations represented by the survey sample (62 percent) said potential liability prevented them from sharing information, and 60 percent said trust issues with others kept them from sharing.
Barriers Beyond Liability
A bill in Congress — the Computer Intelligence Sharing and Protection Act — could address the liability issue. It has received Senate approval and is now hung up between the houses
“If Congress passed and the president signed into law tomorrow a bill limiting liability, I don’t think that will open up the sharing flood gates,” said IID Vice President Mark Foege.
“It is a barrier, but it is not the only barrier,” he added.
Trust would remain a barrier, Foege noted — organizations not trusting others they don’t have a relationship with or might compete with or that just don’t have any information they need or want.
There are technology barriers, too. “Not every organization is set up to exchange their threat indicators. Most are set up to receive them, but not everybody is set up to send them,” he said.
“That being said, we have to work together to make sure that liability as a barrier gets removed so we can move forward across all organizations,” Foege added.
- Nov. 2. Imperva Incapsula releases third-quarter DDoS report finding a quarter-to-quarter increase in DDoS attacks of 116 percent. DDoS botnet traffic from China increased during the period from 14.9 to 37.5 percent, it reported.
- Nov. 3. Dow Corning files for a preliminary injunction against two former contractors, Anjaneyulu Chaganti and Homi Syodia, to prevent them from destroying, altering or transferring any data taken from Corning’s computers. The contractors allegedly downloaded illegally confidential information about Corning’s employees.
- Nov. 4. JPMorgan Chase CSO Jim Cummings is transferred to Texas to work on veteran and military housing initiatives following a data breach last year that compromised confidential information of 83 million customers, Bloomberg Business reports, citing a confidential memo.
- Nov. 4. The U.S. Office of Personnel Management, which suffered the data theft of personal information for 21.5 million people earlier this year, announces hiring of Clifton Triplett as a senior cyber and information technology advisor to the acting director of the agency, Beth Cobert.
- Nov. 4. ShowTix4U notifies an unspecified number of customers that their payment card information may have been compromised in data breach that occurred from April to September.
- Nov. 4. UK Home Secretary Theresa May unveils legislation to give government sweeping surveillance powers, including the right to discover the websites that anyone visits.
- Nov. 5. Ninety 90 percent of 276 board directors and senior executives believe regulators should hold companies liable if they don’t properly secure their data, a survey by the New York Stock Exchange and Veracode reveals.
- Nov. 6. Communications and broadband provider TalkTalk discloses that 156,959 customers were affected by data breach discovered two weeks ago.
- Nov. 6. Cox Communications agrees to pay a $595,000 fine to the Federal Communications Commission in connection with data breach in August 2014. During the attack, a Cox customer service representative and a contractor were persuaded to enter their credentials into a rogue website.
- Nov. 6. Touchnote sends email alert to its users that their identity information is at risk due to a data breach discovered Nov. 4. No financial information was accessed in the attack, the company says.
- Nov. 6. Personal information of law enforcement officials that appears to have been stolen from an FBI Internet portal is posted to the Web. Group that hacked into the email account of CIA Director John Brennan claims responsibility for breach.
- Nov. 7. Four Winds Casino in Michigan alerts patrons that their payment card information may have been compromised in a data breach at three of its locations between October 2014 and Oct. 21, 2015.
Upcoming Security Events
- Nov. 13-14. B-Sides Delaware. Wilmington University, New Castle Campus, 320 North Dupont Highway, New Castle, Delaware. Free with registration.
- Nov. 14. B-Sides Charleston. Tides Folly Beach Hotel, Charleston, South Carolina. Free with registration.
- Nov. 14-15. B-Sides Winnipeg. King’s Head Pub, 120 King St., Winnipeg, Manitoba. Admission: $20 (includes a meals on each day).
- Nov. 18. Leverage Machine Learning Using Splunk User Behavioral Analytics. Noon ET. Webinar sponsored by Splunk. Free with registration.
- Nov. 19. The Business of Phishing: How Phishing Erodes Corporate Trust and Decreases Revenue. Noon ET. Webinar sponsored by Agari. Free with registration.
- Nov. 21. B-Sides Vienna. NIG – Neues Intitutsgebude, Universittsstrae 7 1010, Vienna, Austria. Free.
- Nov. 21. B-Sides Jacksonville. The Sheraton Hotel, 10605 Deerwood Park Blvd., Jacksonville, Florida. Free.
- Nov. 24-25. Cyber Impact Gateway Conference. ILEC Conference Centre and Ibis London Earls Court, London, UK. Registration: Before Oct. 9 — end users, 1,799 pounds plus VAT; solution providers, 2,799 pounds plus VAT. Before Oct. 30 — end users, 1,899 pounds plus VAT; solution providers, 2,899 pounds plus VAT. Standard — end users, 1,999 pounds plus VAT; solution providers, 2,999 pounds plus VAT.
- Dec. 7-9. Gartner Identity & Access Management Summit. Caesars Palace, 3570 Las Vegas Blvd. South, Las Vegas. Registration: $2,695; public sector, $2.225.
- Dec. 12. Threats and Defenses on the Internet. Noon ET. Northeastern University, Burlington Campus, 145 South Bedford St., Burlington, Massachusetts. Registration: $6.
*ECT News Network editor’s note – Nov. 11, 2015: Our original published version of this story quoted Deep Instinct CTO Eli David as saying, “The other solutions average 79 percent.” That is incorrect, according to Deep Instinct spokesperson Lynda Starr, who informed us that the best solution out of the 61 solutions is 79 percent. | <urn:uuid:9db6e091-7df6-4bc3-84a7-8162e91d475f> | CC-MAIN-2022-40 | https://www.crmbuyer.com/story/deep-learning-app-targets-malware-82728.html | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335609.53/warc/CC-MAIN-20221001101652-20221001131652-00557.warc.gz | en | 0.913786 | 2,427 | 2.6875 | 3 |
Days are long gone when we used to interact with the Internet as an undifferentiated network. The reality today is that what we communicate online is mediated by companies that own and operate the Internet services we use. Social media in particular have become, for an increasing number of people, their windows on reality. Whether, and in what ways, those windows might be distorted — by corporate practices or government directives — is thus a matter of significant public importance (but not always easy to discern with the naked eye).
Take the case of WeChat — the most popular chat application in China, and the fourth largest in the world with 806 million monthly active users. WeChat is more than just an instant messaging application. It is more like a lifestyle platform. WeChat subscribers use the app not only to send text, voice, and video but to play games, make mobile payments, hail taxis, and more.
As with all other Internet services operating in China, however, WeChat must comply with extensive government regulations that require companies to police their networks and users, and share user data with security agencies upon request. Over numerous recent case-study reports, Citizen Lab research has found that many China-based applications follow these regulations by building into their applications hidden keyword censorship and surveillance. WeChat is no exception, although with a twist.
Today, we are releasing a new report, entitled “One App, Two Systems: How WeChat uses one censorship policy in China and another internationally.” For this report, we undertook several controlled experiments using combinations of China, Canada, and U.S. registered phone numbers and accounts to test for Internet censorship on WeChat’s platform. What we found was quite surprising.
Turns out that there is substantial censorship on WeChat, but split along several dimensions. There is keyword filtering for users registered with a mainland China phone number but not for those registering with an international number. However, we also found that once a China-based user had registered with a mainland China phone number, the censorship follows them around — even if they switch to an international phone number, or work, travel, or study abroad. To give some context, there are roughly 50 million overseas Chinese people working and living abroad. China’s “One-App, Two Systems” keeps them under the control of China’s censorship regime no matter where they go. This extra-territorial application of information controls is quite unique, and certainly a disturbing precedent to set.
We also found censorship worked differently on the one-on-one versus the “group” chat systems. The latter is a WeChat feature that allows chat groups of up to 500 users. Our tests found censorship on the group chat system was more extensive, possibly motivated by the desire to restrict speech that might mobilize large groups of people into some kind of activism. There is also censorship of WeChat’s web browser — but, again, mostly for China-registered users.
Finally, and most troubling, we found that WeChat no longer gives a notice to users about the blocking of chat messages. In the past, users received a warning saying they couldn’t post a message because it “contains restricted words.” Now if you send a banned keyword, it simply doesn’t appear on the recipient’s screen. It’s like it never happened at all. This type of “silent” censorship is highly unlikely to be noticed by either communicating party unless one of them thinks to double check (or researchers like us scrutinize it closely).
By removing notice of censorship, WeChat sinks deeper into a dark hole of unaccountability to its users.
Research of this sort is essential because it helps pull back the curtain of obscurity that, unfortunately, pervades so much of our digital experiences. As social media companies increasingly shape and control what users communicate — shape our realities — they affect our ability to exercise our rights to seek and impart information — to exercise our human rights.
China may offer the most extreme examples, as our series of reports on China-based applications has shown, but they are important to study as harbingers of a possible future. To wit, as our report is going to publication Facebook is reportedly developing a special censorship system to comply with China’s regulations, one that would “suppress posts from appearing in users’ news feeds.” Along with WeChat’s “One App, Two Systems” model, the services these two social media giants are offering go a long way to cementing a bifurcated, territorialized, and opaque Internet.
Read the full report here: https://citizenlab.org/2016/11/wechat-china-censorship-one-app-two-systems | <urn:uuid:1b6cab53-43ee-4d88-bbe2-93b18a2fa283> | CC-MAIN-2022-40 | https://deibert.citizenlab.ca/2016/11/wechat/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337473.26/warc/CC-MAIN-20221004023206-20221004053206-00557.warc.gz | en | 0.94851 | 986 | 2.625 | 3 |
What is considered as a connected route in the routing table ?
- An interface is configured with an IP address and mask,the configured subnet is installed as connected in the routing table.
- A static route is configured with only an outgoing interface, and not an IP next-hop.
!-- These routes are considered connected ip route 192.168.12.0 255.255.255.0 Serial1/1 ip route 192.168.21.0 255.255.255.0 F0/0
How are these connected routes advertised ?
We have multiple options for advertising a connected route, listed as follows:
- A network command configured that covers any connected network whether defined under the interface or in a static route pointing to the interface.
ip route 192.168.12.0 255.255.255.0 serial1/1 !-- The static route will be advertised by the network statement below router eigrp 10 network 192.168.12.0
- Redistribute connected under any routing protocol.
- Redistributing one routing protocol into another, by default the connected routes advertised by the redistributed protocol will be included. | <urn:uuid:01a3d648-94c8-4919-9575-ad77577ae9a3> | CC-MAIN-2022-40 | https://www.networkers-online.com/blog/2008/10/connected-routes-advertisment/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337625.5/warc/CC-MAIN-20221005105356-20221005135356-00557.warc.gz | en | 0.906345 | 239 | 2.671875 | 3 |
Using technology to increase voting numbers, increase the speed, but also ensure that it is safe.
By utilizing security methods of blockchain, mixed with two form factor authentication, encryption, something you know method (password-phrase-pin), mixed with other methods.
Basically, my thought for making voting more secure is this:
Signing Up / What if locked out / forgot password:
Voter registers with their local government for online voting.
The staff then goes online to the federal and state approved election vendor to input the data.
They receive a randomized nine digit snail-mailed PIN. (Like your bank card pin)
Then they receive an email, with their username and initial password.
Username will not be something to remember. More like randomized generated user ID
Example: JR12345678 (First letter of their first name and last name with random eight digits behind it. Making it ten characters.
Password will be something that much be changed every 90 days, or before an election.
Must be 10 or more characters
Must include at least one upper and one lower letter
Must include at least two numbers
Must include at least two special characters (!@#$%^&*)
During password resets / changes, the voter will not be able to reuse past 12 passwords
Lockout if tried more than five times incorrectly
Five unique questions and answers to unlock.
If you get locked out, you have to wait 15 minutes, then 60 minutes, then five hours, then have to request manual reset, by calling to verify your information.
When performing password login, change, reset, or forgot password, you MUST have that nine digit pin that was snail-mailed to you.
Enter two-form factor unique ID
Sounds like a lot, but it will ensure a few methods… Something you know, something you have, something you are, etc.
How to log in - to vote:
**Preferred method would to use a cell phone, with iris and/or fingerprint locking technology. **
- Log into the website or mobile app.
- Enter your randomized username.
- Enter your password.
- Enter your randomized snail-mailed pin.
- Enter your drivers license number.
- Verify via pictures captcha pictures.
Then just like any other online poll, you vote as you desire.
Then the information is actively saved after every function. In case of internet outage, phone call, power outage, etc.
The voters have the ability to return after their interruption at where they left off.
Once submitted, the results will be instantly updated at the national / state / local levels (pending the election purpose).
At the end of your voting, before you click Submit. You have two review steps…
Review all your choices, without the hassle. Literally it will just show the voting topic, and your selection.
After you approve that first review, you will get a second time to review once more, but have to verify your information by entering your PIN.
How the voting log in and results are submitted / verified:
By utilizing BlockChain methods and Ransomware encryption methods, each local, county, state, and federal voting precinct will be the authenticator that randomly checks/verified the data, automatically.
What about hackers?
Naturally, any system that is connected to the internet, is possible to be hacked. Even the current election system has potential for hackers to over turn results, etc. However, having all these checks and balances in the system, using 256bit encryption or greater, such as those famous Ransomware virus’s, mixed with BitCoin BlockChain methods, then combine that with randomized username, difficult passwords, authenticator, and snail mailed pin, the chances at breaking into the system are next to nothing. But nothing is 100%, except death and taxes. So, they say.
What if it is election day and I cant get into my account?
Naturally, there will be federal, state, and local election poll workers, to “man” the phones. As well as having the Department of Elections approved vendor support staff assisting the poll workers.
How do you make sure that you are indeed the voter and not someone else?
By using all these checks and balances, maybe add photo of voters drivers license and “selfie” to verify vote presence, during voting. Unless the previous systems are fair enough to please administrations.
What are your thoughts? | <urn:uuid:e368ec60-f930-4046-8ef5-257e9f7aa9b6> | CC-MAIN-2022-40 | https://forums.lawrencesystems.com/t/idea-for-new-voting-system-thoughts/6858 | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334802.16/warc/CC-MAIN-20220926051040-20220926081040-00757.warc.gz | en | 0.920571 | 940 | 2.671875 | 3 |
VoIP or Voice over Internet Protocol can be explained as the process by which data is transmitted via the internet. VoIP refers to voice communication over IP networks. VoIP is an extension of internet telephony services that offers many advantages over traditional phone service. It is useful for smooth communication in offices and in public relay systems.
VoIP is also known as Internet Telephony. SIP trunking refers to this voice over internet protocol technology and digital voice service based on the Session Initiation Protocol, which enables voice communication over internet lines. This service offers significant cost savings, increased productivity, flexibility, and portability.
VoIP is an extension of normal phone service provided over the public switched telephone network (PSTN). The basic service allows people to send and receive calls over the internet. The term ‘voice over internet protocol’ (VoIP) is sometimes used to refer to VoIP phone services which are not based on the PSTN infrastructure. The term is used as a verb with an IP attached. A VoIP network has links with internet-based extension service provider (ISP).
The major advantage of VoIP over regular phone service is that calls made using a VoIP phone are routed over the internet rather than over the public switched telephone network. Also, a subscriber can use any type of telephone even though it is connected to the same network as the VoIP service. So, while one is making a long-distance call, the other can use the VoIP instead of the traditional PSTN telephone.
