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With the rapid advancement of large language models (LLMs), safeguarding intellectual property (IP) has become increasingly critical. To address the challenges of high costs and potential contamination in fingerprint integration, we propose LoRA-FP, a lightweight, plug-and-play framework that embeds backdoor fingerpri...
Adversarial examples add imperceptible alterations to inputs with the objective to induce misclassification in machine learning models. They have been demonstrated to pose significant challenges in domains like image classification, with results showing that an adversarially perturbed image to evade detection against ...
Background: According to GitGuardian's monitoring of public GitHub repositories, secrets sprawl continued accelerating in 2022 by 67% compared to 2021, exposing over 10 million secrets (API keys and other credentials). Though many open-source and proprietary secret detection tools are available, these tools output...
Research on sensor networks has become much more active and is currently being applied to many different fields. However since sensor networks are limited to only collecting and reporting information regarding a certain event, and requires human intervention with that given information, it is often difficult to react ...
Neural networks are powering the deployment of embedded devices and Internet of Things. Applications range from personal assistants to critical ones such as self-driving cars.
Widespread deployment of RFID system arises security and privacy concerns of users. There are several proposals are in the literature to avoid these concerns, but most of them provides reasonable privacy at the cost of search complexity on the server side.
Multi-variant execution (MVX) systems amplify the effectiveness of software diversity techniques. The key idea is to run multiple diversified program variants in lockstep while providing them with the same input and monitoring their run-time behavior for divergences.
In the big data era, more and more cloud-based data-driven applications are developed that leverage individual data to provide certain valuable services (the utilities). On the other hand, since the same set of individual data could be utilized to infer the individual's certain sensitive information, it creates ne...
This paper introduces a fraud-deterrent access validation system for public blockchains, leveraging two complementary concepts: "Transaction Proximity", which measures the distance between wallets in the transaction graph, and "Easily Attainable Identities (EAIs)", wallets with direct transaction connec...
Statistics about traffic flow and people's movement gathered from multiple geographical locations in a distributed manner are the driving force powering many applications, such as traffic prediction, demand prediction, and restaurant occupancy reports. However, these statistics are often based on sensitive locatio...
In 2002, Johnson et al. posed an open problem at the Cryptographers' Track of the RSA Conference: how to construct a secure homomorphic signature on a semigroup, rather than on a group. In this paper, we introduce, for the first time, a semigroup-homomorphic signature scheme.
As the Internet struggles to cope with scalability, mobility, and security issues, new network architectures are being proposed to better accommodate the needs of modern systems and applications. In particular, Content-Oriented Networking (CON) has emerged as a promising next-generation Internet architecture: it sets ...
This paper uses a scenario-based role-play experiment based on the usage of QR codes to detect how mobile users respond to social engineering attacks conducted via mobile devices. The results of this experiment outline a guided mobile phone forensics investigation method which could facilitate the work of digital fore...
We propose just-in-time memoryless trust for crowdsourced IoT services. We leverage the characteristics of the IoT service environment to evaluate their trustworthiness.
Android apps collecting data from users must comply with legal frameworks to ensure data protection. This requirement has become even more important since the implementation of the General Data Protection Regulation (GDPR) by the European Union in 2018.
The network security analyzers use intrusion detection systems (IDSes) to distinguish malicious traffic from benign ones. The deep learning-based IDSes are proposed to auto-extract high-level features and eliminate the time-consuming and costly signature extraction process.
In an era of escalating cyber threats, malware poses significant risks to individuals and organizations, potentially leading to data breaches, system failures, and substantial financial losses. This study addresses the urgent need for effective malware detection strategies by leveraging Machine Learning (ML) technique...
Privacy-Preserving Federated Learning (PPFL) has emerged as a secure distributed Machine Learning (ML) paradigm that aggregates locally trained gradients without exposing raw data. To defend against model poisoning threats, several robustness-enhanced PPFL schemes have been proposed by integrating anomaly detection.
Radio Frequency Fingerprinting Identification (RFFI) is a lightweight physical layer identity authentication technique. It identifies the radio-frequency device by analyzing the signal feature differences caused by the inevitable minor hardware impairments.
Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods which focused on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks focused on fast data processing and model...
As the smartphone market leader, Android has been a prominent target for malware attacks. The number of malicious applications (apps) identified for it has increased continually over the past decade, creating an immense challenge for all parties involved.
