惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
AWS News Blog
AWS News Blog
V
Vulnerabilities – Threatpost
D
Darknet – Hacking Tools, Hacker News & Cyber Security
量子位
博客园 - 叶小钗
AI
AI
T
Tor Project blog
Forbes - Security
Forbes - Security
W
WeLiveSecurity
博客园_首页
爱范儿
爱范儿
J
Java Code Geeks
B
Blog
G
GRAHAM CLULEY
aimingoo的专栏
aimingoo的专栏
Cloudbric
Cloudbric
C
CXSECURITY Database RSS Feed - CXSecurity.com
TaoSecurity Blog
TaoSecurity Blog
L
LINUX DO - 热门话题
阮一峰的网络日志
阮一峰的网络日志
有赞技术团队
有赞技术团队
Threat Intelligence Blog | Flashpoint
Threat Intelligence Blog | Flashpoint
Simon Willison's Weblog
Simon Willison's Weblog
云风的 BLOG
云风的 BLOG
Google DeepMind News
Google DeepMind News
H
Help Net Security
博客园 - 三生石上(FineUI控件)
C
Cisco Blogs
C
Cybersecurity and Infrastructure Security Agency CISA
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
P
Palo Alto Networks Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Recent Commits to openclaw:main
Recent Commits to openclaw:main
博客园 - 司徒正美
The Last Watchdog
The Last Watchdog
Blog — PlanetScale
Blog — PlanetScale
T
The Blog of Author Tim Ferriss
S
Secure Thoughts
Spread Privacy
Spread Privacy
F
Fortinet All Blogs
月光博客
月光博客
大猫的无限游戏
大猫的无限游戏
S
SegmentFault 最新的问题
H
Hackread – Cybersecurity News, Data Breaches, AI and More
A
About on SuperTechFans
Security Latest
Security Latest
Webroot Blog
Webroot Blog
Scott Helme
Scott Helme
Hugging Face - Blog
Hugging Face - Blog

cs.CR updates on arXiv.org

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?
Sandi: A System for Accountability and Applications in Direct Communication (Extended Abstract)
F. Betül Durak, Kim Laine, Simon Langowski, Radames Cruz Moreno, · 2023-11-09 · via cs.CR updates on arXiv.org

Reputation systems guide our decision making both in life and work: which restaurant to eat at, which vendor to buy from, which software dependencies to use, and who or what to trust. These systems are often based on old ideas and are failing in the face of modern threats. Fraudsters have found ways to manipulate them, undermining their integrity and utility. Generative AI adds to the problem by enabling the creation of real-looking fake narratives at scale, creating a false sense of consensus. Meanwhile, the need for reliable reputation concepts is more important than ever, as wrong decisions lead to increasingly severe outcomes: wasted time, poor service, and a feeling of injustice at best, fraud, identity theft, and ransomware at worst. In this extended abstract we introduce Sandi, a new kind of reputation system with a single well-defined purpose: to create trust through accountability in one-to-one transactions. Examples of such transactions include sending an email or making a purchase online. Sandi has strong security and privacy properties that make it suitable for use also in sensitive contexts. Furthermore, Sandi can guarantee reputation integrity and transparency for its registered users. As a primary application, we envision how Sandi could counter fraud and abuse in direct communication. Concretely, message senders request a cryptographic tag from Sandi that they send along with their message. If the receiver finds the message inappropriate, they can report the sender using this tag. Notably, only senders need registered accounts and do not need to manage long-term keys. The design of Sandi ensures compatibility with any communication system that allows for small binary data transmission.