So, how does VoIP Trunking work? VoIP trunking allows voice data to be sent over a single connection from a client (PC) to a server (edge). A VoIP server is simply a software that receive VoIP information, routes it over the internet, and then sends it back to the client. This process is rather simple and is what makes it possible for information sent to a computer to be entirely managed by that computer.
When a phone is connected to the internet, a number of factors come into play. The first is the physical configuration of the telephone. It is used to establish how it is connected to a particular VoIP service so that all relevant data can be passed to the right location. An important component in this connection is the IP address of the VoIP service.
This IP address is used to identify the particular telephone number in question and also to control the communication that is going on between the caller and the receiver. The other factor is the quality of the signal that is being transmitted over the internet. The Internet backbone such as the Internet Service Provider or ISP usually controls the quality of the data that is being transmitted. Once the data has been converted into VoIP, this information is then routed through the IP network so that it can reach the telephone number that is being dialed.
There are two types of VoIP services. One is the basic VoIP service, which is what is VoIP trunking service. This is the actual conversion from analog audio signals to digital data that is later converted back to analog. The other type is what is called an intermediate service that converts the digital data into VoIP so that the end users will be able to enjoy the advantages that VoIP provides.
When you are using this kind of system, it is important that you have an appropriate phone that is compatible with the system. You have to keep in mind that not all phones will work with VoIP because the digital information is different. You should make sure that your telephone is compatible with what is VoIP and not the analog signal that are coming through the telephone line. In order for you to be able to find out the kind of telephone that will work well with what is VoIP, you can try to get advice from people that are already using this service.
You can also look for what is VoIP trunking service on the web. You will be able to get a lot of information about this system which will help you to decide if it would be something that would be of interest for you. This system has many advantages and some of them are that it does not need any wires to transfer the phone information from one location to another. Also, this type of system allows you to have a high speed connection to the internet which is handy when you need to download any information quickly.
However, there are some disadvantages as well when you consider what is VoIP trunking service. The VoIP system does not support what is known as ‘handed’ call connections, and this means that you may find that you cannot connect with certain people who are on the opposite end of the network. Also, the VoIP system does not allow you to make conference calls but this is something that you can do when you are using a dedicated IP telephony system. It is a good idea to look into these disadvantages before you decide to switch over to what is VoIP. | <urn:uuid:d7add303-8a86-40ca-ab4c-39e4f664f1c4> | CC-MAIN-2022-40 | https://ringleader.co/blog/what-is-voip-trunking-service/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334802.16/warc/CC-MAIN-20220926051040-20220926081040-00757.warc.gz | en | 0.96171 | 998 | 3.765625 | 4 |
How to Encrypt Designated iOS Strings with In-App Secrets
Learn to Encrypt Strings and in App Secrets in iOS apps, in mobile CI/CD with a Data-Driven DevSecOps™ build system.
What is Strings and in-app Secrets encryption?
String and in app encryption is all the ways an app can statically encrypt/hide its sensitive strings from static analysis, while maintaining the same expected behavior when running the app on a device.
Most of the raw strings you define in your swift app code will be stored after compile in the result binary in certain sections. Those strings can be anything, error messages , hardcoded passwords or names, classes names, hints about data transferred to the server or hints about the flow of the program. generally speaking, when executing a program, your program will refer to those strings when needed in your code flow at the right time.
Raw strings of your app can be checked with simple tools, like MachoView or Otool, and view them in their sections.
Why encrypt Strings and in-app secrets ?
Along with raw strings, all sensitive strings will be referred from your app code and those connections can be viewed by reversing tools like IDA/Ghidra, which gives the attacker knowledge about what conditions or circumstances will lead to the usage of a specific string and make the reversing of your app much easier and exposed.
Obfuscation is used against static reverse engineering attempts, one of the measures is encrypt the string/obfuscate them. This obfuscation should change the name of your sensitive in-app strings while maintaining the same expected behavior in the run time of your app.
Encrypting Strings and in App Secrets on iOS apps by Using Appdome
On Appdome, follow these 3 simple steps to create self-defending iOS Apps that Encrypt Strings and in App Secrets without an SDK or gateway:
Upload the Mobile App to Appdome.
Upload an app to Appdome’s Mobile App Security Build System
Upload Method: Appdome Console or DEV-API
iOS Formats: .ipa
Build the Protection: Encrypt Strings and in App Secrets.
Congratulations! The Encrypt Strings and in App Secrets protection is now added to the mobile app
Building Encrypt Strings and in App Secrets by using Appdome’s DEV-API:
Create and name the Fusion Set (security template) that will contain the Encrypt Strings and in App Secrets feature as shown below:
Follow the steps in Sections 2.2.1-2.2.2 of this article, Building the Encrypt Strings and in App Secrets feature via Appdome Console, to add the Encrypt Strings and in App Secrets feature to this Fusion Set.
Open the Fusion Set Detail Summary by clicking the “...” symbol on the far-right corner of the Fusion Set, as shown in Figure 1 above, and get the Fusion Set ID from the Fusion Set Detail Summary (as shown below):
Figure 2: Fusion Set Detail Summary
Note: Annotating the Fusion Set to identify the protection(s) selected is optional only (not mandatory).
Follow the instructions below to use the Fusion Set ID inside any standard mobile DevOps or CI/CD toolkit like Bitrise, App Center, Jenkins, Travis, Team City, Cirlce CI or other system:
Figure 1: Fusion Set that will contain the Encrypt Strings and in App Secrets feature
Note: Naming the Fusion Set to correspond to the protection(s) selected is for illustration purposes only (not required).
Building the Encrypt Strings and in App Secrets feature via Appdome Console
To build the Encrypt Strings and in App Secrets protection by using Appdome Console, follow the instructions below.
Where: Inside the Appdome Console, go to Build > Security Tab > TOTALData™ Encryption section
How: Toggle (turn ON) Encrypt Strings and in App Secrets, as shown below.
Figure 3: Encrypt Strings and in App Secrets option
When you select the Encrypt Strings and in App Secrets you'll notice that your Fusion Set you created in step 2.1.1 now bears the icon of the protection category that contains Encrypt Strings and in App Secrets
Figure 4: Fusion Set that displays the newly added Encrypt Strings and in App Secrets protection
- Optional Configuration with Encrypt Strings and in App Secrets:
- Advanced In-App Secrets Protection
Encrypt application specific sensitive data such as keys, shared secrets and tokens.
Click Build My App at the bottom of the Build Workflow (shown in Figure 3).
Certify the Encrypt Strings and in App Secrets feature in iOS Apps.
After building Encrypt Strings and in App Secrets, Appdome generates a Certified Secure™ certificate to guarantee that the Encrypt Strings and in App Secrets protection has been added and is protecting the app. To verify that the Encrypt Strings and in App Secrets protection has been added to the mobile app, locate the protection in the Certified Secure™ certificate as shown below:
Figure 5: Certified Secure™ certificate
Each Certified Secure™ certificate provides DevOps and DevSecOps organizations the entire workflow summary, audit trail of each build, and proof of protection that Encrypt Strings and in App Secrets has been added to each iOS app. Certified Secure provides instant and in-line DevSecOps compliance certification that Encrypt Strings and in App Secrets and other mobile app security features are in each build of the mobile app
Prerequisites to Using Encrypt Strings and in App Secrets:
To use Appdome’s mobile app security build system to Encrypt Strings and in App Secrets , you’ll need:
- Appdome account (create a free Appdome account here)
- A license for Encrypt Strings and in App Secrets
- Mobile App (.ipa For iOS)
- Signing Credentials (see Signing Secure iOS and Android apps)
Using Appdome, there are no development or coding prerequisites to build secured Apps by using Encrypt Strings and in App Secrets. There is no SDK and no library to code or implement in the app and no gateway to deploy in your network. All protections are built into each app and the resulting app is self-defending and self-protecting.
Releasing and Publishing Mobile Apps with Encrypt Strings and in App Secrets
After successfully securing your app by using Appdome, there are several available options to complete your project, depending on your app lifecycle or workflow. These include:
- Customizing, Configuring & Branding Secure Mobile Apps
- Deploying/Publishing Secure mobile apps to Public or Private app stores
- Releasing Secured Android & iOS Apps built on Appdome.
All apps protected by Appdome are fully compatible with any public app store, including Apple App Store, Google Play, Huawei App Gallery and more.
Protections Similar to Encrypt Strings and in App Secrets
If you have any questions, please send them our way at support.appdome.com or via the chat window on the Appdome platform.
Thanks for visiting Appdome! Our mission is to secure every app on the planet by making mobile app security easy. We hope we’re living up to the mission with your project. | <urn:uuid:d4b7e2ae-d124-4245-a182-5374e4ff44df> | CC-MAIN-2022-40 | https://www.appdome.com/how-to/mobile-app-security/mobile-data-encryption/encrypt-designated-ios-strings-with-in-app-secrets/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335034.61/warc/CC-MAIN-20220927131111-20220927161111-00757.warc.gz | en | 0.871202 | 1,588 | 2.671875 | 3 |
In Europe, typically the E1 Primary Rate Interface is provided by telecommunication service providers. It has a gross data transmission rate of 2.048 megabits per second and is divided into 32 channels with 64 kilobit per second each. Out of these 32 channels, 30 channels are so-called B-channels, which are available as bearer channels. The data transmission rate of all bearer channels together comes to 1920 kilobit per second. The two remaining channels are divided into a 64 kilobit per second signalling channel (D-channel) and a 64 kilobit per second synchronisation channel.
The electrical S2M interface is mostly used as the line interface between the telephone system and the network. It can be installed in the direction of transmission on the basis of a twin wire or a coaxial transmission line. Generally, two twin wires with shielding are provided in the direction of the end device. Since a ternary HDB3 code with three electrical states is used for the line coding, the data transmission rate of 2048 kilobit per second is reached despite a bandwidth of only one megahertz.
Primary Rate Interface is set up as a point-to-point connection with a telephone number block. This consists of a main telephone number and a telephone number block for the phone extensions. Thus, the end devices have to be dialled directly. The telephone system handles the task of assigning the extension numbers to the end devices. In addition to a telephone number block with up to 99 numbers, it is possible to apply for a three-digit telephone number block with the provider and the Federal Network Agency.
With the extensive introduction of VoIP telephone, the Primary Rate Interface is becoming less and less significant. IP telephone systems can, in principle, be operated via any internet connection. The maximum number of calls that can be made in parallel depends on the bandwidth and the quality of the internet connection. | <urn:uuid:7cc985d7-5793-4d59-a1cc-59193fcbba58> | CC-MAIN-2022-40 | https://www.nfon.com/en/get-started/cloud-telephony/lexicon/knowledge-base-detail/primary-rate-interface-pri | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335286.15/warc/CC-MAIN-20220928212030-20220929002030-00757.warc.gz | en | 0.919333 | 389 | 2.828125 | 3 |
In this blog, we take a closer look at the concept of privacy-preserving synthetic data. We answer the question “what is synthetic data” and look at the origin of synthetic data in the context of data privacy. We also present one way of generating privacy-preserving synthetic data and its benefits for organizations.
In a general sense, synthetic data is information that is artificially generated, as opposed to collected from the real-world. But it’s important to note that synthetic data is used for a variety of purposes. As a result, there are several types of synthetic data with different properties depending on the use-cases.
For instance, one scenario in which companies use synthetic data is the training of AI/ML models. Real-world data is sometimes expensive to collect, or simply hard to come by. If you take for instance self-driving vehicles, the development of software for autonomous driving involves considerable volumes of data.
In these cases, synthetic data is easier to produce than collecting real-world driver data. It also allows the training of models on a wide variety of situations that real-world data might not capture.
Another scenario in which companies use synthetic data is to make information available for processing when regulations or other privacy concerns restrict access to the original data. For instance, the processing of customer data in a post-GDPR world involves strict compliance and governance rules for companies.
In these cases, synthetic data is used as an anonymization method that brings companies more agility and freedom to process data in a safe and compliant way. This is what we focus on in this article, synthetic data in the context of privacy preservation.
When companies use synthetic data as an anonymization method, a balance must be met between utility and the level of privacy protection. In this context, utility refers to the analytical completeness and validity of the data. This means that synthetic data should provide, from an analytics point of view, the closest value to real-world data. Privacy refers to the protection of information on individual data. The method used to generate synthetic data will affect both privacy and utility.
At Statice, we developed algorithms that learn the statistical characteristics of the original data and create new data from them. As a result, a synthetic dataset consists of new data points that preserve to a high degree the statistical properties and structure of the original dataset. This is done in order to maximize the utility of synthetic data.
We also implemented privacy mechanisms, so our algorithms generate privacy-preserving synthetic data. This means that private and sensitive information of an individual present in the original dataset will be protected after releasing the synthetic dataset.
For instance, one of these mechanisms is to train the model using algorithms that satisfy the definition of differential privacy. A model respecting this definition guarantees that the synthetic data is robust against all sorts of privacy attacks, for example which could lead to the re-identification of an individual. The main premise of this approach is that in synthetic data produced with such a model, it is impossible to tell whether a single individual was part of the original dataset or not.
Privacy-preserving synthetic data preserves to a high degree the properties and statistical information of the original data. This means that the utility of the synthetic data should be high enough to allow drawing similar conclusions as one would from the original data.
It retains the data structure of the original data. This means it should be possible to use the same code and tools on synthetic data than on the original data, without the need for any modification.
No information can be learned about a particular individual from privacy-preserving synthetic data. It should not be possible to tell whether a real-world individual was a part of the original dataset.
The idea of privacy-preserving synthetic data dates back to the 90s when researchers introduced the method to share data from the US Decennial Census without disclosing any sensitive information. The US Census Bureau has since been actively working on generating synthetic data.
While it has been around since the 90s, the last decade saw a growing interest from both the public and private sectors. In 2018, synthetic data and differential privacy were the subjects of an innovation challenge run by the US National Institute of Standards and Technology. In 2019, Deloitte and the World Economic Forum's team released a study highlighting the potential of privacy-enhancing technologies, including synthetic data, in the future of financial services.
A reason for the growing interest in privacy-preserving synthetic data is the fact that it addresses some of the shortcomings of traditional “anonymization” methods, such as pseudonymization or k-anonymity. As we explained in a previous blog, not all anonymous data is created equal.
Some of the techniques currently used present limitations when it comes to guaranteeing the privacy or utility of the data. As a result, researchers are always looking for new or improved methods to overcome this trade-off between data utility and privacy. Today, privacy-preserving synthetic data represents an alternative to other traditional methods like pseudonymization.
It’s important to note that different methods produce different types of synthetic data. As opposed to partially synthetic data, where only a selection of the dataset is replaced with synthetic data, fully synthetic data doesn’t contain any of the original data. Depending on the approach, privacy-preserving fully synthetic has the potential of providing a stronger privacy guarantee, without significant loss on utility.
One way of generating synthetic data is to use deep generative models. As the name suggests, these models are a way of generating data that rely on deep learning techniques. They can learn the statistical distribution underlying in the data in an unsupervised way and generate new data by sampling from it.