Commodity OS kernels have broad attack surfaces due to the large code base and the numerous features such as device drivers. For a real-world use case (e.g., an Apache Server), many kernel services are unused and only a small amount of kernel code is used.
Networks exist all around on the planet, and inside the brain of every living organism. On the city streets we see transport networks, inside homes and organizations we see water piping networks.
The IoT has made possible the development of increasingly driven services, like industrial IIoT services, that often deal with massive amounts of data. Meantime, as IIoT networks grow, the threats are even greater, and false data injection attacks (FDI) stand out as being one of the most aggressive.
Infrastructure as Code (IaC) is the process of managing IT infrastructure via programmable configuration files (also called IaC scripts). Like other software artifacts, IaC scripts may contain security smells, which are coding patterns that can result in security weaknesses.
Cyber-attacks have been one of the deadliest attacks in today's world. One of them is DDoS (Distributed Denial of Services).
We develop a new integrated communications and security (ICAS) design paradigm by leveraging the concept of reconfigurable intelligent surfaces (RISs). In particular, we propose RIS-assisted simultaneous transmission and secret key generation by sharing the RIS for these two tasks.
Reports and press releases highlight that security incidents continue to plague organizations. While researchers and practitioners' alike endeavor to identify and implement realistic security solutions to prevent incidents from occurring, the ability to initially identify a security incident is paramount when rese...
Pufferfish privacy is a flexible generalization of differential privacy that allows to model arbitrary secrets and adversary's prior knowledge about the data. Unfortunately, designing general and tractable Pufferfish mechanisms that do not compromise utility is challenging.
The few-shot fine-tuning of Latent Diffusion Models (LDMs) has enabled them to grasp new concepts from a limited number of images. However, given the vast amount of personal images accessible online, this capability raises critical concerns about civil privacy.
Evidence of signatures associated with cryptographic modes of operation is established. Motivated by some analogies between cryptographic and dynamical systems, in particular with chaos theory, we propose an algorithm based on Lyapunov exponents of discrete dynamical systems to estimate the divergence among ciphertext...
Modern large language model (LLM) developers typically conduct a safety alignment to prevent an LLM from generating unethical or harmful content. Recent studies have discovered that the safety alignment of LLMs can be bypassed by jailbreaking prompts.
The differential privacy is a widely accepted conception of privacy preservation and the Laplace mechanism is a famous instance of differential privacy mechanisms to deal with numerical data. In this paper, we find that the differential privacy does not take liner property of queries into account, resulting in unexpec...
In this paper the author present a new technique of using QR Codes (commonly known as 'Quick Respond Codes') in the field of Cryptography. QR Codes are mainly used to convey or store messages because they have higher or large storage capacity than any other normal conventional 'barcodes'.
We measure the association between generative AI (GAI) tool adoption and four metrics spanning security operations, information protection, and endpoint management: 1) number of security alerts per incident,
Cyber-Physical Systems (CPS) are formed through interconnected components capable of computation, communication, sensing and changing the physical world. The development of these systems poses a significant challenge since they have to be designed in a way to ensure cyber-security without impacting their performance.
Steganography is about how to send secret message covertly. And the purpose of steganalysis is to not only detect the existence of the hidden message but also extract it.
Quasi-subfield polynomials were introduced by Huang et al. together with a new algorithm to solve the Elliptic Curve Discrete Logarithm Problem (ECDLP) over finite fields of small characteristic. In this paper we provide both new quasi-subfield polynomial families and a new theorem limiting their existence.
Machine learning is increasingly used to make sense of the physical world yet may suffer from adversarial manipulation. We examine the Viola-Jones 2D face detection algorithm to study whether images can be created that humans do not notice as faces yet the algorithm detects as faces.
Nowadays, many technological advances applied to the Internet of Things (IoT) make the introduction of innovative sensors aimed to deploy efficient wireless sensor networks possible. In order to improve the environment and people's lives, real time analysis of certain environmental variables may favor the reductio...
Parked-assisted vehicular edge computing (PVEC) fully leverages communication and computing resources of parking vehicles, thereby significantly alleviating the pressure on edge servers. However, resource sharing and trading for vehicular task offloading in the PVEC environment usually occur between untrustworthy enti...
Physical Unclonable Functions (PUFs) are promising security primitives for resource-constrained network nodes. The XOR Arbiter PUF (XOR PUF or XPUF) is an intensively studied PUF invented to improve the security of the Arbiter PUF, probably the most lightweight delay-based PUF.
