In Search of Lost Data: a Study of Flash Sanitization Practices

To avoid the disclosure of personal or corporate data, sanitization of storage devices is an important issue when such devices are to be reused. While poor sanitization practices have been reported for second-hand hard disk drives, it has been reported that data has been found on original storage...

iOS 18.3 Beta / 18.2.1 Audio File Buffer Overflow

A critical vulnerability exists in AudioConverterService on iOS 18.3 Beta and also affects iOS 18.2.1 that allows a remote attacker to exploit a buffer overflow vulnerability via a malicious audio file sent through iMessage or SMS...

Agency Problems and Adversarial Bilevel Optimization under Uncertainty and Cyber Threats

We study an agency problem between a holding company and its subsidiary, exposed to cyber threats that affect the overall value of the subsidiary. The holding company seeks to design an optimal incentive scheme to mitigate these losses. In response, the subsidiary selects an optimal cybersecurity...

Topology-Aware Detection and Localization of Distributed Denial-Of-Service Attacks in Network-On-Chips

Network-on-Chip NoC enables on-chip communication between diverse cores in modern System-on-Chip SoC designs. With its shared communication fabric, NoC has become a focal point for various security threats, especially in heterogeneous and high-performance computing platforms. Among these attacks,...

CSAGC-IDS: a Dual-Module Deep Learning Network Intrusion Detection Model for Complex and Imbalanced Data

As computer networks proliferate, the gravity of network intrusions has escalated, emphasizing the criticality of network intrusion detection systems for safeguarding security. While deep learning models have exhibited promising results in intrusion detection, they face challenges in managing...

Adaptive Pruning of Deep Neural Networks for Resource-Aware Embedded Intrusion Detection on the Edge

Artificial neural network pruning is a method in which artificial neural network sizes can be reduced while attempting to preserve the predicting capabilities of the network. This is done to make the model smaller or faster during inference time. In this work we analyze the ability of a selection...

Robust and Efficient AI-Based Attack Recovery in Autonomous Drones

We introduce an autonomous attack recovery architecture to add common sense reasoning to plan a recovery action after an attack is detected. We outline use-cases of our architecture using drones, and then discuss how to implement this architecture efficiently and securely in edge devices...

Trustworthy Reputation Games and Applications to Proof-Of-Reputation Blockchains

Reputation systems play an essential role in the Internet era, as they enable people to decide whom to trust, by collecting and aggregating data about users' behavior. Recently, several works proposed the use of reputation for the design and scalability improvement of decentralized blockchain...

Multiple Proposer Transaction Fee Mechanism Design: Robust Incentives against Censorship and Bribery

Censorship resistance is one of the core value proposition of blockchains. A recurring design pattern aimed at providing censorship resistance is enabling multiple proposers to contribute inputs into block construction. Notably, Fork-Choice Enforced Inclusion Lists FOCIL is proposed to be include...

VulCPE: Context-Aware Cybersecurity Vulnerability Retrieval and Management

The dynamic landscape of cybersecurity demands precise and scalable solutions for vulnerability management in heterogeneous systems, where configuration-specific vulnerabilities are often misidentified due to inconsistent data in databases like the National Vulnerability Database NVD. Inaccurate...

ArcGIS Insecure OAuth 2.0 Implementation

The ArcGIS clientcredentials OAuth 2.0 API implementation does not adhere to the RFC/standards; This hidden known and by-design, but undocumented functionality enables a requester referred to as client in RFC 6749 to request an, undocumented, custom token expiration from ArcGIS referred to as...

When Mitigations Backfire: Timing Channel Attacks and Defense for PRAC-Based RowHammer Mitigations

Per Row Activation Counting PRAC has emerged as a robust framework for mitigating RowHammer RH vulnerabilities in modern DRAM systems. However, we uncover a critical vulnerability: a timing channel introduced by the Alert Back-Off ABO protocol and Refresh Management RFM commands. We present...

Provable Execution in Real-Time Embedded Systems

Embedded devices are increasingly ubiquitous and vital, often supporting safety-critical functions. However, due to strict cost and energy constraints, they are typically implemented with Micro-Controller Units MCUs that lack advanced architectural security features. Within this space, recent...

The Hidden Dangers of Browsing AI Agents

Autonomous browsing agents powered by large language models LLMs are increasingly used to automate web-based tasks. However, their reliance on dynamic content, tool execution, and user-provided data exposes them to a broad attack surface. This paper presents a comprehensive security evaluation of...

Traceable Black-Box Watermarks for Federated Learning

Whitepaper called Traceable Black-Box Watermarks For Federated Learning...

DynaNoise: Dynamic Probabilistic Noise Injection for Defending against Membership Inference Attacks

Membership Inference Attacks MIAs pose a significant risk to the privacy of training datasets by exploiting subtle differences in model outputs to determine whether a particular data sample was used during training. These attacks can compromise sensitive information, especially in domains such as...