A famous example of leveraging deep generative models is the phenomenon of deep fakes. To create these artificial images or videos, algorithms train on real-word data to produce synthetic media that mimic the original subject but aren’t real. Similarly, if you train deep generative models on datasets containing people’s pictures, they can recreate synthetic faces mimicking human faces features. These new faces are entirely artificially generated.
Generating privacy synthetic data is similar, except that the data we work with at Statice isn’t images or videos. Rather, our software can generate privacy-preserving synthetic data from structured data such as financial information, geographical data, or healthcare information.
Because it holds similar statistical properties as the original data, synthetic data is an ideal candidate for any statistical analysis intended for original data. A common use-case is thus to make data available for processing when regulations or other privacy concerns restrict access to the original data. This processing can be of multiple nature:
Many organizations started using privacy-preserving synthetic data because it offers many benefits and a good ROI. One of the most significant ones is the ability to overcome sensitive data usage restrictions while safeguarding individuals’ privacy.
Indeed, in today’s highly regulated data landscape, processing data for secondary purposes, such as analysis, is often not only complex and time-consuming, but it also presents multiple security risks. With privacy-preserving synthetic data, an organization gets the ability to:
Besides the data anonymization field, another interesting aspect of working with synthetic data is that for large volumes of data, the production cost can be lower than for real-world data. Today, the training of machine learning and AI systems require huge amounts of data. Synthetic data offers a cost-effective alternative for organizations.
Synthetic data holds a lot of potential. In essence, the idea of synthetic data is to be used just like real data, while protecting sensitive information and safeguarding the privacy of individuals. In a world where regulatory bodies are strengthening data protection laws, where citizens are asking for more privacy, and where data breaches are putting businesses and individuals at risk, privacy-preserving synthetic data can help companies protect their sensitive data while remaining data-driven and innovative.
Contact us and get feedback instantly. | <urn:uuid:0ae8678a-c5a9-4c07-8c43-5040a73a1209> | CC-MAIN-2022-40 | https://www.statice.ai/post/what-is-synthetic-data-introduction | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335286.15/warc/CC-MAIN-20220928212030-20220929002030-00757.warc.gz | en | 0.913338 | 1,628 | 3.28125 | 3 |
Schools have always had a battle on their hands when it comes to cyber security; then Covid-19 stepped on to the scene.
The Covid-19 pandemic has resulted in significant cyber security uncertainty on a global level. Carefully tailored spear phishing, ransomware attacks and contact-tracing scams have already created widespread fear. Now the stakes have become higher than ever regarding cyber attacks targeted towards schools and the education sector.
Schools have significant cybersecurity shortfalls
Funding concerns for cyber security systems, regulatory complexity and a clear lack of skilled staff and resources to identify security risks will never help improve a school’s overall security posture. Schools as a result are far more likely to make basic configuration errors in system setup or leave known vulnerabilities unpatched – effectively leaving the door wide open for hackers and other opportunist cyber criminals.
“A severe lack of funding for cyber security hasn’t made it any easier to keep data secure – and that issue became even more apparent when classes moved to an online environment. With this digital transformation schools now need to look way beyond industry data to find gaps in their security.”
Security Director – Infosec Partners
THE REAL IMPACTS OF A SUCCESSFUL BREACH ARE CLEAR
- Disruption to classes & education
- Exposure to identity theft
- Compromised equipment
- Data loss
- Resultant costs, liabilities and regulatory fines
In this article we will be looking at the key security concerns that schools are currently facing and how these security gaps can be closed with maximum effect.
The Biggest Threats to Schools Include:
Data Loss & Data Breach
A data breach is the release of secure confidential information.
Educational establishments including schools, colleges and universities all share a culture that promotes sharing of information. However, due to the information they safeguard and control, they face very similar issues as most other businesses when it comes to protecting their data.
With data regarding parents, students, research data, payment information, health records, and other sensitive data, educational establishments must facilitate a secure environment for its students and staff by implementing data loss prevention measures.
- End users should receive training advice on what data they are responsible for protecting and how the information should be handled
- Encryption services should be used for any data that needs to be sent via email.
- Establish processes for what to do if a data breach occurs.
- Consider insurance to cover the cost of mitigating the damage in the case a data reach should occur.
- Security systems should be audited by a 3rd party to ensure compliance
Phishing and Spear Phishing are tactics scammers use to trick email recipients into providing confidential information such as usernames, passwords and network credentials. Implementing email security is essential in combating the spread of malicious emails as well as training staff to detect and report suspicious emails can significantly reduce the risk of systems being compromised.
Ransomware attacks are where hackers encrypt data files and systems through malicious software and request a ransom to regain access. The most effective response to regain access to data is to backup data on a server that is not accessible to the rest of the school’s network and therefore is not vulnerable to ransomware encryption agents.
One of the biggest cyber security threats to a school is its staff. Most breaches occur from either human caused factors due to poor decision making processes, deliberate sabotage or external financial manipulation. However, poor decision making doesn’t always relate to reckless behaviour of those responsible but more likely is due to poor understanding of cyber security as a process.
BYOD & IoT
Allowing staff and students to use their own devices provides significant cyber security and data protection risks. Unless this is effectively managed the BYOD model can introduce new risks into the classroom – particularly to safety and security. IoT devices in schools might include interactive whiteboards, virtual reality, robots, tablets and laptops, 3-D printers devices and other devices that may be student or teacher owned. IoT devices should be isolated to a separate VLAN where they can be monitored and don’t have access to the rest of the school’s network. Also make sure all default passwords are changed on the IOT devices.
Web security and content filtering helps safeguard digital learning in and out of the classroom by blocking inappropriate content, malware and phishing scams.
Our managed SIEM service helps limit any disruptions to learning by highlighting anomalies, such as those indicative of insider threats, to increase response time.
Our IAM service provides a more secure and streamlined access to online learning resources and provides increased protection of student and faculty data, even if passwords are compromised or stolen.
Managed Network Access Control (NAC)
Our Network Access Control service provides schools with a perfect balance between security and usability by authorising who is allowed network access, when, where and from what devices.
Email is one of the top attack vectors for cyber criminals. Infosec Partners can provide comprehensive protection for staff and student email accounts under the school’s control; from spam, malware, phishing and other advanced threats. Our Managed Email service scans inbound and outbound email for viruses, spam and malware to identify suspect messages before they reach your servers.
Managed Backup and Disaster Recovery
Our managed backup and disaster recovery service provides rapid data restoration in the event of a breach and protects against costly ransomware payouts and minimises classroom interruptions.
To arrange a free consultation for your school, please contact Infosec Partners today.
call +44 (0)1256 893 662 or email firstname.lastname@example.org | <urn:uuid:a122d365-9157-44d8-b2a5-8560ef4928eb> | CC-MAIN-2022-40 | https://www.infosecpartners.com/back-to-school | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337889.44/warc/CC-MAIN-20221006222634-20221007012634-00757.warc.gz | en | 0.938893 | 1,170 | 2.78125 | 3 |
An unprecedented ransomware cyberattack that researchers believe was developed using tools stolen from the National Security Agency (NSA) has struck tens of thousands of computers around the world.
The world witnessed the first ever sweeping cyberattack of its kind on Friday, when a strain of ransomware, now known as ‘WannaCry’, along with other variants of that name, struck number of organizations around the world.
In the UK, the National Health Service (NHS) was adversely impacted, particularly in England and Scotland. According to the BBC, about 40 NHS organizations in the two countries were struck by the ransomware, with medical procedures, surgeries and appointments canceled.
Screenshots shared by NHS staff of the ransomware revealed extortion demands of $300 in Bitcoin, a digital currency, to regain access to files on each computer.
The infections were traced back to a worm, a self-perpetuating program that spreads between computers by infecting them. While common malware programs rely on phishing schemes to trigger a malicious file, WannaCry actively hunts vulnerable and exploitable machines within an organization’s network once it is triggered.
Experts have pointed to tools released by hacker group ‘The Shadow Brokers’ who publicly dumped stolen NSA tools in April. These tools are believed to be built by the NSA to exploit a weakness in Microsoft computers.
For its part, Microsoft has already released a patch for the vulnerability in March. Windows machines with ‘Windows Update’ enabled will have automatically downloaded in patched the exploit. The software giant has also revealed it would roll out the update to users of outdated operating systems that no longer see any support, including the likes of Windows XP, Windows 8 and Windows Server 2003.
Security firm Avast detected some 75,000 cases of the WannaCry ransomware around the world. A growing number of European countries reported the infections on Friday.
Intriguingly, Russia has reportedly seen more infections than any other single country in the world. Russian domestic banks, the interior and health ministries, Russian state-owned railway operator among others were all victims of the ransomware. In Spain, telecom giants Telefonica and utility provider Gas Natural were among a host of others that were struck, before being forced to turn off their computers to evade the infection.
Other giants, including US logistics firm FedEx and French automobile manufacturer Renault, were also struck.Up to 99 countries were affected.
Microsoft’s advisory and details of the patch can be found here.
Image credit: Pixabay. | <urn:uuid:8975c641-bd67-4f30-980f-aeccc4413ceb> | CC-MAIN-2022-40 | https://www.lifars.com/2017/05/ransomware-epidemic-hits-99-countries/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334514.38/warc/CC-MAIN-20220925035541-20220925065541-00157.warc.gz | en | 0.962157 | 512 | 2.828125 | 3 |
As businesses start to open, owners must prepare to protect their employees’ health and safety in the workplace.
Tips for Cleaning Electronics
- Always refer to the manufacturer’s manual for proper cleaning instructions prior to using products on electronics
- Never spray water or cleaner directly onto electronics
- Remove any batteries or disconnect from power prior to cleaning electronics
Desktop / Laptop. Use compressed air to remove any debris caught in between the keyboard keys. To remove dust and smudges from electronics, lightly dampen a microfiber cloth to wipe down the keyboard, mouse, back of the laptop/ desktop tower and any other surrounding electronics found on the desk. Use a cotton swab for hard to reach crevices. Sanitize the area with an alcohol swab, one part alcohol/water mixture or approved electronic cleaner.
Monitors, LCD Screens and Touch Screens. Some glass cleaners have been known to corrode screens. To safely remove oils and germs from screens use water, eyeglass cleaner or approved screen cleaner to dampen a microfiber cloth.
Headsets and Earbuds. Unplug the headset or earbuds from the device. Remove any removable earbud tips or parts to clean with soap and water, rinse completely. Use a damp microfiber cloth to wipe down the rest of the headset and cord. Allow all headphone and earbud sets to dry thoroughly before use. Bluetooth devices should only be cleaned using proper approved cleaners or a dry cloth to prevent internal damage.
Phone and Tablets. Most phone and tablet screens use tempered-glass screen protectors that use a fingerprint-resistant coating. To prevent damage during cleaning, remove the case and wipe it down with a damp microfiber cloth. Use cotton swabs or a damp microfiber cloth to wipe down the device. If the device has a screen protector that doesn’t have a resistant coat, using an alcohol swab or mixture with a microfiber cloth is safe.
The CDC has provided resources to help your company stay healthy and prevent the spread of COVID-19.
Top 10 Tips to Protect Employees’ Health
Actively encourage sick employees to stay home. Develop policies that encourage sick employees to stay at home without fear of reprisals, and ensure employees are aware of these policies.
Have conversations with employees about their concerns. Some employees may be at higher risk for severe illness, such as older adults and those with chronic medical conditions.
Develop other flexible policies for scheduling and telework (if feasible) and create leave policies to allow employees to stay home to care for sick family members or care for children if schools and childcare close.
Talk with companies that provide your business with contract or temporary employees about their plans. Discuss the importance of sick employees staying home and encourage them to develop non-punitive “emergency sick leave” policies.
Plan to implement practices to minimize face-to-face contact between employees if social distancing is recommended by your state or local health department. Actively encourage flexible work arrangements such as teleworking or staggered shifts.
Perform routine environmental cleaning. Routinely clean and disinfect all frequently touched surfaces, such as workstations, counter-tops, handrails, and doorknobs. Discourage sharing of tools and equipment, if feasible.
Consider the need for travel and explore alternatives. Check CDC’s Travelers’ Health for the latest guidance and recommendations. Consider using teleconferencing and video conferencing for meetings, when possible.
Provide education and training materials in an easy to understand format and in the appropriate language and literacy level for all employees, like fact sheets and posters.
If an employee becomes sick while at work, they should be separated from other employees, customers, and visitors and sent home immediately. Follow CDC guidelines for cleaning and disinfecting areas the sick employee visited.
For more information on how to protect your employees health and download a printable PDF, visit: https://www.cdc.gov/coronavirus/2019-ncov/community/guidance-business-response.html | <urn:uuid:c62f5199-c02e-448c-9da0-7ceda01cde72> | CC-MAIN-2022-40 | https://www.ecsoffice.com/prepare-your-business-and-employees-for-the-effects-of-covid-19/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334871.54/warc/CC-MAIN-20220926113251-20220926143251-00157.warc.gz | en | 0.911916 | 855 | 2.5625 | 3 |
Artificial intelligence (AI) is a technology that enables computer systems to accomplish tasks that would normally require human interaction. The use of AI has increased exponentially across all industries over the past several years. AI can help automate labor intensive processes, leading to lower costs and saved time. It can also be used to understand customers better. We are now using AI throughout our daily lives, often without realizing it.
Over the past several years, AI technology has progressed immensely and continues to develop and improve. It has become increasingly proficient at performing tasks that were historically difficult for computers to execute. The successes of AI are also being facilitated by the massive amounts of data we have today, increased computing capabilities, and changing consumer expectations.
AI is composed of several technologies, including but not limited to:
- Machine Learning: Machine learning enables a computer system to make predictions or make some decisions using historical data without being explicitly programmed. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate results or give predictions based on that data.
- Deep Learning: Deep learning is a subset of machine learning that has networks capable of learning from unstructured or unlabeled data without any supervision.
- Neural Networks: Neural networks are a subset of Deep Learning. They can identify, classify and analyze diverse data, and can find patterns that are too complex for a human to recognize. Neural networks rely on training data to learn and improve their accuracy over time.
Where is AI needed in the real world?
Everywhere! One specific area that we’ll cover in this post is the insurance industry. It’s very old, and it relies on manual, time-consuming paperwork. Policies are also not tailored in order to meet every customer’s unique needs. AI can be implemented to design customer-centric policies in order to fit each client.
The wealth of data the insurance industry generates is overwhelming. It needs AI and machine learning tools to unearth the underlying insights in their data that insurers are struggling to take advantage of.
AI has the potential to affect the insurance industry in multiple ways, from understanding risk appetite and premium leakage, to expense management, subrogation, litigation, fraud identification, sales, marketing, and operations.
How is AI being implemented in the insurance industry?
The insurance industry has already begun its venture into AI. Insurers have no other option but to embrace artificial intelligence and machine learning to remain competitive. There are many areas where insurers are adopting AI solutions, below are some notable examples:
- Fraud Prevention: Insurance companies lose billions of dollars a year to fraudulent claims. Artificial intelligence can help insurance organizations query the alleged events of an accident while processing claims. Machine learning algorithms (cluster analysis) can tap into unstructured and semi-structured data, such as claims notes and documents, as well as structured data, to identify potential fraud.
- Lead Management: AI can assist insurers and salespeople in pointing out leads by extracting valuable insights from data. AI can personalize recommendations according to the buyer’s purchase history and potential spend for the salespeople, thereby helping the salespeople to interact more effectively with the buyers.