Machine learning (ML) models are known to be vulnerable to a number of attacks that target the integrity of their predictions or the privacy of their training data. To carry out these attacks, a black-box adversary must typically possess the ability to query the model and observe its outputs (e.g., labels).
Decentralized on-chain smart contracts enable trustless collaboration, yet their inherent data transparency and execution overhead hinder widespread adoption. Existing cryptographic approaches incur high computational costs and lack generality.
Information or data is very crucial resource to us. Thus securing the information becomes all the more necessary.
Metaverse is a vast virtual world parallel to the physical world, where the user acts as an avatar to enjoy various services that break through the temporal and spatial limitations of the physical world. Metaverse allows users to create arbitrary digital appearances as their own avatars by which an adversary may disgu...
With the advent of new IEEE 802.11ax (WiFi 6) devices, enabling security is a priority. Since previous versions were found to have security vulnerabilities, to fix the most common security flaws, the WiFi Protected Access 3 (WPA3) got introduced.
Modern computing systems rely on the Unified Extensible Firmware Interface (UEFI), which has replaced the traditional BIOS as the firmware standard for the modern boot process. Despite the advancements, UEFI is increasingly targeted by threat actors seeking to exploit its execution environment and take advantage of it...
In order to preserve the possibility of an Internet that is free at the point of use, attention is turning to new solutions that would allow targeted advertisement delivery based on behavioral information such as user preferences, without compromising user privacy. Recently, explorations in devising such systems eithe...
In this report, we propose a novel black-box jailbreak attacking framework that incorporates various LLM-as-Attacker methods to deliver transferable and powerful jailbreak attacks. Our method is designed based on three key observations from existing jailbreaking studies and practices.
The North Atlantic Treaty Organization (NATO) Exploratory Team meeting, "Model-Driven Paradigms for Integrated Approaches to Cyber Defense," was organized by the NATO Science and Technology Organization's (STO) Information Systems and Technology (IST) panel and conducted its meetings and electronic exchange...
A Negative Pressure Room (NPR) is an essential requirement by the Bio-Safety Levels (BSLs) in biolabs or infectious-control hospitals to prevent deadly pathogens from being leaked from the facility. An NPR maintains a negative pressure inside with respect to the outside reference space so that microbes are contained i...
Manufacturers of modern electronic devices are constantly attempting to implement additional features into ever-increasingly complex and performance demanding systems. This race has been historically driven by improvements in the processor's clock speed, but as power consumption and real estate concerns in the emb...
A good amount of effort has been dedicated to surveying and systematizing Ethereum smart contract security bug classes. There is, however, a gap in literature when it comes to surveying implementation-level security bugs that commonly occur in basic PoW blockchain node implementations, discovered during the first deca...
The widespread application of machine learning algorithms is a matter of increasing concern for the data privacy research community, and many have sought to develop privacy-preserving techniques for it. Among existing approaches, the homomorphic evaluation of ML algorithms stands out by performing operations directly ...
Wireless sensor networks have attracted a lot of interest over the last decade in wireless and mobile computing research community. Applications of these networks are numerous and growing, which range from indoor deployment scenarios in the home and office to outdoor deployment in adversary's territory in a tactic...
Large language models (LLMs) have transformed the way computers understand and process human language, but using them effectively across different organizations remains still difficult. When organizations work together to improve LLMs, they face several main challenges.
Trusted execution environment (TEE) has provided an isolated and secure environment for building cloud-based analytic systems, but it still suffers from access pattern leakages caused by side-channel attacks. To better secure the data, computation inside TEE enclave should be made oblivious, which introduces significa...
The growth of the Bitcoin network during the first decade of its operation to a global scale system is a singular event in the deployment of Information Technology systems. Can this approach serve as a wider paradigm for Information Technology services beyond the use case of digital currencies?
We provide formal definitions and efficient secure techniques for <br>- turning noisy information into keys usable for any cryptographic application, and, in particular, <br>- reliably and securely authenticating biometric data. <br>Our techniques apply not just to biometric information, but to any keying material tha...
Since IoT systems provide services over the Internet, they must continue to operate safely even if malicious users attack them. Since the computational resources of edge devices connected to the IoT are limited, lightweight platforms and network protocols are often used.