Apple Security Advisory 05-12-2025-4

Apple Security Advisory 05-12-2025-4 - macOS Sonoma 14.7.6 addresses bypass, code execution, double free, information leakage, integer overflow, out of bounds read, and use-after-free vulnerabilities...

Malware Families Discovery Via Open-Set Recognition on Android Manifest Permissions

Malware are malicious programs that are grouped into families based on their penetration technique, source code, and other characteristics. Classifying malware programs into their respective families is essential for building effective defenses against cyber threats. Machine learning models have ...

Quantum Opacity, Classical Clarity: a Hybrid Approach to Quantum Circuit Obfuscation

Quantum computing leverages quantum mechanics to achieve computational advantages over classical hardware, but the use of third-party quantum compilers in the Noisy Intermediate-Scale Quantum NISQ era introduces risks of intellectual property IP exposure. We address this by proposing a novel...

One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems

Large Language Models LLMs enhanced with Retrieval-Augmented Generation RAG have shown improved performance in generating accurate responses. However, the dependence on external knowledge bases introduces potential security vulnerabilities, particularly when these knowledge bases are publicly...

Prink: $K_s$-Anonymization for Streaming Data in Apache Flink

In this paper, we present Prink, a novel and practically applicable concept and fully implemented prototype for ks-anonymizing data streams in real-world application architectures. Building upon the pre-existing, yet rudimentary CASTLE scheme, Prink for the first time introduces semantics-aware...

Optimal Client Sampling in Federated Learning with Client-Level Heterogeneous Differential Privacy

Federated Learning with client-level differential privacy DP provides a promising framework for collaboratively training models while rigorously protecting clients' privacy. However, classic approaches like DP-FedAvg struggle when clients have heterogeneous privacy requirements, as they must...

RAR: Setting Knowledge Tripwires for Retrieval Augmented Rejection

Content moderation for large language models LLMs remains a significant challenge, requiring flexible and adaptable solutions that can quickly respond to emerging threats. This paper introduces Retrieval Augmented Rejection RAR, a novel approach that leverages a retrieval-augmented generation RAG...

Apple Security Advisory 05-12-2025-1

Apple Security Advisory 05-12-2025-1 - iOS 18.5 and iPadOS 18.5 addresses code execution, double free, integer overflow, out of bounds read, spoofing, and use-after-free vulnerabilities...

Apple Security Advisory 05-12-2025-7

Apple Security Advisory 05-12-2025-7 - tvOS 18.5 addresses code execution, double free, integer overflow, out of bounds read, and use-after-free vulnerabilities...

Apple Security Advisory 05-12-2025-3

Apple Security Advisory 05-12-2025-3 - macOS Sequoia 15.5 addresses bypass, code execution, double free, information leakage, integer overflow, out of bounds read, and use-after-free vulnerabilities...

Recommender Systems for Democracy: toward Adversarial Robustness in Voting Advice Applications

Voting advice applications VAAs help millions of voters understand which political parties or candidates best align with their views. This paper explores the potential risks these applications pose to the democratic process when targeted by adversarial entities. In particular, we expose 11...

Security Degradation in Iterative AI Code Generation -- a Systematic Analysis of the Paradox

The rapid adoption of Large Language ModelsLLMs for code generation has transformed software development, yet little attention has been given to how security vulnerabilities evolve through iterative LLM feedback. This paper analyzes security degradation in AI-generated code through a controlled...

WordPress Eventin 4.0.26 Privilege Escalation

WordPress Eventin plugin versions 4.0.26 and below suffers from an unauthenticated privilege escalation vulnerability due to a missing authorization check in the importitems function...

BeamClean: Language Aware Embedding Reconstruction

In this work, we consider an inversion attack on the obfuscated input embeddings sent to a language model on a server, where the adversary has no access to the language model or the obfuscation mechanism and sees only the obfuscated embeddings along with the model's embedding table. We propose...

An Automated Blackbox Noncompliance Checker for QUIC Server Implementations

We develop QUICtester, an automated approach for uncovering non-compliant behaviors in the ratified QUIC protocol implementations RFC 9000/9001. QUICtester leverages active automata learning to abstract the behavior of a QUIC implementation into a finite state machine FSM representation. Unlike...

ACE: Confidential Computing for Embedded RISC-V Systems

Confidential computing plays an important role in isolating sensitive applications from the vast amount of untrusted code commonly found in the modern cloud. We argue that it can also be leveraged to build safer and more secure mission-critical embedded systems. In this paper, we introduce the...

DeFeed: Secure Decentralized Cross-Contract Data Feed in Web 3.0 for Connected Autonomous Vehicles

Smart contracts have been a topic of interest in blockchain research and are a key enabling technology for Connected Autonomous Vehicles CAVs in the era of Web 3.0. These contracts enable trustless interactions without the need for intermediaries, as they operate based on predefined rules encoded...