- Intelligent Virtual Assistants: Chatbots using neural networks can be developed to understand and answer the bulk of customer queries over email, chat, and phone calls. This can free up significant time and resources for insurers, which they can deploy towards more profitable activities.
- Customer Retention: AI can look at a variety of data, including new data sources, to determine risk, which can be used to recommend the best offer that will most likely retain a valuable customer.
- Claims Processing: Claims processing includes multiple stages, including review, investigation, adjustment, and remittance or denial. Speed is critical to customer experience in these processes. Thanks to document capture technologies, businesses can rapidly handle large volumes of documents required for claims processing tasks, detect fraudulent claims, and check if claims fit regulations.
Other applications include risk tolerance calculation and management, claims analysis, asset management, and consistent optimization of customer investments and insurance coverage.
What is the future of AI in the insurance industry?
Companies in this space face numerous challenges. It’s a highly-competitive industry, especially when customers are able to easily compare competitors online. Unfortunately, it has suffered from a long period of underinvestment in new technologies. As insurance companies realize the benefits of AI, they will build upon the above use-cases and find new applications for providing an enhanced customer experience.
AI has the potential to transform the frustrating insurance experience for customers to something fast, on-demand, and more affordable. If insurers start applying AI technology to the abundant data they are sitting on, we will soon start to see more flexible insurance as insurers will be able to better understand what their customers want and need. AI will also make it easier for the customers to interact with the insurance companies, which will result in people being more likely to purchase. | <urn:uuid:df73fbc5-9fe4-4495-bf9c-203d5811738a> | CC-MAIN-2022-40 | https://atrium.ai/resources/how-ai-and-machine-learning-are-helping-the-insurance-industry/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335058.80/warc/CC-MAIN-20220927194248-20220927224248-00157.warc.gz | en | 0.94495 | 1,016 | 2.875 | 3 |
Google releases open source 'Cartographer'
Machine learning and vision are essential technologies for the advancement of robotics. When sensors come together, they can enable a computer or robot to collect data and images in real-time.
A good example of this technology in real-world use is the latest Roomba vacuums. As the robot cleans your dirty floor, it is using sensors combined with a camera to map your home. Today, Google releases Cartographer -- an open source project that developers can use for many things, such as robots and self-driving cars.
"We are happy to announce the open source release of Cartographer, a real-time simultaneous localization and mapping (SLAM) library in 2D and 3D with ROS support. SLAM is an essential component of autonomous platforms such as self driving cars, automated forklifts in warehouses, robotic vacuum cleaners, and UAVs", says Google.
The search giant further shares, "our focus is on advancing and democratizing SLAM as a technology. Currently, Cartographer is heavily focused on LIDAR SLAM. Through continued development and community contributions, we hope to add both support for more sensors and platforms as well as new features, such as lifelong mapping and localizing in a pre-existing map".
You can see Toyota leveraging this open source project with one of its robots in the video below.
In addition to this open source project, Google is also sharing 2D and 3D LIDAR and IMU data that was collected using its backpack platform. This data was collected while the search-giant tested and developed Cartographer, and should be very valuable for developers.
Want to try it for yourself? Check out Cartographer on GitHUb here.
How do you see developers using this open source project? Tell me in the comments. | <urn:uuid:ab2c62d6-ecb4-47d1-9bac-e561c5a157f2> | CC-MAIN-2022-40 | https://betanews.com/2016/10/05/google-open-source-cartographer/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335058.80/warc/CC-MAIN-20220927194248-20220927224248-00157.warc.gz | en | 0.94895 | 374 | 2.703125 | 3 |
“Crucial data pertaining to accounts and finance of State Forest Department of Kerala, India was ‘locked’ by unidentified hackers in mid-March “Reported by The New Indian Express in September 2016
“Reports show that Indian organizations are the third most attacked in the Asia Pacific region. While ransomware attacks declined this year, the attacks are becoming more targeted”. Reported by CISO Magazine eccouncil.org on September 8, 2021
“Tamil Nadu Government Hit By Cyber Attack For Second Time This Year “-Reported on SEPTEMBER 18, 2021, by The Hindu, The New Indian Express, and many other news agencies.
What is a Ransomware attack?
Ransomware is a cyberattack on individual systems or computer servers that uses malicious software to encrypt the entire data. Once affected, the attacker asks for a fee to decrypt the data back to its original state. The below picture is an actual screenshot of such an attack where the computer screen shows a banner to pay money in cryptocurrency (Bitcoin). A deadline will also be mentioned in the banner else the files will be lost forever.
Why common man should be worried?
More and more departments in governments are moving in the ‘Digitization ‘direction. This makes things easy for citizens as well as employees in government services to serve citizens faster, transparently and try to avoid the so-called ‘red-tapism ‘to a certain extend.
Cyber attacks are not only targeted at large corporations. It can also aim at individuals as well as the government sector equally. Here lies the real threat to citizens. What if data related to the land registration department is hacked and tampered with, encrypted, or destroyed? What if a government employee’s employment history details are hacked? What if my electricity, vehicle registration, any personal identity information stored are all gone one day due to a cyber-attack? The outcome will be disastrous beyond what we think and imagine.
Most of the cyber-attacks mentioned at the beginning of this article happened due to poor management of the computer systems. Old and venerable versions of operating systems, obsolete technologies, poor infrastructure and governance, weak and shared passwords, the autonomy of employees to use any software in the personal computers inside the organization like WhatsApp for Desktop, freeware tools, and mails. Lack of awareness of government employees on cyber threats including phishing attacks and many more. Despite Private organizations spending millions of dollars every year to secure their internal systems, there are threats and data breaches happening across the world. A recent cyber-attack happened in the largest fuel pipeline company – Colonial Pipeline in the US on 29th April 2021. The cybercriminals gained entry to their networks via VPN. It was a Ransomware attack, the company has reportedly paid 4.4 million dollars to get back the data stolen by the Russian hacker group – DarkSide. | <urn:uuid:9895f667-e9ed-49a5-8cea-9bdabdea76e7> | CC-MAIN-2022-40 | https://www.dailyhostnews.com/citizens-are-at-risk | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335058.80/warc/CC-MAIN-20220927194248-20220927224248-00157.warc.gz | en | 0.943898 | 592 | 2.75 | 3 |
Don’t be BOT and Sold –
In malware-speak, a”botnet” is a collection of computers that are all infected with malware used to perform malicious tasks or functions. A computer becomes a bot when it downloads a file (e.g., an email attachment) that has bot software embedded in it. A botnet is considered a botnet if it is taking action on the client itself via IRC channels without the hackers having to log in to the client’s computer. A botnet consists of many threats contained in one. The typical botnet consists of a bot server (usually an IRC server) and one or more botclients.
Hello. My name is Inigo Montoya. You killed my father. Prepare to die.
– – Inigo Montoya
SONY BOT & SOLD?
Recently, the Sony and PlayStation brands have taken a huge hit following last month’s attack on their PlayStation Network. Sony shut down the PlayStation Network on April 20 after discovering the breach and announced on April 26 that customer personal data had been compromised. The networks remain down; Sony spokesman Patrick Seybold says that the company is working to relaunch them “as soon as possible.”
Vizzini: Finish him. Finish him, your way.
Fezzik: Oh good, my way. Thank you Vizzini… what’s my way?
Vizzini: Pick up one of those rocks, get behind a boulder, in a few minutes the man in black will come running around the bend, the minute his head is in view, hit it with the rock.
Fezzik: My way’s not very sportsman-like.
Consequently, Sony’s shares have fallen more than 6 percent since the beginning of the two-week crisis. One of the big intangibles is the damage to Sony’s brand image. That could be immeasurable, but to get a flavor of what we are talking about. Recently, 3 out of 10 respondents to a USA TODAY Game Hunters poll about the Sony network breaches say they don’t trust Sony to protect their personal data. Still, 54% of the more than 2,100 respondents said they will continue to use their PlayStation 3 or PlayStation Portable online. Naturally, since there are many unknowns, the estimates of possible losses are all over the place, from a mere $1.6 million to more than $1.25 billion. Incidentally, this is going beyond the breach, whispers of SONYGATE and why it took so long to report the breach, and why there still not fessing up to the lost credit card information of millions of customers.
But that’s not what he said—he distinctly said “To blave” and as we all know, to blave means to bluff, heh? So you were probably playing cards, and he cheated – Miracle Max
What Can I Do?
If you are diagnosing a single machine, there are several steps you can take to discover a possible bot infection. On the other hand, if you are investigating an entire network, you can uncover a slew of infected drones or a botnet command and control (C&C) itself.
Ha ha! You fool! You fell victim to one of the classic blunders – The most famous of which is “never get involved in a land war in Asia” – but only slightly less well-known is this: “Never go against a Sicilian when death is on the line”! Ha ha ha ha ha ha ha! Ha ha ha ha ha ha ha! Ha ha ha…
Just a single machine
1. AntiVirus – I can’t quit you… Don’t even think the conventional anti-virus is sufficient, for many BOT infections will simply not be detected.
2. Rootkit detection packages are a plus.
3. Watch for modification of the windows hosts file
4. Random unexplained popups are likely an adware infection, however it this could be clickfraud or a little league version of a BOT.
5. Machine slowness. Well this admittedly is a useless symptom, for who doesn’t experience this. However in many situations it is massive spyware infections. Whether it is botnet related or not is another story. Scan your machine for spyware.
6. Check the machine’s default DNS resolution servers. Are they what you would expect to see (a company’s or ISP’s DNS servers, or that of your internal LAN’s router?) If not, malware may be redirecting DNS requests to a shady source. For extra precaution, you may want to investigate the DNS traffic on the network itself with a trusted clean host.
As you know, the concept of the suction pump is centuries old. Well, really that’s all this is except that instead of sucking water, I’m sucking life. I’ve just sucked one year of your life away. I might one day go as high as five, but I really don’t know what that would do to you, so let’s just start with what we have. What did this do to you? Tell me. And remember, this is for posterity, so be honest. How do you feel?
– Count Rugen
Monitoring a Network
1. Since IRC is usually rare in a corporate network, seeing any IRC traffic, across typical IRC ports, may be worth looking into.
a. IRC traffic usually manifests itself in clear text, so sensors can be built to sniff particular IRC commands or other protocol keywords on a network gateway
b. Look for the most commonly used default irc port: 6667. The full port range specified by the RFC: 6660-6669,7000. Also, since many IRC services utilize ident, port 113 is a (less common) heads up parameter. However, well known or default ports are less likely to be used by the big boys, take a look at outbound connection attempts on any suspicious ports.
2. If you have access to a list of known botnet command and control (C&C) servers, you can simply look for outbound connection attempts to these services and/or ranges. This is key, although there are signature designed for applications like snort IDS, this is predominately reactive, i.e., tell me about the ones that are so old, that companies have defined a well-known signature for them, the new one, I guess we’ll let by? Try to find a tool that measures outbound traffic against bad destinations as well, this way, you don’t care if we thoroughly understand the malware enough to have it well known enough to have the commercial space evaluate, distill, and stamp out a unique signature.
3. If a large quantity of machines in your direct control are making the same DNS requests, or accessing the same server at once, you can rest assured you likely have a problem on your hands.
4. Similarly, check your DNS caches. Many BOT Command and Control (C & C) mechanisms will make use of a DNS domain that the BOT herder can easily change if he needs to relocate his C&C infrastructure.
5. Malware detection on your network:
a Installing a malware-base honeypot in your internal network will allow you to detect malware propagations from infected machines you may have control over. If your network is penetrated, so too eventually shall an appropriately placed honeypot.
b. Keep an eye on the ports of any typically vulnerable or exploited service. If you see a lot of traffic on 135,139,445 (windows file sharing), you may have a malware propagation scheme attempting to spread its payloads.
c. Portscan traffic is an obvious symptom of any infection. Again, use a proper IDS signature to find these, and then investigate the machine.
6. Keep an eye out for a massive amount of SMTP outbound traffic. Such patterns, especially coming from machines that are not supposed to be SMTP servers, will likely point to a malware spam bot that has implanted itself in your organization. e.g.SpamThru
7. Does your organization make use of an HTTP proxy? If so, malware processes may reveal themselves by requesting http data external to the proxy, and you may catch binary download attempts in your firewall logs if you monitor outbound port 80.
Westley: Give us the gate key.
Yellin: I have no gate key.
Inigo Montoya: Fezzik, tear his arms off.
ellin: Oh, you mean *this* gate key.
In summary, there are many tools out there that address this type of detection; however, don’t discount the tools that simply look for outbound connection attempts to these services and/or ranges. Not only does this do the trick, it does it fast and addresses the new BOTs out there that don’t have a signature yet, i.e., can be detected day 0 of origination, unless you’re willing to wait till a chosen manufacturer discovers, analyzes, authors, tests, and distributes a unique signature for the particular malware. Frankly, by then… who cares – your data is long gone…
About Affant Communication
Affant Communication is a leading provider of Network/Security Solutions and one of the nation’s premier infrastructure solution providers. Offerings include, but are not limited to Telco/Network & Security Solutions, Software Programming, 24 x 7 Network/Security Monitoring, and Wireless Broadband and Mobile Solutions.
About Rick Ricker
An IT professional with over 20 years experience in Information Security, wireless broadband, network and Infrastructure design, development, and support.
for more information, contact Rick at (714) 338-7137
Founding and leading technology-oriented service organizations since 1988. Specializes in Public speaking relating to Business Management, Entrepreneurship, Communication Network Management, Network Security, Managing your Team, and IP Telephony /VoIP / IP Communication. | <urn:uuid:c00c4bb5-3e28-48cb-b52b-4586badf9e2d> | CC-MAIN-2022-40 | https://affant.com/blogbid59935botnets-hello-my-name-is-inigo-montoya-you-killed-my-father-prepare-to-die/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335469.40/warc/CC-MAIN-20220930113830-20220930143830-00157.warc.gz | en | 0.925834 | 2,135 | 2.53125 | 3 |
Data science impact on business: How it supports business growth
The analysis of data and the application of statistical techniques to solve problems has been around for decades. However, it wasn’t until recently that data science impact on business became palpable. The rise of Big data and other technological advancements have resulted in this explosion of interest. Data science for business also became a powerful anti-pandemic tool. Thus, it’s now the cornerstone of building the knowledge required to navigate the new reality.
The numbers prove the omnipresence of data science for business. The global market size stood at $3.93 billion in 2019. During 2020 – 2027, it is set to grow further at a CAGR of 26.9%. But beyond numbers, what are the actual applications of Big data used in business? We’re about to find out.
What is the difference between data science and business analytics?
Data science for business and business analytics get equal mentions when it comes to insight generation. So what is the difference between data science and business analytics?
Data science is the application of statistical analysis, machine learning, data visualization, and programming to help you make better decisions. It’s a multidisciplinary field with backgrounds in mathematics, computer science, business intelligence, and even psychology. It is proving to be a powerful tool that can be used to generate insights into commercial situations that would otherwise remain hidden from view.
As for business analytics, it also relies on a concoction of technologies. In this case, it is computer software, statistical analysis, and business processes that help extract insight from input gathered from internal and external sources. Business analytics can be used in a variety of fields. Information technology, finance, human resources, and marketing are just some examples where business analytics play an important role.
