The effect of constraints on information loss and risk for clustering and modification based graph anonymization methods

Backdoor Channels Hidden in Latent Space: Cryptographic Undetectability in Modern Neural Networks

CTFusion: A CTF-based Benchmark for LLM Agent Evaluation

Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety

From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World

Red-Teaming Agent Execution Contexts: Open-World Security Evaluation on OpenClaw

Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs

Containment Verification: AI Safety Guarantees Independent of Alignment

Defense effectiveness across architectural layers: a mechanistic evaluation of persistent memory attacks on stateful LLM agents

From Specification to Deployment: Empirical Evidence from a W3C VC + DID Trust Infrastructure for Autonomous Agents

Agentic Vulnerability Reasoning on Windows COM Binaries

From Beats to Breaches:How Offensive AI Infers Sensitive User Information from Playlists

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions

When Embedding-Based Defenses Fail: Rethinking Safety in LLM-Based Multi-Agent Systems

Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking

FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation

TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models

Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility

Hardening x402: PII-Safe Agentic Payments via Pre-Execution Metadata Filtering

Hijacking Text Heritage: Hiding the Human Signature through Homoglyphic Substitution

Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit

Private Seeds, Public LLMs: Realistic and Privacy-Preserving Synthetic Data Generation

StegoStylo: Squelching Stylometric Scrutiny through Steganographic Stitching

Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models

AutoGraphAD: Unsupervised network anomaly detection using Variational Graph Autoencoders

CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks

Feedback Lunch: Learned Feedback Codes for Secure Communications

Noise Aggregation Analysis Driven by Small-Noise Injection: Efficient Membership Inference for Diffusion Models

A First Look at the Security Issues in the Model Context Protocol Ecosystem

Formalizing the Safety, Security, and Functional Properties of Agentic AI Systems

MEASER: Malware embedding attacks on open-source LLMs

Fall into a Pit, Gain in a Wit: Cognitive-Guided Harmful Meme Detection via Misjudgment Risk Pattern Retrieval

When Search Goes Wrong: Red-Teaming Web-Augmented Large Language Models

Differentially Private Synthetic Text Generation for Retrieval-Augmented Generation (RAG)

From surveillance to signalling: escalation channels as environmental controls for agentic AI

STAC: When Innocent Tools Form Dangerous Chains to Jailbreak LLM Agents

Federated Spatiotemporal Graph Learning for Passive Attack Detection in Smart Grids

Guidance Watermarking for Diffusion Models

SecureVibeBench: Benchmarking Secure Vibe Coding of AI Agents via Reconstructing Vulnerability-Introducing Scenarios

xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models

Hammer and Anvil: Toward a Theory of Backdoors in Federated Learning

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities

Tell-Tale Watermarks for Explanatory Reasoning in Synthetic Media Forensics

Between a Rock and a Hard Place: The Tension Between Ethical Reasoning and Safety Alignment in LLMs

A Comprehensive Guide to Differential Privacy: From Theory to User Expectations

Enabling Transparent Cyber Threat Intelligence Combining Large Language Models and Domain Ontologies

Unveiling Unicode's Unseen Underpinnings in Undermining Authorship Attribution

Searching for Privacy Risks in LLM Agents via Simulation

Exact Verification of Graph Neural Networks with Incremental Constraint Solving

SPRINT: Robust Model Attribution of Generated Images via Secret Pixel Reconstruction

Majority Bit-Aware Watermarking For Large Language Models

Coward: Collision-based OOD Watermarking for Practical Proactive Federated Backdoor Detection

Prompt to Pwn: Automated Exploit Generation for Smart Contracts

Activation-Guided Local Editing for Jailbreaking Attacks

Random Walk Learning and the Pac-Man Attack

ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation

White-Basilisk: A Hybrid Model for Code Vulnerability Detection

Intrinsic Fingerprint of LLMs: Continue Training is NOT All You Need to Steal A Model!

InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy

Logit-Gap Steering: A Forward-Pass Diagnostic for Alignment Robustness

Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem

Exploring the Secondary Risks of Large Language Models

Benchmarking Misuse Mitigation Against Covert Adversaries

Efficient Preimage Approximation for Neural Network Certification

Practical Adversarial Attacks on Stochastic Bandits via Fake Data Injection

PARASITE: Conditional System Prompt Poisoning to Hijack LLMs

Secure LLM Fine-Tuning via Safety-Aware Probing

Can Large Language Models Really Recognize Your Name?

PoLO: Proof-of-Learning and Proof-of-Ownership at Once with Chained Watermarking

A Survey on the Safety and Security Threats of Computer-Using Agents: JARVIS or Ultron?

AutoRAN: Automated Hijacking of Safety Reasoning in Large Reasoning Models

Remote Rowhammer Attack using Adversarial Observations on Federated Learning Clients

Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents

DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion

Chronology of Multi-Agent Interactions for Provenance of Evolving Information

Gungnir: Exploiting Stylistic Features in Images for Backdoor Attacks on Diffusion Models

DeePen: Penetration Testing for Audio Deepfake Detection

Detecting Malicious Concepts without Image Generation in AI-Generated Content (AIGC)

How Vulnerable Is My Learned Policy? Universal Adversarial Perturbation Attacks On Modern Behavior Cloning Policies

Imitation Game for Adversarial Disillusion with Chain-of-Thought Reasoning in Generative AI

PromptGuard: Soft Prompt-Guided Unsafe Content Moderation for Text-to-Image Models

A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis

Red-Teaming Text-to-Image Models via In-Context Experience Replay and Semantic-Preserving Prompt Rewriting

DeTrigger: A Gradient-Centric Approach to Backdoor Attack Mitigation in Federated Learning

Privacy Leakage via Output Label Space and Differentially Private Continual Learning

ARQ: A Mixed-Precision Quantization Framework for Accurate and Certifiably Robust DNNs

CoreGuard: Safeguarding Foundational Capabilities of LLMs Against Model Stealing in Edge Deployment

Power-Softmax: Towards Secure LLM Inference over Encrypted Data

Hypnopaedia-Aware Machine Unlearning via Psychometrics of Artificial Mental Imagery

Anomaly Detection from a Tensor Train Perspective

Survival of the Cheapest: Cost-Aware Hardware Adaptation for Adversarial Robustness

Convergent Differential Privacy Analysis for General Federated Learning

Improving Clean Accuracy via a Tangent-Space Perspective on Adversarial Training

The AI risk repository: A meta-review, database, and taxonomy of risks from artificial intelligence

Towards Agentic Runtime Healing

Verification of Machine Unlearning is Fragile

Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated Learning

Whispers in the Machine: Confidentiality in Agentic Systems

MalPurifier: Enhancing Android Malware Detection with Adversarial Purification against Evasion Attacks

Towards Adaptive, Learning-Based Security in Decentralized Applications

Can Blockchains Reliably Train Machine Learning Models?

推荐订阅源

cs.CR updates on arXiv.org