The Hitchhiker'S Guide to Efficient, End-To-End, and Tight DP Auditing

This paper systematizes research on auditing Differential Privacy DP techniques, aiming to identify key insights into the current state of the art and open challenges. First, we introduce a comprehensive framework for reviewing work in the field and establish three cross-contextual desiderata tha...

Privacy-Preserving LLM Interaction with Socratic Chain-Of-Thought Reasoning and Homomorphically Encrypted Vector Databases

Large language models LLMs are increasingly used as personal agents, accessing sensitive user data such as calendars, emails, and medical records. Users currently face a trade-off: They can send private records, many of which are stored in remote databases, to powerful but untrusted LLM providers...

Emission Impossible: Privacy-Preserving Carbon Emissions Claims

Information and Communication Technologies ICT have a significant climate impact, and data centres account for a large proportion of the carbon emissions from ICT. To achieve sustainability goals, it is important that all parties involved in ICT supply chains can track and share accurate carbon...

CUBA: Controlled Untargeted Backdoor Attack against Deep Neural Networks

Backdoor attacks have emerged as a critical security threat against deep neural networks in recent years. The majority of existing backdoor attacks focus on targeted backdoor attacks, where trigger is strongly associated to specific malicious behavior. Various backdoor detection methods depend on...

Few-Shot Learning-Based Cyber Incident Detection with Augmented Context Intelligence

In recent years, the adoption of cloud services has been expanding at an unprecedented rate. As more and more organizations migrate or deploy their businesses to the cloud, a multitude of related cybersecurity incidents such as data breaches are on the rise. Many inherent attributes of cloud...

Watermarking Autoregressive Image Generation

Watermarking the outputs of generative models has emerged as a promising approach for tracking their provenance. Despite significant interest in autoregressive image generation models and their potential for misuse, no prior work has attempted to watermark their outputs at the token level. In thi...

Advantech WISE 4060LAN / IoT Gateway Packet Injection

Remote attackers can execute Modbus commands to WISE-4060/LAN module and manipulate the DO channels. This could lead to unauthorized control of connected devices, such as turning systems on or off, causing disruptions or unsafe conditions. In industrial settings, the DO channels might control...

Differentiation-Based Extraction of Proprietary Data from Fine-Tuned LLMs

The increasing demand for domain-specific and human-aligned Large Language Models LLMs has led to the widespread adoption of Supervised Fine-Tuning SFT techniques. SFT datasets often comprise valuable instruction-response pairs, making them highly valuable targets for potential extraction. This...

Spotting Tell-Tale Visual Artifacts in Face Swapping Videos: Strengths and Pitfalls of CNN Detectors

Face swapping manipulations in video streams represents an increasing threat in remote video communications, due to advances in automated and real-time tools. Recent literature proposes to characterize and exploit visual artifacts introduced in video frames by swapping algorithms when dealing wit...

AndroIDS : Android-Based Intrusion Detection System Using Federated Learning

The exponential growth of android-based mobile IoT systems has significantly increased the susceptibility of devices to cyberattacks, particularly in smart homes, UAVs, and other connected mobile environments. This article presents a federated learning-based intrusion detection framework called...

Centre Driven Controlled Evolution of Wireless Virtual Networks Based on Broadcast Tokens

In a wireless sensor network, the virtual connectivity between nodes is a function of the keys shared between various nodes. Pre-embedding these key configurations in the nodes would make the network inflexible. On the other hand, permitting subsets of nodes to engage in a common key synthesis...

Efficient Blockchain-Based Steganography Via Backcalculating Generative Adversarial Network

Blockchain-based steganography enables data hiding via encoding the covert data into a specific blockchain transaction field. However, previous works focus on the specific field-embedding methods while lacking a consideration on required field-generation embedding. In this paper, we propose a...

Applications of Zero-Knowledge Proofs on Bitcoin

This paper explores how zero-knowledge proofs can enhance Bitcoin's functionality and privacy. First, we consider Proof-of-Reserve schemes: by using zk-STARKs, a custodian can prove its Bitcoin holdings are more than a predefined threshold X, without revealing addresses or actual balances. We...

FARFETCH'D: a Side-Channel Analysis Framework for Privacy Applications on Confidential Virtual Machines

Confidential virtual machines CVMs based on trusted execution environments TEEs enable new privacy-preserving solutions. Yet, they leave side-channel leakage outside their threat model, shifting the responsibility of mitigating such attacks to developers. However, mitigations are either not gener...

Trustworthy Artificial Intelligence for Cyber Threat Analysis

Artificial Intelligence brings innovations into the society. However, bias and unethical exist in many algorithms that make the applications less trustworthy. Threats hunting algorithms based on machine learning have shown great advantage over classical methods. Reinforcement learning models are...

Sudoku: Decomposing DRAM Address Mapping into Component Functions

Decomposing DRAM address mappings into component-level functions is critical for understanding memory behavior and enabling precise RowHammer attacks, yet existing reverse-engineering methods fall short. We introduce novel timing-based techniques leveraging DRAM refresh intervals and consecutive...