The main difference between the two is the word ‘business’. Business analytics is restricted to commercial use and problems (profit, number of employees, etc.). Conversely, science has a much broader application area and a set of problems, thus being a superset of business analytics. Business analytics also relies on analytics tools to discern insights from data that a company can leverage for its strategy.
Let’s have a closer look at the crucial differences between the two.
Therefore, data science is a more broad discipline. It is not limited to business use only and lays the foundation for business analysis. Business analytics is a narrow field that uses the core methodologies of science to produce mission-critical knowledge for businesses. Both business analytics and data science play a pivotal role for organizations.
Therefore, the question remains: why are data science partners pivotal to business decision-making? It’d be more logical to sing praises to business analytics, wouldn’t it?
What are the main benefits of data science?
The secret sauce of data science impact on business is its versatility. Data science for business professionals is a skill set that can be used to solve any problem, at any scale. From analyzing social media posts to making A/B testing calls, it is changing the face of business as we know it. Here are some other benefits of data science that make a difference in the business landscape.
Ensures business predictability
Being prepared and secured for the future is the key to business success. Predictive analytics solutions allow companies to anticipate trends in customer behavior. They usually rely on customer analytics and data science to process historical data. Customer trends often stem from changes in customer buying habits and consumption patterns. Using predictive analytics software, organizations can take advantage of their large amounts of data to make more informed decisions and improve profitability.
Amplifies real-time intelligence
Real-time business intelligence refers to the ability of a company to receive, process, and analyze information in real time. Businesses can now make faster decisions and have an up-to-the-minute understanding of their customers. The ability to capture time-sensitive benefits (e.g. seasonal peaks) also comes from real-time data processing. Logistics providers, manufacturers, and CRMs are just a sliver of those who benefit greatly from real-time analysis.
Makes customer experience granular
This discipline also helps companies to step up the customer experience. By knowing exactly the most beneficial product associations for your customers. you can fine-tune your product recommendations or make more targeted efforts. Thus, data scientists can crunch customer data to segment customers and flesh out accurate user personas to guide product initiatives.
Helps test new business ideas
Data science along with machine learning consulting can assist businesses in tackling complex, data-rich problems. They add value by identifying new market trends, blazing new business trails, and targeting hidden weak points. For example, you can test the consumer’s flexibility towards price changes or perform benchmarking. Thus, a Google-commissioned study by IDG pinpointed the role of data analytics and intelligent solutions when it comes to helping businesses separate from their competition.
Analytical techniques are also being applied to derive insights from large datasets to improve the effectiveness of security operations. Thus, companies can now identify unusual activity that might point towards potential threats and fight off malicious agents. It also helps you build impenetrable protocols by introducing data-driven algorithms.
As you see, the benefits of data science are manifold and positively impact a wide range of critical business operations. But there’s another noteworthy advantage that should be mentioned in 2022.
Why is data science important for business: COVID edition
Along with other promising boons, processing capabilities can become your trump card in the pandemic realities and economic fallout. The very view of COVID-19 is only possible due to analyzing huge datasets such as hundreds of genomes. Not to mention the difference a data-driven mindset makes for businesses to withstand the turbulence.
According to McKinsey, companies have been using analytics to back up four areas. These include employee support and protection, decision-making, supply chain management, and customer engagement.
Source: McKinsey & Company
Ernst & Young, for example, also found a link between supply chain disruption and growing tech investments. Their survey demonstrates that US enterprises increase investment in supply chain technologies (AI, robotics, and data science) to stay afloat.
For example, demand for toilet paper and paper towels alone grew by 750% during the week of March 8, 2019, in the US. As a result, most companies were unable to satisfy the sudden demand. On the contrary, they could have leveraged data processing to improve visibility and have a holistic overview of the demand, inventory, capacity, supply, and finances across the ecosystem.
FAANG companies, for example, were fast enough to bounce back from the pandemic and even experienced a new influx of users. This wouldn’t be possible without real-time insight into the market.
Let’s dive into other success stories and data science business ideas commonly used for Big data business.
Top 5 data science business ideas
The role of a data scientist is one of the most sought-after jobs in the US. According to LinkedIn’s 2021 Emerging Job Report, the demand for this role is increasing steadily — demonstrating about a 35% average annual growth. It means that the business ecosystem has fully recognized the need for data science applied to business to bolster its growth.
Businesses looking to build a post-pandemic roadmap can add value by using data science business ideas. We’ll go over the most popular ones below.
Fraud and risk detection
All business processes are subject to change, especially today. And there’s not much as high-risk and vulnerable as introducing modifications into time-tested flows. Thus, according to The Financial Cost of Fraud Report, the UK is losing £137bn to fraud each year.
Data science can smoothen the transformation and predict possible trade-offs and weak points. The hallmark of analytics tools is their ability to process massive amounts of data in real-time. That is why they can quickly identify anomalies that differ from the usual operations stored in the system. To do that, data science consultants set up a baseline of non-fraudulent activity to compare against the suspicious dataset.
Thanks to analytics, systems at the National Australia Bank warned a woman against fraudsters when she was trying to raise her account transaction limit. The software detected deviations from the normal activities thus hinting that something wasn’t right.
Effective risk management is another byproduct of data processing. Thus, companies can mine the past patterns and get a deeper understanding of future metrics, threats, and success rates. Also, predictions allow businesses to take a proactive stance and think of remedial measures beforehand.
Another example of data science for business professionals is related to manufacturing. The key to the manufacturing industry’s competitiveness is its quality, cost, and delivery. To deliver these three aspects in a high-quality manner, manufacturers need a better understanding of their products and processes. That is why a growing number of manufacturers rely on analytics to optimize manufacturing processes.
For example, industrial automation company Oden Technologies came up with an ML-based tool that processes manufacturing input. It then pinpoints times of highest efficiency and gives recommendations on replicating golden optimum settings so that the machine operates at peak performance.
Besides effective equipment maintenance, manufacturers can leverage intelligence to:
- perform warranty analysis
- optimize prices
- design and develop new products
- perform inventory management
- predict demand
- anticipate supply chain risks and others.
Overall, effective processing and analysis introduce more visibility into manufacturing workflows. Data science impact on business encompasses everything from concept to transportation.
Assisted customer pathways
Retailers are also resorting to mighty data to transform insights into profit margins. Data science applied to business allows brands to make a dent in the market, enhance the customer experience, as well as boost sales and revenue.
Today, there are quite a few data points that link your customer to specific products, including:
- Search engine queries
- Celebrity and influencer activity
- Consumer attitudes and intent
- Current purchase data
By gathering and analyzing these points, companies can tailor their marketing efforts to specific customers. Moreover, they can automate relevant offerings and embed them into the recommendation engine. Companies such as Amazon, Netflix, Linkedin, and Pandora employ recommender systems to help consumers discover new and related items (products, movies, jobs, and music), resulting in a pleasant user experience and additional revenue.
Sentiment and behavioral analysis are other data-laden implementations. They can uncover hidden insights otherwise inaccessible for brands.
The recent surge in interest in autonomous vehicle technology has been fueled by the tremendous amount of data generated from sensors. The sheer volume and complexity of this data make it a key challenge. The scientists have to develop algorithms that can make reliable decisions about the current state of an autonomous vehicle and its environment. That is why input processing is used to power each step of driverless cars.
Source: The Economist
It is a combination of AI, ML, and computer vision that pinpoint the insights of self-driving vehicles. Data science, in return, lays the ground for each of the technologies and processes each data point in the system. Thus, engineers build algorithms that allow autonomous cars to identify certain objects and gather new data from their sensors.
Along the line, Tesla cars prioritize input collection and analysis. They do this by generating data points during each human-car interaction. These points are then analyzed and used to enhance or create new algorithms. At the very onset, the company also relied on intelligent algorithms to set up its product for success. The company’s engineers gathered autopilot data and sent it to their servers for analysis. This enabled them to detect issues with their vehicles, perfecting the experience.
The automated recruitment process is another example of data science for business professionals. Today, recruiters need to process hordes of resumes, and they are expected to make decisions in a much shorter time. As a result, 71% of recruiters face an acute need for automation and intelligent tools. Automated resume screening is what can now help out the hectic routine of a recruiter.
Image and optical character recognition backed by other analytical technologies can turn visual stimuli from a resume into a digital version. The input then goes through analytical algorithms to find the best hire for the position. Candidate pre-screening tools can also rank and grade candidates. This helps pre-qualify those who click the most with the job requirements.
LinkedIn Talent Insights is a prominent example of insight-driven hiring. This talent intelligence platform gathers over 12 billion data points. The latter provides a real-time view of relevant talent supply and demand. Employer branding metrics, benchmarking, and others are also critical yardsticks.
To sum up
In the Big data era, data science and analytics are critical to the success of organizations of all kinds — from large corporations to small businesses. These disciplines enable effective marketing strategy and real-time decision-making. They also support a whole wealth of other critical operations. Due to the pandemic-caused strain, businesses are also in special need to find a new, data-driven way to ensure resilience and continuity. All these lead to a growing interest in analytical assets and data scientist talent to set them up.
Enhance your business with Top-Notch Technologies
Need a reliable Data Science Partner? Contact us and we’ll get back to you soon to discuss business challenges you face. | <urn:uuid:e87876c7-de67-430e-9118-81145fdec2b5> | CC-MAIN-2022-40 | https://indatalabs.com/blog/data-science-impact-on-business | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335469.40/warc/CC-MAIN-20220930113830-20220930143830-00157.warc.gz | en | 0.929337 | 2,788 | 2.609375 | 3 |
Blockchain is a technology that enables movement of digital coins or cryptocurrency or digital assets from one individual to another and Cryptocurrencies are those assets which are transacted using blockchain.
Initially, Blockchain Technology solved the problems related to money transfer. Usually, if an individual had to transfer some amount across time zones (Suppose from London to Tokyo), the transfer was done using a trusted third party which used to identify the receiving party (in Tokyo), his identity and account details. Once the verification was successfully conducted, the transfer was completed charging some specific fees from the amount transacted. This process consumed time and significant fees as well.
Now what blockchain does:
- It removes the requirement of the “trusted third party” that means the process complexity is reduced.
- The transaction fee charged is very low as compared to the typical transactions.
- The transaction time is reduced to parts of a second that means the transfer is immediate.
Blockchain utilizes the concept of distributed open ledger in which the transactions can be seen by the individuals present on the network. The transactions on the network are added to the the ledgers only when they are validated. The transactions are validated after solving mathematical puzzles and on successful validation, financial rewards are given to those who does validation. The individuals who do this validations are called Miners. The miners compete among themselves to pick transactions from the network, validate them and add them to their ledgers based on their computational powers, post which the rest of the miners add the validated transactions to their own ledgers too.
Blockchain has many applications like Digital Identity, Smart Contracts, Digital Voting, Distributed Cloud Storage and Decentralized Notary.
“A cryptocurrency is a digital asset designed to work as a medium of exchange that uses cryptography to secure its transactions, to control the creation of additional units, and to verify the transfer of assets”, says Wikipedia.
Satoshi Nakamoto, the Godfather or we can say the unknown inventor of Bitcoin, presented the first ever digital currency in late 2008. He stated that he developed “a peer to peer electronic cash system” which is not centralised or controlled by any ‘so called’ trusted third party.
A cryptocurrency can be transferred from one individual to another through blockchain without entertaining any third party. The transaction is confirmed by the miners after which that particular transaction is registered in the distributed open ledger system. These transactions can be viewed and verified by any individual present over the network.
Bitcoin is created as a reward to the miners and it can be exchanged for other cryptocurrency, product or services. Following this system, many cryptocurrencies have taken up the shape with bitcoin like reward process and similar strategy. Although, there have been various innovations and modifications in the implementation in creation of new virtual currencies.
Till date only money oriented application of blockchain, cryptocurrencies, have been overhyped but there are lot more to be discovered and capitalized. There are thousands of cryptocurrencies floating over virtual network, regulated by countries but legally or illegally being transacted all over the globe extensively.
Recently bitcoin touched the highest mark of ($19,783.06) of all time which created huge hype in the global market. This helped the Altcoins to rise up the charts too.
Bitcoin being the largest followed by Ethereum, BitcoinCash, Litecoin, Neo and many more such coins in terms of which regular transactions can be noted every second.
The real potential of blockchain is yet to be exploited to its max. | <urn:uuid:3c40c3de-0e3e-4a5f-b583-5912d9aa74e3> | CC-MAIN-2022-40 | https://www.1kosmos.com/blockchain/blockchain-vs-cryptocurrencies/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337504.21/warc/CC-MAIN-20221004121345-20221004151345-00157.warc.gz | en | 0.959315 | 712 | 3.40625 | 3 |
In today’s digital-first world, banks and financial service companies need to allow their customers to easily manage money online in order to compete. Unfortunately, most banking platforms were not designed securely and hackers have been taking advantage of these built-in weaknesses ever since banks first went online.
Although banking attacks have become more complex in the past few years, the vast majority still rely on tricking users. For example, one common phishing attack used against banks involves directing targets to a malicious clone of the banking platform’s actual website. Once users try to log in to this genuine-looking fake website, the platform can confuse them by displaying a “Service Not Available” messages and store the credentials the user just tried to enter.
It’s all about manipulating users into making mistakes. But phishing attacks are just one tactic to be aware of in the age of e-banking. Here are five more ways hackers attack banks through their users:
SMS swapping has become quite common in the banking industry. First, the attacker steals a victim’s private phone number, along with the phone’s Security ID. Then the attacker calls the SIM card call center claiming they lost their phone, have bought a new SIM card and now need to get their old number back. Using the Security ID and other private information, possibly gathered from snooping on social media accounts, they convince the telecommunication support person to perform the phone swap.
This scam can even evade security protections. Most banking institutions that offer multi-factor authentication (MFA) to protect online banking sessions and applications rely on SMS-based MFA instead of using mobile tokens. Once hackers steal people’s phone numbers, they have access to these SMS messages. That means they can access the victim’s account even if it has SMS-based MFA in place.
Another old but effective tactic is the Man In-The-Middle (MITM) attack, in which attackers target banking platforms that do not adequately protect their infrastructure. This not only allows hackers to steal money, but also negatively affects the bank’s reputation by making their infrastructure seem fragile and vulnerable. The attack allows fraudsters to interfere with the communication between users and the bank’s backend implementation to change transaction values and accounts. It can be prevented by using certificate pinning technology, which allows bank application to trust a specific certificate for a given server.
However, vulnerabilities have been found on this implementation when using TLS connections. A common technique called DNS spoofing can easily redirect the victim’s traffic when they’re connected under the same Wi-Fi network, failing to validate the hostname. The best way banks can prevent this attack from harming a customer’s account is by implementing a token multi-factor signature.
Man-in-the-Browser attack (MITB) is a trojan horse proxy that infects online browsers. It plays the role of a MITM, sniffing and modifying transactions performed on the infected browser, but still displaying back the user’s legitimate input. Most users assume their transactions are protected via SSL if they’re using a website with HTTPS enabled, but SSL only protects data in transit, between the browser and the server.
Better certificate management can prevent infection, but this is very hard to guarantee when a user is banking from their personal computer. Luckily, this attack can also be prevented by implementing multi-factor authentication tokens to protect the bank transaction itself.