Remote Code Execution (RCE) exploits pose a significant threat to AI and ML systems, particularly in GPU-accelerated environments where the computational power of GPUs can be misused for malicious purposes. This paper focuses on RCE attacks leveraging deserialization vulnerabilities and custom layers, such as TensorFl...
Mixed reality (MR) technology development is now gaining momentum due to advances in computer vision, sensor fusion, and realistic display technologies. With most of the research and development focused on delivering the promise of MR, there is only barely a few working on the privacy and security implications of this...
Web searching is becoming an essential activity because it is often the most effective and convenient way of finding information. However, a Web search can be a threat to the privacy of the searcher because the queries may reveal sensitive information about the searcher.
Backdoors on federated learning will be diluted by subsequent benign updates. This is reflected in the significant reduction of attack success rate as iterations increase, ultimately failing.
LLM-based programming assistants offer the promise of programming faster but with the risk of introducing more security vulnerabilities. Prior work has studied how LLMs could be maliciously fine-tuned to suggest vulnerabilities more often.
Physical signature verification on absentee ballots became a major flashpoint in the 2018 midterm elections in the United States, especially in states like Georgia, Florida, and Arizona, where close election margins resulted in heightened attention to the counting of absentee ballots. As vote-by-mail solutions are bec...
Mobile Ad hoc Network (MANET) is a collection of mobile nodes that can communicate with each other using multihop wireless links without requiring any fixed based-station infrastructure and centralized management. Each node in the network acts as both a host and a router.
Although deep neural networks (DNNs) are known to be fragile, no one has studied the effects of zooming-in and zooming-out of images in the physical world on DNNs performance. In this paper, we demonstrate a novel physical adversarial attack technique called Adversarial Zoom Lens (AdvZL), which uses a zoom lens to zoo...
Decentralized crypto-currencies based on the blockchain architecture under-utilize available network bandwidth, making them unable to scale to thousands of transactions per second. We define the Blockclique architecture, that addresses this limitation by sharding transactions in a block graph with a fixed number of th...
Fairly recently, a novel image encryption based on Arnold scrambling and Lucas series has been proposed in the literature. The scheme design is based on permutation-substitution operations, where Arnold map is used to permute pixels for some T rounds, and Lucas sequence is used to mask the image and substitute pixel&#...
Ripple Effect is a logic puzzle where the player has to fill numbers into empty cells in a rectangular grid. The grid is divided into rooms, and each room must contain consecutive integers starting from 1 to its size.
We give an alternative derivation of $(N,N)$-isogenies between fast Kummer surfaces which complements existing works based on the theory oftheta functions. We use this framework to produce explicit formulae for the case of $N = 3$, and show that the resulting algorithms are more efficient than all prior $(3, 3)$-isoge...
With the popularization and application of privacy protection technologies in cloud service and social network, ciphertext has been gradually becoming a common platform for public to exchange data. Under the cover of such a plat-form, we propose steganography in encrypted domain (SIED) in this paper to re-alize a nove...
Data is the lifeblood of the modern world, forming a fundamental part of AI, decision-making, and research advances. With increase in interest in data, governments have taken important steps towards a regulated data world, drastically impacting data sharing and data usability and resulting in massive amounts of data c...
The shuffled (aka anonymous) model has recently generated significant interest as a candidate distributed privacy framework with trust assumptions better than the central model but with achievable errors smaller than the local model. We study pure differentially private (DP) protocols in the shuffled model for summati...
Jailbreak backdoor attacks on LLMs have garnered attention for their effectiveness and stealth. However, existing methods rely on the crafting of poisoned datasets and the time-consuming process of fine-tuning.
Non-malleable codes are randomized codes that protect coded messages against modification by functions in a tampering function class. These codes are motivated by providing tamper resilience in applications where a cryptographic secret is stored in a tamperable storage device and the protection goal is to ensure that ...
In this paper, we study the problem of obtaining $1$-of-$2$ string oblivious transfer (OT) between users Alice and Bob, in the presence of a passive eavesdropper Eve. The resource enabling OT in our setup is a noisy broadcast channel from Alice to Bob and Eve.
Frontier AI models pose increasing risks to public safety and international security, creating a pressing need for AI developers to provide credible guarantees about their development activities without compromising proprietary information. We propose Flexible Hardware-Enabled Guarantees (flexHEG), a system integrated...