Tracking GPTs Third Party Service: Automation, Analysis, and Insights

ChatGPT has quickly advanced from simple natural language processing to tackling more sophisticated and specialized tasks. Drawing inspiration from the success of mobile app ecosystems, OpenAI allows developers to create applications that interact with third-party services, known as GPTs. GPTs ca...

Multi-Use LLM Watermarking and the False Detection Problem

Digital watermarking is a promising solution for mitigating some of the risks arising from the misuse of automatically generated text. These approaches either embed non-specific watermarks to allow for the detection of any text generated by a particular sampler, or embed specific keys that allow...

Tech-ASan: Two-Stage Check for Address Sanitizer

Address Sanitizer ASan is a sharp weapon for detecting memory safety violations, including temporal and spatial errors hidden in C/C++ programs during execution. However, ASan incurs significant runtime overhead, which limits its efficiency in testing large software. The overhead mainly comes fro...

Dynamic Risk Assessments for Offensive Cybersecurity Agents

Foundation models are increasingly becoming better autonomous programmers, raising the prospect that they could also automate dangerous offensive cyber-operations. Current frontier model audits probe the cybersecurity risks of such agents, but most fail to account for the degrees of freedom...

A Sea of Cyber Threats: Maritime Cybersecurity from the Perspective of Mariners

Maritime systems, including ships and ports, are critical components of global infrastructure, essential for transporting over 80% of the world's goods and supporting internet connectivity. However, these systems face growing cybersecurity threats, as shown by recent attacks disrupting Maersk, on...

Beyond the Scope: Security Testing of Permission Management in Team Workspace

Nowadays team workspaces are widely adopted for multi-user collaboration and digital resource management. To further broaden real-world applications, mainstream team workspaces platforms, such as Google Workspace and Microsoft OneDrive, allow third-party applications referred to as add-ons to be...

Context Manipulation Attacks : Web Agents Are Susceptible to Corrupted Memory

Autonomous web navigation agents, which translate natural language instructions into sequences of browser actions, are increasingly deployed for complex tasks across e-commerce, information retrieval, and content discovery. Due to the stateless nature of large language models LLMs, these agents...

Efficient Malware Detection with Optimized Learning on High-Dimensional Features

Malware detection using machine learning requires feature extraction from binary files, as models cannot process raw binaries directly. A common approach involves using LIEF for raw feature extraction and the EMBER vectorizer to generate 2381-dimensional feature vectors. However, the high...

Clam AntiVirus Toolkit 1.4.3

Clam AntiVirus is an anti-virus toolkit for Unix. The main purpose of this software is the integration with mail servers attachment scanning. The package provides a flexible and scalable multi-threaded daemon, a command-line scanner, and a tool for automatic updating via Internet. The programs ar...

ETrace:Event-Driven Vulnerability Detection in Smart Contracts Via LLM-Based Trace Analysis

With the advance application of blockchain technology in various fields, ensuring the security and stability of smart contracts has emerged as a critical challenge. Current security analysis methodologies in vulnerability detection can be categorized into static analysis and dynamic analysis...

Rubber Mallet: a Study of High Frequency Localized Bit Flips and Their Impact on Security

The increasing density of modern DRAM has heightened its vulnerability to Rowhammer attacks, which induce bit flips by repeatedly accessing specific memory rows. This paper presents an analysis of bit flip patterns generated by advanced Rowhammer techniques that bypass existing hardware defenses...

Version-Level Third-Party Library Detection in Android Applications Via Class Structural Similarity

Android applications apps integrate reusable and well-tested third-party libraries TPLs to enhance functionality and shorten development cycles. However, recent research reveals that TPLs have become the largest attack surface for Android apps, where the use of insecure TPLs can compromise both...

Unsourced Adversarial CAPTCHA: a Bi-Phase Adversarial CAPTCHA Framework

With the rapid advancements in deep learning, traditional CAPTCHA schemes are increasingly vulnerable to automated attacks powered by deep neural networks DNNs. Existing adversarial attack methods often rely on original image characteristics, resulting in distortions that hinder human...

A Nested Watermark for Large Language Models

The rapid advancement of large language models LLMs has raised concerns regarding their potential misuse, particularly in generating fake news and misinformation. To address these risks, watermarking techniques for autoregressive language models have emerged as a promising means for detecting...

Bias Variation Compensation in Perimeter-Gated SPAD TRNGs

Random number generators that utilize arrays of entropy source elements suffer from bias variation BV. Despite the availability of efficient debiasing algorithms, optimized implementations of hardware friendly options depend on the bit bias in the raw bit streams and cannot accommodate a wide BV...

Graph Neural Networks for Jamming Source Localization

Graph-based learning provides a powerful framework for modeling complex relational structures; however, its application within the domain of wireless security remains significantly underexplored. In this work, we introduce the first application of graph-based learning for jamming source...