Spear phishing attacks
Spear phishing is an email spoofing technique used by fraudsters to target a specific organization or individual with a customized, highly-realistic phishing email. Simply put, it’s a more targeted, complex and research-intensive version of phishing.
This attack is usually used against organizations that the attacker is familiar with. Attackers will use insider knowledge to specifically target the employee responsible for making payments in a way that seems realistic. For example, they might send an email to an accountant that appears to be from the CFO asking them to make a payment that appears normal at first glance. If the employee falls for the attack, it could lead them to a fake website or download link that triggers a MITM or MITB attack.
Mobile malware attacks
Mobile banking trojans are one of the most flexible and dangerous types of malware, designed to steal funds from user’s accounts by stealing their credentials. They look like genuine mobile applications in the Apple or Google store, but when the user downloads and runs the application, it will start monitoring the phone’s banking apps. Not every banking app is designed to protect its own assets appropriately, so passwords and accounts are often easily traceable due to bad implementations and open source libraries exposures.
How banks can defend themselves
One of the best ways for banks to protect their payment systems is to require MFA security layers for each money transaction. Even if customers are tricked into logging onto a fake website or clicking a phishing link, attackers would never be able to transfer money or make payments.
These actions depend on the final user tokens, which the attacker would not have if MFA controls are in place! This can be accomplished by generating password-based signatures using fixed and random transaction attributes like names, values, accounts, timestamps, and so on. Plus, MFA won’t negatively impact the user experience of a banking app or service if it’s implemented correctly.
One thing’s for certain – hackers will continue to view banks and financial institutions as fertile grounds for lucrative fraud campaigns. Banks owe it to their customers to constantly reassess their security measures in order to protect against the above online threats, but users play a role in e-banking security as well. Customers need to educate themselves on the top banking attacks, understand when their money might be at risk, and advocate for better security controls when necessary. | <urn:uuid:61c4c4ec-86f1-46d1-ae58-466d258bf184> | CC-MAIN-2022-40 | https://www.helpnetsecurity.com/2019/08/02/user-centered-bank-fraud/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337668.62/warc/CC-MAIN-20221005203530-20221005233530-00157.warc.gz | en | 0.932275 | 1,233 | 2.703125 | 3 |
Instead of using expensive lawyers to draw up the contracts that govern a business, what if you could write the contracts directly in code and have everyone run them on their own computers? That’s what smart contracts, a relatively new feature built using decentralized blockchain technology, are supposed to do. Unfortunately, one of them just lost tens of millions of dollars. Whoops.
Launched in April, the DAO was the first completely decentralized business governed by smart contracts. Last week, someone exploited a flaw in the smart contract code and snarfed funds reportedly ranging from $53M to $89M in Ether, the cryptocurrency used to run the organization (the ETH/USD exchange rate has been bouncing around more than a Donald Trump campaign cheque, so the amount is hard to pin down).
Now, Ethereum developers have launched a counter-attack on the person who took the funds. It’s also considering a change in its code — known as a fork — that would stop them from spending the digital dough. Here’s the interesting part: the ‘thief’ even left a note, saying they were just playing by the rules of the contract (although the note’s validity has been questioned).
Presumably if the contract’s code allowed the pilferer to split with the funds so easily, one has to wonder if going after them is entirely fair. After all, one person’s bug is another person’s feature.
Bringing the dead to life …
Here’s your horrible thought for the week. Researchers at Ryerson are working with MIT boffins to create AI technology that will keep a facsimile of you alive after you die. “It may sound like one of those science fiction brain in a jar movies,” says the Guardian.
That’s because it is. The facsimile wouldn’t be picture perfect, or indeed visual at all, but by recording and watching everything we do digitally during our lives, it would learn how to respond to questions and interact with those still alive, as though it were us. We suspect it’ll be just good enough to cross into the uncanny valley but not beyond, creeping us all out entirely.
… and consigning the living to history
Talking of people who creep you out entirely, how about that date last night who was clearly more into you than vice versa? They won’t stop messaging you, looking for a second shot, and every time you see a text from them you want to run in the other direction.
Now, Ghostbot will do it for you. You can set it up to take care of dismissing them for you, by sending unenthusiastic messages “lacking in warmth and enthusiasm” until they take the hint. Because heaven forbid that you take responsibility for your own relationships and be assertive.
Dingbat of the week
We like to go large occasionally, so this time, the dingbat of the week is the entire Republican party in the U.S. House of Congress. This has a tech angle, stick with us.
The Democrats wanted a vote on legislation increasing background checks on gun sales and restricting the sale of firearms to people on terrorist watch lists, as a first step toward gun control. The Republicans refused to allow a vote on it, and gavelled Congress into a recess. The Democrats refused to leave, so the GOP turned off the cameras. The Democrats responded by streaming the sit-in live on Twitter’s Periscope service, which C-SPAN (the public access political channel that normally streams camera footage from inside the House) began broadcasting.
It’s worth noting that dingbattery is a bipartisan activity: the Democrats did the same to the GOP eight years ago, but there was no Periscope back then.
In any case, this is a use of social media that we can get behind.
Image courtesy of Ethereum | <urn:uuid:63e2c394-e3c7-4286-8842-c93acfe22b13> | CC-MAIN-2022-40 | https://blog.allstream.com/doh-dao-downed-by-debilitating-defect/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337971.74/warc/CC-MAIN-20221007045521-20221007075521-00157.warc.gz | en | 0.960469 | 815 | 2.5625 | 3 |
Internet Safety for Kids: How to Protect Your Child from the Top 7 Dangers They Face Online
The internet can be a dangerous neighborhood for everyone, but children and teens are especially vulnerable. From cyber predators to social media posts that can come back to haunt them later in life, online hazards can have severe, costly, even tragic, consequences. Children may unwittingly expose their families to internet threats, for example, by accidentally downloading malware that could give cyber criminals access to their parents' bank account or other sensitive information. Protecting children on the internet is a matter of awareness—knowing what dangers lurk and how to safeguard against them. Although cyber security software can help protect against some threats, the most important safety measure is open communication with your children.
The vast majority, 90%, of teens agree that cyber bullying a problem, and 63% believe this is a serious problem. What’s more, a 2018 survey of children’s online behavior found that approximately 60% of children who use social media have witnessed some form of bullying, and that, for various reasons, most children ignored the behavior altogether. And according to enough.org, as of February 2018, nearly half (47%) of all young people had been the victims of cyber bullying. Social media and online games are today's virtual playground, and that is where much cyber bullying takes place, and it’s operating 24/7. Children can be ridiculed in social media exchanges. Or, in online gaming, their player personas can be subjected to incessant attack, turning the game from an imaginative adventure into a humiliating ordeal that escalate into cyber bullying across multiple platforms and in real-life.
The best foundation for protecting against cyber bullying is to be comfortable talking to your children about what is going on in their lives online and in in real-life (IRL) and how to stand up to bullies. Cyber security software and specialized apps for monitoring your child’s online and mobile activity can help, but nothing will replace an open dialog.
- Cyber Predators
These days sexual and other predators often stalk children on the internet, taking advantage of their innocence, lack of adult supervision and abusing their trust. This can culminate in children being lured into dangerous personal encounters IRL. These predators lurk on social media and gaming platforms that appeal to children—the same virtual venues where anonymity facilitates cyber bullying. There, they can exploit not only children's innocence, but also their gift of imagination. "Let's play pretend" is a common and healthy part of online gaming and interaction, but predators can use it as a hook to pull children in.
The FBI offers guidance in safeguarding against predators and other online risks to child safety. However, again, the best protection is regularly talking to your children about what is going on in their day-to-day lives.
- Posting Private Information
Children do not yet understand social boundaries. They may post personally identifiable information (PII) online, for example in their social media profiles, that should not be out in public. This might be anything from images of awkward personal moments to their home addresses or family vacation plans.
Much, but not all, of what your children post is in public view. This means that you can also see it—and there's no harm in reminding them that if Mom and Dad can see it, so can everyone else. Avoid snooping, but speak frankly to your kids about public boundaries and what they mean for your children and your family as a whole.
Phishing is what cyber security professionals call the use of emails that try to trick people into clicking on malicious links or attachments. These can be especially difficult for kids to detect because often, the email will appear to be from someone legitimate, like a friend or family member, saying simply, "Hey—thought you might like this!" This can also be done with using messaging apps or text messages—then it's called "smishing".
Phishing emails and smishing texts can pop up at any time, but the cyber criminals who devise them keep watch on sites that are popular with children, and gather information such as email addresses and friends' names and other information to tailor their attacks, just as they do when spear phishing adults to access corporate networks. Teach your children to avoid clicking on emails or texts from strangers and to be wary of messages that appear to be from their friends but seem "off" or have no genuine personal message attached.
- Falling for Scams
Children are probably not going to fall for Nigerian princes offering them a million dollars, but they might fall for scams that offer things they value, such as free access to online games or special features. Young people are easy marks for scams because they have not yet learned to be wary. As with phishing, cyber criminals can use sites popular with children to identify potential victims, and then promise prizes in return for what they want—like parents' credit card information.
Young or old, the best protection against scams is knowing that if an offer sounds too good to be true, it probably isn't true. Teach your children to be leery of online offers that promise too much.
- Accidentally Downloading Malware
Malware is computer software that is installed without the knowledge of permission of the victim and performs harmful actions on the computer. This includes stealing personal information from your computer or hijacking it for use in a "botnet," which causes sluggish performance. Cyber criminals often trick people into downloading malware. Phishing is one such trick, but there are others—such as convincing victims to download malware masquerading as games—can be especially beguiling to children.
As with scams, educating your children is the best protection, but comprehensive, cross-device cyber security software and related securityprotections can help safeguard your child's computer against any malware that sneaks into it. In addition, many internet security products also include specific parental controls and applications that can help you build a secure framework for your children's online activities.
- Posts that Come Back to Haunt a Child Later in Life
The internet does not have a "Delete" key. It is the opposite of Las Vegas. Things that happen online, stay online. Forever. Anything your child puts online is nearly impossible to remove later. The dangers of social media are especially daunting. It is hard for teenagers in particular to consider how a party picture or Snapchat message could cause problems ten years down the road when they interview for a new job, or how a prospective mate might respond to personal content that they post to their social media profiles or other websites.
Explain to your teens that their style and opinions are guaranteed to change as they grow older. With no "Take-Back" or "Delete" buttons, their 15-year-old self can dramatically alter their adult life in a single click. How they wish to present themselves online and IRL will likely change as they age—but internet posts are forever.
The internet can pose serious dangers to children. It can also open doors of wonder for them that previous generations could not even have dreamed of. Help ensure that your children’s online safety so they experience the joys and opportunities of the online world, and avoid its hazards. Be aware. Be vigilant. But first and foremost be actively involved in your children’s digital and day-to-day lives and communicate openly.
More helpful articles:
- 10 Potentially Dangerous Things You Do Online
- Internet Safety for Kids: Top 7 Internet Threats
- Internet Safety for Kids: Tips for Parents of Twitter Teens
- Internet Safety for Kids: 5 Quick Tips for Snapchat Security
- Internet Safety for Kids: Terrifying Stats & 10 Ways to Stop Cyberbullying Now
- Internet Safety For Kids: How to Protect Your Child from the Top 7 Dangers of Online Gaming
- What is cyber security?
- Infographic: 30 years of cyber security as a pixel art maze
- Computer viruses and malware FAQ
- Today’s biggest web threats
- What is social engineering?
- Public Wi-Fi risks
Internet Safety for Kids: How to Protect Your Child from the Top 7 Dangers They Face OnlineKaspersky
Online Safety for Kids: Protect your child from these 7 internet dangers. Awareness & communication a crucial, but there's more. Learn what you need to do. | <urn:uuid:7a8a8a02-696a-4347-95e6-3eed6772d1ce> | CC-MAIN-2022-40 | https://www.kaspersky.com/resource-center/threats/top-seven-dangers-children-face-online | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337971.74/warc/CC-MAIN-20221007045521-20221007075521-00157.warc.gz | en | 0.944733 | 1,713 | 2.9375 | 3 |
Microsoft getmac and MAC Address (Flashback)
When troubleshooting it is quite common to get the mac address of the host, server or network equipment for a variety of reasons.
For example, many syslog messages or logs may refer to mac addresses depending on what the error is. If you are working from the switch, you more than likely need to know the mac address if you need to figure out which port the target is for your monitor or span command. And of course if you are using a protocol analyzer, you should always capture with a mac address, when possible.
In this video I review how most people figure out their mac address and how to determine the mac address of another device on the same vlan as you. The issue with this methodology is that in some scenarios you may want to figure out the mac address of a Microsoft device that is on another VLAN.
Using Microsoft’s getmac command allows you to get your mac address as well as a remote system’s mac address. As I mention in the video, this command seems to be using the DCE/RPC protocol, so if you block this protocol on your host, servers, or network you might have an issue with command.
Lastly, you need to know the user name/password on the remote system for this to work remotely.
Hope this helps you with your troubleshooting. | <urn:uuid:33e2763a-136c-4eac-8295-2e08f99d8a9c> | CC-MAIN-2022-40 | https://www.networkdatapedia.com/post/2018/11/01/microsoft-getmac-and-mac-address-by-tony-fortunato | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335059.31/warc/CC-MAIN-20220927225413-20220928015413-00357.warc.gz | en | 0.947479 | 284 | 2.59375 | 3 |
Implementing 802.11ac/ax Does Not Guarantee High Throughput
After upgrading a Wi-Fi network to new technologies that boast speeds in excess of 1Gpbs, network engineers are often frustrated to find that the performance of network applications and services still lags. After all, if the data rate promises 10x the speed, shouldn’t we see a similar improvement in end user experience?
Well, not necessarily. By now, many of us have experienced that especially in the Wi-Fi space, 1Gbps does not really mean 1Gbps. There are many variables that go into delivering data over radio waves, and as network engineers we are tasked with delivering the best performance possible.
When testing and troubleshooting a Wi-Fi network, it is critical that we understand the difference between PHY data rate, bandwidth, and true throughput – as these values can vary dramatically depending on the environment. These measurements can also help to determine if a given area is performing as it should, or if there is room for improvement.
Wait – PHY data rate, bandwidth, and throughput – aren’t those basically the same thing? Not exactly…
Let’s define these metrics first, then look at how to measure them.
PHY Data Rate is the maximum rate at which the physical layer can transmit. It represents the rate that data is transferred over the channel, which includes protocol headers, control and management frames. Usually, this is the number advertised by the access point or controller.
Bandwidth is often used synonymously with the data rate. It usually represents the maximum rate at which data can be transmitted but does not include any physical or data link layer overhead.
Throughput is the actual rate achieved by the data in flight. Only the data frames are taken into consideration when measuring throughput, this measurement does not include control frames, management frames, retries, or any other protocol overhead.
To troubleshoot a performance problem, or to test the rate of transfer in each area, it is best to focus on actual throughput measurements. This is commonly done using tools like iPerf, which can create data streams to measure the throughput between two devices. It is not uncommon for the throughput to be less than 50% of the PHY data rate. If it falls to a much lower value, we can start to focus on other metrics such as noise, channel interference, retries and utilization to determine why it is low.
This screenshot shows us the output of the iPerf test from an AirCheck G2 from NetAlly. This throughput test makes it easy to se the difference between the true throughput and the PHY Data Rate.