A Systematic Review and Taxonomy for Privacy Breach Classification: Trends, Gaps, and Future Directions

In response to the rising frequency and complexity of data breaches and evolving global privacy regulations, this study presents a comprehensive examination of academic literature on the classification of privacy breaches and violations between 2010-2024. Through a systematic literature review, a...

FLTG: Byzantine-Robust Federated Learning Via Angle-Based Defense and Non-IID-Aware Weighting

Byzantine attacks during model aggregation in Federated Learning FL threaten training integrity by manipulating malicious clients' updates. Existing methods struggle with limited robustness under high malicious client ratios and sensitivity to non-i.i.d. data, leading to degraded accuracy. To...

Apple Security Advisory 05-12-2025-9

Apple Security Advisory 05-12-2025-9 - Safari 18.5 addresses various issues that could lead to memory corruption...

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?

Low rank adaptation LoRA has emerged as a prominent technique for fine-tuning large language models LLMs thanks to its superb efficiency gains over previous methods. While extensive studies have examined the performance and structural properties of LoRA, its behavior upon training-time attacks...

Writing a Good Security Paper for ISSCC (2025)

Security is increasingly more important in designing chips and systems based on them, and the International Solid-State Circuits Conference ISSCC, the leading conference for presenting advances in solid-state circuits and semiconductor technology, is committed to hardware security by establishing...

Testing Access-Control Configuration Changes for Web Applications

Access-control misconfigurations are among the main causes of today's data breaches in web applications. However, few techniques are available to support automatic and systematic testing for access-control changes and detecting risky changes to prevent severe consequences. As a result, those...

Network-Wide Quantum Key Distribution with Onion Routing Relay

The advancement of quantum computing threatens classical cryptographic methods, necessitating the development of secure quantum key distribution QKD solutions for QKD Networks QKDN. In this paper, a novel key distribution protocol, Onion Routing Relay ORR, that integrates onion routing OR with...

An Alignment between the CRA'S Essential Requirements and the ATT&CK'S Mitigations

The paper presents an alignment evaluation between the mitigations present in the MITRE's ATT&CK framework and the essential cyber security requirements of the recently introduced Cyber Resilience Act CRA in the European Union. In overall, the two align well with each other. With respect to the...

Information-Theoretically Secure Quantum Timestamping with One-Time Universal Hashing

Accurate and tamper-resistant timestamps are essential for applications demanding verifiable chronological ordering, such as legal documentation and digital intellectual property protection. Classical timestamp protocols rely on computational assumptions for security, rendering them vulnerable to...

Lara: Lightweight Anonymous Authentication with Asynchronous Revocation Auditability

Anonymous authentication is a technique that allows to combine access control with privacy preservation. Typically, clients use different pseudonyms for each access, hindering providers from correlating their activities. To perform the revocation of pseudonyms in a privacy preserving manner is...

HChain 4.0: a Secure and Scalable Permissioned Blockchain for EHR Management in Smart Healthcare

The growing utilization of Internet of Medical Things IoMT devices, including smartwatches and wearable medical devices, has facilitated real-time health monitoring and data analysis to enhance healthcare outcomes. These gadgets necessitate improved security measures to safeguard sensitive health...

Shielding Latent Face Representations from Privacy Attacks

In today's data-driven analytics landscape, deep learning has become a powerful tool, with latent representations, known as embeddings, playing a central role in several applications. In the face analytics domain, such embeddings are commonly used for biometric recognition e.g., face...

MorphMark: Flexible Adaptive Watermarking for Large Language Models

Watermarking by altering token sampling probabilities based on red-green list is a promising method for tracing the origin of text generated by large language models LLMs. However, existing watermark methods often struggle with a fundamental dilemma: improving watermark effectiveness the...

Outsourced Privacy-Preserving Feature Selection Based on Fully Homomorphic Encryption

Feature selection is a technique that extracts a meaningful subset from a set of features in training data. When the training data is large-scale, appropriate feature selection enables the removal of redundant features, which can improve generalization performance, accelerate the training process...

MCP Guardian: a Security-First Layer for Safeguarding MCP-Based AI System

As Agentic AI gain mainstream adoption, the industry invests heavily in model capabilities, achieving rapid leaps in reasoning and quality. However, these systems remain largely confined to data silos, and each new integration requires custom logic that is difficult to scale. The Model Context...

Cross-Cloud Data Privacy Protection: Optimizing Collaborative Mechanisms of AI Systems by Integrating Federated Learning and LLMs

In the age of cloud computing, data privacy protection has become a major challenge, especially when sharing sensitive data across cloud environments. However, how to optimize collaboration across cloud environments remains an unresolved problem. In this paper, we combine federated learning with...

FlowPure: Continuous Normalizing Flows for Adversarial Purification

Despite significant advancements in the area, adversarial robustness remains a critical challenge in systems employing machine learning models. The removal of adversarial perturbations at inference time, known as adversarial purification, has emerged as a promising defense strategy. To achieve...