With the raise in practice of Internet, in social, personal, commercial and other aspects of life, the cybercrime is as well escalating at an alarming rate. Such usage of Internet in diversified areas also augmented the illegal activities, which in turn, bids many network attacks and threats.
Key agreement is a fundamental cryptographic primitive. It has been proved that key agreement protocols with security against computationally unbounded adversaries cannot exist in a setting where Alice and Bob do not have dependent variables and communication between them is fully public, or fully controlled by the ad...
Recent research has shown that Machine Learning/Deep Learning (ML/DL) models are particularly vulnerable to adversarial perturbations, which are small changes made to the input data in order to fool a machine learning classifier. The Digital Twin, which is typically described as consisting of a physical entity, a virt...
This paper presents a hybrid blockchain-edge architecture for managing Electronic Health Records (EHRs) with attribute-based cryptographic mechanisms. The architecture introduces a novel attribute-based signature aggregation (ABSA) scheme and multi-authority attribute-based encryption (MA-ABE) integrated with Paillier...
Recent changes in standards and regulations, driven by the increasing importance of software systems in meeting societal needs, mandate increased security testing of software systems. Penetration testing has been shown to be a reliable method to asses software system security.
In this work we describe, design and analyze the security of a tamper-evident, append-only data structure for maintaining secure data sequences in a loosely coupled distributed system where individual system components may be mutually distrustful. The resulting data structure, called an Authenticated Append-Only Skip ...
Fuchsia is a new open-source operating system created at Google that is currently under active development. The core architectural principles guiding the design and development of the OS include high system modularity and a specific focus on security and privacy.
Building on previous work using reinforcement learning (RL) focused on identification of exfiltration paths, this work expands the methodology to include protocol and payload considerations. The former approach to exfiltration path discovery, where reward and state are associated specifically with the determination of...
With the release of Amazon Alexa and the first Amazon Echo device, the company revolutionised the smart home. It allowed their users to communicate with, and control, their smart home ecosystem purely using voice commands.
There was a time when the word security was only confined to the physical protection of things that were valuable which must be guarded against all the odds. Today, in a world where people can do things virtually have emerged the necessity to protect the virtual world.
We introduce Unity Interleave, a new consensus algorithm for public blockchain settings. It is an eventual consistency protocol merging the Proof-of-Work (PoW) and Proof-of-Stake (PoS) into a coherent stochastic process.
This document introduces XinFin DPoS 2.0, the proposed next generation decentralized consensus engine for the XinFin XDC Network. Built upon the most advanced BFT consensus protocol, this upgrade will empower the XDC Network with military-grade security and performance while consuming extremely low resources, and will...
Cryptocurrencies redefined how money can be stored and transferred among users. However, independent of the amount being sent, public blockchain-based cryptocurrencies suffer from high transaction waiting times and fees.
Blockchain has received tremendous attention in non-monetary applications including the Internet of Things (IoT) due to its salient features including decentralization, security, auditability, and anonymity. Most conventional blockchains rely on computationally expensive consensus algorithms, have limited throughput, ...
In recent years, machine learning-based anomaly detection (AD) has become an important measure against security threats from Internet of Things (IoT) networks. Machine learning (ML) models for network traffic AD require datasets to be trained, evaluated and compared.
We show that on an $n=24m+8k$-dimensional even unimodular lattice, if the shortest vector length is $\geq 2m$, then as the number of vectors of length $2m$ decreases, the secrecy gain increases. We will also prove a similar result on general unimodular lattices.
The increasing popularity of certain programming languages has spurred the creation of ecosystem-specific package repositories and package managers. Such repositories (e.g., npm, PyPI) serve as public databases that users can query to retrieve packages for various functionalities, whereas package managers automaticall...
Voice over IP (VoIP) is unquestionably the most popular real-time service in IP networks today. Recent studies have shown that it is also a suitable carrier for information hiding.
This paper presents CyberSecEval, a comprehensive benchmark developed to help bolster the cybersecurity of Large Language Models (LLMs) employed as coding assistants. As what we believe to be the most extensive unified cybersecurity safety benchmark to date, CyberSecEval provides a thorough evaluation of LLMs in two c...
Nowadays, Android is the most dominant operating system in the mobile ecosystem, with billions of people using its apps daily. As expected, this trend did not go unnoticed by miscreants, and Android became the favorite platform for discovering new victims through malicious apps.