In conclusion, to experience the high data speeds boasted by newer Wi-Fi technologies, the environment needs to be tested for PHY data rate and actual throughput. Where throughput is low, look for causes of high noise floors, high utilization, channel overlap, and interference that can impact application performance, regardless of what is advertised by the PHY data rate. | <urn:uuid:39e84e20-f0ba-4b2f-a8c8-b0a58f4dd784> | CC-MAIN-2022-40 | https://www.networkdatapedia.com/post/implementing-802-11ac-ax-does-not-guarantee-high-throughput | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335059.31/warc/CC-MAIN-20220927225413-20220928015413-00357.warc.gz | en | 0.932029 | 620 | 3.078125 | 3 |
Day 2 of Appian World 2021 blasted off with a high-flying keynote featuring engineer, physician, author and former NASA astronaut Mae Jemison who became the first black woman to travel into space aboard the Space Shuttle Endeavour.
She talked about making mud pies as a kid because it was about exploring the world around her. She talked about space and interstellar travel. “The nearest star, said Jemison, "is 4.2 light years away. That’s 25 trillion miles. Think about that. The probe voyager left the earth in 1977 to study the outer reaches of our solar system, traveling at 35,000 miles per hour. And it’s just now getting to interstellar space. At that rate, it would take 50 years to get to the nearest star.”
“Space helps us see ourselves as a species,” said Jemison. “We start to see ourselves as earthlings. We can see that we’re connected to the planet. We can’t survive without it. That's what I’ve learned from space. The earth doesn’t need us. We need the earth. And we need to figure out how to preserve it.”
As an astronaut, Jemison said that she had a feeling about being connected with the earth. It wasn’t because of looking back, she said, it was about looking out. It made her feel like she was a part of the universe. She said that if she’s trying to hold on to something from her years as an astronaut, it’s that. As for a leadership style, Jameson said that she likes to bring in a wild card, somebody who’s not constrained by the “right answer”, somebody who will look at a problem in a different way. She said that she doesn’t have all the answers but isn’t afraid to bring in a wild card because they may have the solution.
When Jemison was a kid, there were no women, no people of color in space. But she says that she never bought into the notion that she couldn’t do it. She believed she had something to contribute and a skill set that was important. She was strong on science and engineering and she loved exploring. So, she called the Johnson Space Center and asked for an application.
“I never thought of myself as a trailblazer.. I did it because it was something I was compelled to do. But you still have to own it. You have a platform to connect with other people."
"There was a Mae Jemison before NASA and it’s a part of me and it doesn’t go away. But I’m more than one dimensional person. I love art, African dance, and I have a medical degree,” said Jemison.
After Jameson’s keynote, Malcolm Ross, Appian VP, Product Strategy & Deputy CTO and a team of company product Leaders gave us a preview of the latest Appian release, packed with new user, designer, developer, and platform capabilities that enable even faster low-code automation application development.
There was also a Customer Fireside Chat in which Appian CEO Matt Calkins sat down with Adena Friedman, NASDAQ President and CEO, giving viewers the inside scoop on how Nasdaq has navigated the convergence of technology and helped its clients manage risk and grow and expand their businesses in the age of accelerating change.
It’s worth noting that Friedman has led the charge on one of the biggest tech projects on Wall Street—transitioning Nasdaq’s operations to the cloud. In her chat with Calkins, she said that Nasdaq is pivoting towards its technology and data analytics businesses because that's where tech trends were heading.
“In some of our businesses like our Index business,” said Friedman, “we’re actually seeing a confluence of enormous amounts of data. We have to get streaming information from every exchange in the world. We then also have to tie that back to corporate actions, information, reference data. It's an enormous, complex migration."
"You have to put processes and change management around the data. But you also have to be able to activate and manage the data appropriately. And that's where Appian has come in.”
Friedman also talked about the importance of agility to facilitate acquisitions in the digital age. She talked about operational resilience and reacting to change, noting that resilience for Nasdaq is more about processes and systems that facilitate processes. Having a low-code platform, she said, is what helps you be much more nimble.
“One of the things we decided to do when I first became CEO,” said Friedman, “is make a significant investment in our market infrastructure software. It’s nimble and it works really well to meet today's needs. But what are the needs going to be in 10 years? And are we ready? Because you know to move a market onto a new system, to move into a whole new technology around markets is not something that happens overnight.”
“So, we actually have made a significant investment to rewrite all of our trading software,” said Friedman. “All of it. So we can launch markets in the cloud. And we can facilitate that for 130 other clients around the world which gives them a lot more flexibility and agility going forward.”
The Nasdaq CEO wrapped up the chat with a quick retrospective on the digital evolution of Nasdaq over the last 50 years, and how it has pivote from computers to the internet to the cloud. Then, looking ahead, Friedman said that she envisioned future markets operating in the cloud and being managed in the cloud. She also said that she anticipated bringing more machine learning into the investment lifecycle to leverage massive amounts of data and protect markets.
“Machine learning, the cloud and leveraging data in new ways is what I think will drive the industry.”
Next, it was time to tune in to a stellar lineup of breakout sessions as day two of this year’s low-code palooza kicked into high gear. The challenge, as always, was choosing where to start. The program guide included everything from Changing Culture to Keep up with Innovation and Optimizing Customer Lifecycle Management, to Innovating Experiences for Connected Insurance, Unify your Data Silos and Apps Faster with Enhanced Appian Records, and more.
Yes, there was a strong tech presence at Appian World 2021. But the agenda also showcased the inspiring humanitarian story of guest keynoter Chef and Restaurateur José Andrés, who is an innovator in his own right. No doubt about that. In fact, before the COVID-19 crisis, Andrés was awarded the National Humanities Medal in a White House ceremony for his work with World Central Kitchen.
I can’t write a recap of this year’s Appian World without giving you a taste of Andrés’s remarkable interview with Appian CTO Michael Beckley, which covered everything from Adapting to change and fighting food insecurity to molecular cooking and giving props to chicken nuggets.
“We don’t brag about what we do (at World Central Kitchen),” said Andrés. “We want you to know that we’re about taking care of people. “We need to simplify things because big problems have simple solutions,“ said Andrés. During the COVID-crisis, we transformed from restaurant to community kitchen. We have partnered with 3,000 restaurants across the country, and we feed 150,000 people per day.”
“Republicans and Democrats came together to support us,” said Andrés. “We’re breaking down walls and building bigger tables to feed people. We’re fast, we’re quick, and we adapt."
"Adapting is the best way to prepare for the unexpected. At many companies, the walls are full of plans. But being able to adapt defeats even the best plan of the day.”
Yes, there were plenty of memorable moments packed into Day 2. But after a full day of feasting on mind-blowing keynotes, panels, breakouts and fireside chats, Appian World 2021 is finally in the books. | <urn:uuid:30924dba-d7ae-4da7-8107-5526ab8424d9> | CC-MAIN-2022-40 | https://appian.com/blog/2021/appian-world-2021-day-two-recap.html | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335326.48/warc/CC-MAIN-20220929065206-20220929095206-00357.warc.gz | en | 0.969257 | 1,745 | 2.578125 | 3 |
There are many rules when it comes to protecting yourself online. One of the most important is to have strong, unique passwords for every one of your online accounts.
If you don’t know how to come up with strong passwords, we can help. Tap or click here for 5 new rules to create the best passwords.
But even those who follow the most sound privacy protection advice can make mistakes every now and then. There’s one thing many people are doing that put them at risk. If you’re doing this, stop immediately.
Take note: Do not store sensitive data here
Most smartphones come with a handy note-taking app pre-installed. These are perfect for keeping track of things you need to pick up at the grocery store and honey-do lists but you never want to store sensitive information on them. You might be shocked to know how many people are doing just that.
A recent survey of 1,029 American adults by DuckDuckGo revealed nearly half of them have saved at least one piece of sensitive data in a note-taking app.
Here are some of the things those surveyed admitted to storing:
- Credit/debit card information
- Social Security numbers
- Security or PIN codes
You might be wondering why it’s so dangerous to store this type of information in a notes app. Well, consider the fact that these types of apps are not encrypted by default.
That means everything stored on your note app is vulnerable to hackers. If they break into your phone, they can steal all of your saved notes. Even worse, if the note-taking app has a sync function that is also not encrypted by default, hackers could steal the data by spying on your network.
Most people don’t know these apps are not encrypted by default, as explained in the following chart:
As you can see, less than 35% of those surveyed knew note apps do not encrypt notes by default.
You may also like: Facebook knows everything about you. Here’s what you can do about it
How to protect your sensitive data
Since many note-taking apps are not encrypted, your best move is to not save sensitive information on them.
Imagine the damage a cybercriminal could do by getting ahold of your Social Security number and banking information. Not good.
Just use notes apps for things like simple reminders. For example, you need to pick up bread on your way home from work or you’re having lunch with an old friend at your favorite restaurant Thursday. Never store your credit card numbers or passwords on them.
Like our tips? Then you’ll love our security alerts. | <urn:uuid:e73b8ed0-4146-4473-a278-eaee14314d64> | CC-MAIN-2022-40 | https://www.komando.com/security-privacy/privacy-mistake-notes-apps/710357/ | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335326.48/warc/CC-MAIN-20220929065206-20220929095206-00357.warc.gz | en | 0.940917 | 555 | 2.734375 | 3 |
Many years ago, one of the world’s most popular hacker Kevin Mitnick explained in his book “The Art of Deception” the power of social engineering techniques, today we are aware that social engineering can be combined with hacking to power insidious attacks.
Let’s consider for example social media and mobile platforms; they are considered powerful attack vectors for various categories of threat actors because they allow hitting large audience instantaneously.
Most of the attacks exploiting both paradigms are effective because leverage the concept of “trust” on which social networks are built.
Let’s see in detail which are most common social engineering attacks used to targets users.
Phishing attacks are the most common type of attacks leveraging social engineering techniques. Attackers use emails, social media and instant messaging, and SMS to trick victims into providing sensitive information or visiting malicious URL in the attempt to compromise their systems.
Read the full cool article here.
Source: NFOSEC INSTITUTE | <urn:uuid:7ba59bb1-5851-4fd7-b6f1-7910cdec8a38> | CC-MAIN-2022-40 | https://www.mitnicksecurity.com/in-the-news/the-most-common-social-engineering-attacks | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030336978.73/warc/CC-MAIN-20221001230322-20221002020322-00357.warc.gz | en | 0.929295 | 206 | 2.71875 | 3 |
For most enterprise technology endeavors, there is a cost benefit analysis to innovation. Companies routinely must choose between launching quickly and launching correctly. If speed is the primary driver, quality suffers; alternatively, if quality is the primary driver, speed suffers.
The same is true when it comes to chatbot development, specifically the natural language processing component (NLP). Believe it or not, chatbots don’t come right out of the gate with the ability to understand human speech, they need to be trained just like a human would before going out in the real world and conversing. Machine learning (ML) is the most common way developers can NL-enable a bot to talk to people, systems, and things. But, Machine Learning requires a substantial amount of time, work, and most importantly – data – to create a bot that can accurately interpret and respond to predetermined inputs.
When it comes to natural language training, the essential question is “can Machine Learning alone solve for both quality of the chatbot’s NL intelligence and the enterprise’s need for speed to market?” The answer to that question, at least for now, is complicated. Under an ML model development cycles for complex chatbots can quickly elongate, and time to deployment becomes a business issue in many instances. The greater the accuracy (viz., quality) the chatbot demands, the longer it takes to train it. That’s the conventional wisdom for most enterprises hoping to build intelligent chatbots, but it doesn’t have to be.
Analyzing Machine Learning and Chatbots
To fully understand why ML presents a game of give-and-take for chatbot training, it’s important to examine the role it plays in how a bot interprets a user’s input. The common misconception is that ML actually results in a bot understanding language word-for-word. To get at the root of the problem, ML doesn’t look at words themselves when processing what the user says. Instead, it uses what the developer has trained it with (patterns, data, algorithms, and statistical modeling) to find a match for an intended goal. In the simplest of terms, it would be like a human learning a phrase like “Where is the train station” in another language, but not understanding the language itself. Sure it might serve a specific purpose for a specific task, but it offers no wiggle room or ability vary the phrase in any way.
To learn like this – the ML way - requires huge amounts of data and teaching to achieve an acceptable degree of accuracy. With ML, it typically takes around 1,000 examples to develop a degree of accuracy that produces positive user experiences.
When an insufficient amount of data exists during the pre-deployment stage – which is usually the case without users to supply it - bot developers must relegate themselves to developing custom rules to identify the intent of a message. The simplest of rules may involve something like “if a sentence contains the word ‘forecast,’” then the user is asking about the weather. It sounds like a simple enough fix, but when a conversation is longer and more complex, the level of accuracy decreases quickly and the bot is prone to false positives and the user experience suffers. Not good if you’ve spent time and resources on a bot that’s a pain to use!
Using Fundamental Meaning to Aid Your Chatbot’s NLP
Fundamental Meaning is an approach to NLP that’s all about understanding words themselves. Each user utterance is broken down word-for-word, as if the chatbot were in school breaking down a sentence on the chalkboard. During this process, it’s looking for two things – intent (what the user is asking it to do) and entities (the necessary data needed to complete a task).
For example, if a user types this request to a shopping chatbot:
“I am trying to find a pair of black dress shoes for my husband”
The chatbot would then break the utterance down to the essentials (verbs and nouns), to determine the intent would be “find shoes.” Since that chatbot now knows what its supposed to be doing, it can look for entities. In this scenario “black” (color) and “dress” (category) and “husband” (men’s department) give the bot an idea of where to start.
Because a chatbot using FM possesses a basic understanding of language, it can recognize common synonyms of a command and determine its intended action. As developers think of new synonyms for words like “find” (i.e. search, look for, get, display, show) and “shoes” (wingtips, square toes) they can add them to build the chatbot’s vocabulary and increase its intelligence. Then a chatbot could process an utterance like “Display options for black wingtips” identically to our example sentence.
The Kore.ai Approach: Don’t Play Guessing Games With Your Users
The NLP engine for Kore.ai’s Bots Platform combines ML with fundamental meaning (FM), thereby relieving most of the problems with an ML-only bot approach. Using a multipronged model, bot accuracy improves while development cycles are slashed and the ability to spot failure to interpret categories becomes easier.
ML-only chatbots are essentially optimistic. Their primary function is to try and match a user’s utterance to the closest piece of data it already knows, i.e. it’s making an educated guess, and inevitably it’s going to guess wrong and frustrate a user. In contrast, chatbots using FM err on the side of pessimism. If they can’t identify the intent or entities within a sentence, they ask additional questions to gain more information and clarification. Adding ML to FM enables developers results in a more well-rounded NLP engine, allowing developers to fill gaps in communications by resolving conflicts between idiomatic phrases.
Measuring the Benefits
A multi-pronged NLP bot model using both ML and FM presents advantages to both chatbot developers and users.
For developers, the following are some of the most notable business outcomes:
- Faster bot training. Rather than supplying hundreds or thousands of sentences to train the bot, as required with an ML-only approach, developers only need to supply a few synonyms and field data when using FM to create tasks for their bot. (Of course, it goes without saying the more synonyms the better.)