On the Performance of Cyber-Biomedical Features for Intrusion Detection in Healthcare 5.0

Healthcare 5.0 integrates Artificial Intelligence AI, the Internet of Things IoT, real-time monitoring, and human-centered design toward personalized medicine and predictive diagnostics. However, the increasing reliance on interconnected medical technologies exposes them to cyber threats...

Falco 0.41.2

Sysdig Falco is a behavioral activity monitoring agent that is open source and comes with native support for containers. Falco lets you define highly granular rules to check for activities involving file and network activity, process execution, IPC, and much more, using a flexible syntax. Falco...

IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems

The rapid advancement of Large Language Models LLMs has led to the emergence of Multi-Agent Systems MAS to perform complex tasks through collaboration. However, the intricate nature of MAS, including their architecture and agent interactions, raises significant concerns regarding intellectual...

Think Twice Before Adaptation: Improving Adaptability of DeepFake Detection Via Online Test-Time Adaptation

Whitepaper called Think Twice Before Adaptation: Improving Adaptability Of DeepFake Detection Via Online Test-Time Adaptation...

Safety Features for a Centralised AGI Project

Recent AI progress has outpaced expectations, with some experts now predicting AI that matches or exceeds human capabilities in all cognitive areas AGI could emerge this decade, potentially posing grave national and global security threats. AI development is currently occurring primarily in the...

PolyGuard: Massive Multi-Domain Safety Policy-Grounded Guardrail Dataset

Whitepaper called PolyGuard: Massive Multi-Domain Safety Policy-Grounded Guardrail Dataset...

Proposal for Improving Google A2A Protocol: Safeguarding Sensitive Data in Multi-Agent Systems

A2A, a protocol for AI agent communication, offers a robust foundation for secure AI agent communication. However, it has several critical issues in handling sensitive data, such as payment details, identification documents, and personal information. This paper reviews the existing protocol,...

KGMark: a Diffusion Watermark for Knowledge Graphs

Knowledge graphs KGs are ubiquitous in numerous real-world applications, and watermarking facilitates protecting intellectual property and preventing potential harm from AI-generated content. Existing watermarking methods mainly focus on static plain text or image data, while they can hardly be...

On Key Exchange Protocol Based on Two-Side Multiplication Action

We present a cryptanalysis of a key exchange protocol based on the digital semiring. For this purpose, we find the maximal solution of a linear system over such semiring, and use the properties of circulant matrix to demonstrate that the protocol is vulnerable. Specifically, we provide an efficie...

Technical Options for Flexible Hardware-Enabled Guarantees

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,...

SHADE-Arena: Evaluating Sabotage and Monitoring in LLM Agents

As Large Language Models LLMs are increasingly deployed as autonomous agents in complex and long horizon settings, it is critical to evaluate their ability to sabotage users by pursuing hidden objectives. We study the ability of frontier LLMs to evade monitoring and achieve harmful hidden goals...

LLM Jailbreak Oracle

As large language models LLMs become increasingly deployed in safety-critical applications, the lack of systematic methods to assess their vulnerability to jailbreak attacks presents a critical security gap. We introduce the jailbreak oracle problem: given a model, prompt, and decoding strategy,...

Specification and Evaluation of Multi-Agent LLM Systems -- Prototype and Cybersecurity Applications

Recent advancements in LLMs indicate potential for novel applications, e.g., through reasoning capabilities in the latest OpenAI and DeepSeek models. For applying these models in specific domains beyond text generation, LLM-based multi-agent approaches can be utilized that solve complex tasks by...

Mitigating Data Poisoning Attacks to Local Differential Privacy

The distributed nature of local differential privacy LDP invites data poisoning attacks and poses unforeseen threats to the underlying LDP-supported applications. In this paper, we propose a comprehensive mitigation framework for popular frequency estimation, which contains a suite of novel...

Theoretically Unmasking Inference Attacks against LDP-Protected Clients in Federated Vision Models

Federated Learning enables collaborative learning among clients via a coordinating server while avoiding direct data sharing, offering a perceived solution to preserve privacy. However, recent studies on Membership Inference Attacks MIAs have challenged this notion, showing high success rates...

Miliaris Amigdala 2.2.6 Cross Site Scripting

Miliaris Amigdala version 2.2.6 suffers from multiple reflective cross site scripting vulnerabilities. Please note this entry aggregates three separate advisories...

Can We Infer Confidential Properties of Training Data from LLMs?

Large language models LLMs are increasingly fine-tuned on domain-specific datasets to support applications in fields such as healthcare, finance, and law. These fine-tuning datasets often have sensitive and confidential dataset-level properties -- such as patient demographics or disease prevalenc...

Locally Differentially Private Frequency Estimation Via Joint Randomized Response

Local Differential Privacy LDP has been widely recognized as a powerful tool for providing a strong theoretical guarantee of data privacy to data contributors against an untrusted data collector. Under a typical LDP scheme, each data contributor independently randomly perturbs their data before...