- Simpler training data. With ML, all verb tenses, singular or plural nouns, adjectives, and adverbs are treated as unique pieces of data, and that can add a ton of upfront work for developers when training a bot. FM understands known language patterns and is able to easily account for these variations without the need to explicitly train the bot for a simple change like “find ATM” vs “find ATMs.”
- Maturing intelligence. Unlike ML, which has no concept of sentence structure, FM treats each sentence separately. Thus, chatbots are able to process more complex requests, even prioritize intents within an utterance. Adding ML to FM also allows developers to increase the intelligence of bots and improve the accuracy of input interpretation over time as they get more data.
- Easier identification of missing elements. With ML, missing data elements are not easy to find. With FM, developers simply need to look through a list of synonyms and a small set of sentences.
- Fewer false positives. A combined ML and fundamental meaning approach reduces the number of false positives. Thus, developers can spend less time trawling through logs to find inaccurate interpretations.
For users, fewer false positives translate into a superior user experience, and since chatbots store their data, the bot actually gets to “know” them over time. Things like preferences, billing addresses, account numbers, birthdays, anything a bot can use to help make tasks easier and faster, get stored. The more conversations a user has with a bot, the more it learns and the more useful it gets.
Not One, But Both
A Fundamental Meaning approach to NLP helps organizations get chatbots off the ground faster and easier, while ML enables developers to resolve idiomatic phrase conflicts and to add utterances to the lexicon library. The two combine to enable not only faster NLP development but more thorough NLP processing. For enterprises, a chatbot strategy doesn’t have to be a choice between one or the other. Now it can be both.
Learn how to further define, develop, and execute your chatbot strategy with our CIO Toolkit. | <urn:uuid:67be2e20-abdf-4056-9825-6b2514da5f38> | CC-MAIN-2022-40 | https://blog.kore.ai/chatbot-nlp-adding-insurance-policy-machine-learning | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030337680.35/warc/CC-MAIN-20221005234659-20221006024659-00357.warc.gz | en | 0.915933 | 1,821 | 2.5625 | 3 |
Big Data deployments are everywhere, the use of data to guide business decisions, create products, improve infrastructure and to affect almost every aspect of our lives is prevalent in today’s world.
What may not be as commonly known is some of the ways which Big Data analytics is being used in health care to improve treatment, predict diseases and to help us operate at peak performance.
CBR has compiled a list of some of the best ways that healthcare is using data analytics.
1. Cancer treatment
Genomics England was given £300 million in funding in 2014 to map 100,000 people’s genomes by 2017.
The purpose of this is to develop personalised medicine for the treatment of cancer, which has been dubbed the greatest breakthrough in cancer treatment since chemotherapy.
One of the challenges involved with this is that each genome can generate files of 150GB each, and having an infrastructure in place which can manage the transfer of such large files is difficult to arrange.
Additionally, issues with data privacy and security are of vital importance, to help solve this, the data is likely to be stored in only G-Cloud accredited datacentres.
The project is being undertaken in partnership with biotechnology company Illumina.
2. Heart Disease
IBM’s natural language and machine learning systems have been applied in trials to help identify individuals who were at risk of suffering from heart disease.
The pilot at Carilion Clinic used a pool of 8,500 patients and used both structured and unstructured data from doctors’ notes to achieve 85% accuracy in detecting heart failure.
IBM has been working for a long time to help predict heart disease and with a number of different research centres.
One of the key findings from the trial was the ability to identify social and behavioural factors which could contribute to heart disease.
The use of unstructured data from doctors notes was something that traditional analysis was unable to factor in to decisions.
3. E. coli genome.
Mount Sinai Medical Centre, a teaching hospital in the U.S. is using technology from Ayasdi to analyse the E. coli genome sequence in order to try and understand why some strains are able to develop resistance to antibiotics.
The technology from Ayasdi uses mathematics and topological data analysis to understand the shape of the data and helps to analyse more than 1 million DNA variants.
Other research teams have been mapping the genome of E. coli strains in order to help track future outbreaks in order to help control them.
4. Premature birth care
The Children’s Hospital of Philadelphia has been using a Care Assistant built using the JBoss Drools Rules Engine, to help make clinical decisions with premature newborns.
The rules engine uses 1,500 rules to search through 200 variables and then provide recommendations to the hospitals EHR users.
In an 8 month trial of more than 1,500 premature newborns, clinicians found that they were more likely to be able to predict the correct growth charts and development milestones.
These are key for administering treatments and vaccines at the correct times, as well as for ensuring development is making healthy progress.
After the trial, those who had been using the rules engine would not give it up.
5. Predicting injuries
Injury to your players can be a costly affair for teams and so more and more is being invested to help to closely monitor players, their fitness levels and to detect when they are likely to get injured.
IBM is working in this field with NSW Waratahs to improve the physical condition of players and to help monitor them for any injuries or pre existing conditions such as heart problems.
Using data from a GPS tracker, collisions can be tracked as well as traditional distance tracking, this is combined with medical data, wellness data and player data which over time can help to build up patterns and develop warning zones.
The use of similar technology is being implemented in football and other sports around the world and both professionals and amateurs become more concerned about prolonging careers and maintaining peak level performance. | <urn:uuid:8e6cc0b1-40e4-4d78-9dfa-8b6c6ede990e> | CC-MAIN-2022-40 | https://techmonitor.ai/technology/data/big-data-in-healthcare-5-ways-its-saving-your-life-4557913 | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030338001.99/warc/CC-MAIN-20221007080917-20221007110917-00357.warc.gz | en | 0.959639 | 824 | 2.96875 | 3 |
Researchers pitch combined biometrics to enable identification from blurred, dark images
As demand for remote identification via surveillance increases, a survey of academic work on biometrics including facial recognition and gait recognition finds the gaps in understanding for dealing with images that are blurred, poorly-lit, from a difficult angle or where the subject has been partly cut from the frame or is simply too small. Ways to improve methods and lighten algorithms that will help bring better recognition to the edge are called for.
‘A Survey on Face and Body Based Human Recognition Robust to Image Blurring and Low Illumination’ from the Division of Electronics and Electrical Engineering, Dongguk University in Seoul, published by MDPI, centers on overall biometric ‘human recognition’ from problematic images and attempts at improving image quality to counteract the issues.
While facial recognition has received much of the research attention, as faces are deemed to contain the most important information for identification, the researchers argue that multimodal body and gait recognition can help with what they term overall ‘human recognition.’
Low-resolution images have been sufficiently dealt with, yet survey papers on blurred images are not comprehensive, which the paper attempts to address. It reviews studies on blurred image restoration and low-illumination and classifies them as to whether or not deep learning was used and whether face and body were combined.
The team tackles indoor and outdoor settings which generate distinct problems. Indoor images are more prone to motion blur and difficult angles as the subjects are closer. Outdoors, illumination can be non-uniform and images lower in resolution.
“No study has yet been conducted on body-based human recognition robust to image blurring in indoor environments; in this case, only the body region is used, dismissing the face. In other words, neither body-based recognition nor body-based re-identification have been studied yet,” states the study. “This is because, compared to the face region, the body region requires more global features for recognition. This in turn implies that the recognition performance is not significantly affected by image blurring.”
The survey covers how the degree of blurring is evaluated through image quality assessment, how the color of clothing can affect results for body-based recognition. Gait recognition can be used in more situations due to the low impact of image blurring.
Further studies are needed on the impact of low-illumination on gait-based recognition. Further studies are also required for human recognition in more severe instances of low lighting. Studies so far have shied away from this as “it is difficult to restore colors perfectly when converting severe low-illumination images into normal-illumination images. It is expected that these problems could be solved through the various deep learning methods.”
“As a whole, both face- and body-based recognition shows a higher accuracy and more processing time than the face-based method,” state the authors, who hope to help biometrics researchers as more demands are made for criminal and missing persons detection, as well as settings such as driver identification in vehicles and crowd analytics. | <urn:uuid:178e80de-45b0-4208-a38c-7fce0ebf3cf9> | CC-MAIN-2022-40 | https://www.biometricupdate.com/202205/researchers-pitch-combined-biometrics-to-enable-identification-from-blurred-dark-images | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030334915.59/warc/CC-MAIN-20220926175816-20220926205816-00557.warc.gz | en | 0.95241 | 650 | 2.90625 | 3 |
Looking to maintain its competitive advantage for years to come, Intel yesterday said it has developed a new, ultra-fast, yet very low power prototype transistor.
The transistor uses new materials that could form the basis of Intel’s microprocessors and other logic products beginning in the second half of the next decade.
Intel and QinetiQ researchers have jointly demonstrated an enhancement-mode transistor using indium antimonide (chemical symbol: InSb) to conduct electrical current.
Transistors control the flow of information/electrical current inside a chip. Intel said the prototype transistor is much faster and consumes less power than previously announced transistors. Intel anticipates using this new material to complement silicon, further extending Moore’s Law.
“The results of this research reinforce our confidence in being able to continue to follow Moore’s Law beyond 2015,” said Ken David, director of components research for Intel’s Technology and Manufacturing Group. “As was the case with other Intel technical advancements, we expect these new materials will enhance the future of silicon-based semiconductors.”
Less Power, More Performance
Significant power reduction at the transistor level, accompanied by a substantial performance increase, could play a crucial role in delivering future platforms to computer users by allowing an increased number of features and capabilities, according to Intel.
The company said considerably less energy used and heat generated could addsignificant battery life for mobile devices and increase opportunities for building smaller more powerful products.
“By providing 50 percent more performance while reducing power consumption by roughly 10 times, this new material will give us considerable flexibility because we will have ability to optimize for both performance and power of future platforms,” David said.
New Uses for Today’s Technology
InSb is in a class of materials called III-V compound semiconductors which are in use today for a variety of discrete and small scale integrated devices such as radio-frequency amplifiers, microwave devices and semiconductor lasers.
Researchers from Intel and QinetiQ have previously announced transistors with InSb channels. The company said the prototype transistors being announced this week, with a gate length of 85nm, are the smallest ever, at less than half the size of those disclosed earlier.
Intel said this is the first time that enhancement mode transistors have been demonstrated. Enhancement mode transistors are the predominant type of transistor used in microprocessors and other logic. These transistors are able to operate at a reduced voltage, about 0.5 volts — roughly half of that for transistors in today’s chips — which leads to chips with far less power consumption.
Another Rabbit in Intel’s Hat
Roger Kay, Principal Analyst for Endpoint Technologies Associates, told TechNewsWorld that it appears Intel has pulled yet another rabbit out of itsresearch hat.
“Obviously, in order to keep pulling off its magic Intel has to keep finding new ways to keep feature sizes down. This development is going to allow themto do that,” Kay said. “It’s pretty amazing stuff when they can find a new process or a new material that can help them to keep going in that respect.”
Of course, there are challenges. Fitting more data on a chip also concentrates more power on portions of the chip. So while there is reducedpower consumption, there may be increased power concentration. Leaping over that industry hurdle, Kay said, would require Intel to pull another trickfrom its sleeve.
“I am sure that the development guys are probably raising questions about power concentration even as the researchers come up with this new material,”Kay said. “It’s not trivial to get from the research discovery to the production of silicon.” | <urn:uuid:ceb2b6e6-d0ff-4cfb-9ad1-8d1df8d2b3f3> | CC-MAIN-2022-40 | https://www.ecommercetimes.com/story/intel-boasts-cooler-more-powerful-chip-breakthrough-47736.html | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335059.43/warc/CC-MAIN-20220928020513-20220928050513-00557.warc.gz | en | 0.939954 | 778 | 2.828125 | 3 |
The general public knows little about the true technology fundamentals of cloud computing, suggests a recent survey commissioned by IT vendor Citrix. Almost a third of the roughly 1,000 U.S. adults polled thought cloud computing was related to weather.
However, the ascendance of Linux and open source software 10 years ago demonstrated that everyday people do not have to understand, appreciate or knowingly participate in a technology in order to leverage it in their lives.
To avoid further confusion about the cloud, I should probably define it. “Cloud computing” is basically the delivery of technology resources such as compute, storage and software applications as externally delivered services — specifically, third-party, hosted, pay-as-you-go services.
The cloud is, at its very essence, a service delivery and consumption model. Thus, cloud computing is defined not by the technologies that enable it, but instead by the method of service delivery and consumption.
True Cloud Believers
Similar to open source software — which today is associated with cost-savings, flexibility and other advantages, cloud computing has many additional connotations. For example, cloud computing is inherently “agile” or “automated,” in the view of many developers and industry executives.
Cloud computing is also a main driver and component of the devops trend, which blends application development with IT operations for greater speed and effectiveness.
When I was writing about Linux and open source software — as well as using it — 10 years ago, most of my friends and acquaintances knew little about it. Even some who were into technology had big misconceptions about free and open source software.
Nevertheless, it was likely these folks were using digital video recorders (which meant Linux, in many cases), flying commercial flights that relied on Linux and open source software for both aerospace and air-control technology, and making purchases at Linux-powered point-of-sale (POS) systems.
They were also laying the groundwork for their future cloud computing use, much of which is built on Linux and open source technology.
A few years ago, when I met with technology vendor executives and CEOs — many of whom are atop the cloud computing wave today — they often downplayed, dismissed or otherwise dissed cloud computing as just another buzz term. That seems to have changed as its implementation and success — not just of Amazon EC2 but several other cloud computing technologies — have illustrated the cloud is real.
This is another parallel to open source software. A decade ago it was often prohibited or limited within many, if not most, enterprise IT organizations, but today it is associated with speed, flexibility, performance and mitigation from vendor lock-in.
Just as we saw with the rise of open source software, a lot of cloud critics and haters are now speaking of the virtue, value and greatness that is cloud computing.
Cloud Ignorance, Cloud Bliss
For many people, cloud computing may still represent a lot of mystery or even myth. Fourteen percent of respondents to the Citrix survey admitted they pretended to know what cloud computing was during a job interview, for instance — and an even greater number, 17 percent, did the same thing on a first date.
What people do seem to know is that cloud computing will be a significant factor in their lives, with nearly 60 percent of respondents indicating they believed the “workplace of the future” would exist entirely in the cloud.
Again, as in the case of open source, just because today’s average folks don’t understand or think they’re using the cloud, that doesn’t mean they’re not significantly leveraging it.
Anyone who plays games or posts comments or photos on Facebook — or even just views those of others — is using cloud computing. Send a tweet? That’s the cloud. Check your Gmail? You guessed it, cloud computing helped make it happen.
Citing online shopping, banking, social networking and file sharing, Citrix estimated that 97 percent of Americans are actually using the cloud today.
Today we all rely on open source software and cloud computing to a high degree beyond our own technology use as well — for conducting financial transactions of all sizes, for transportation and travel, in entertainment, manufacturing, retail, government, pharmaceuticals and other life sciences, and more.
Regardless of people’s comprehension of the cloud, their consumption of it seems certain to expand — as it did with free and open source software. | <urn:uuid:173abdf5-353e-441c-bbc4-662a96220677> | CC-MAIN-2022-40 | https://www.ecommercetimes.com/story/like-foss-fog-cloud-confusion-may-not-matter-76121.html | null | s3://commoncrawl/crawl-data/CC-MAIN-2022-40/segments/1664030335059.43/warc/CC-MAIN-20220928020513-20220928050513-00557.warc.gz | en | 0.962661 | 915 | 2.59375 | 3 |
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