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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 Token-Efficient Change Detection in LLM APIs Selfie-Capture Dynamics as an Auxiliary Signal Against Deepfakes and Injection Attacks for Mobile Identity Verification Trident: Improving Malware Detection with LLMs and Behavioral Features When Alignment Isn't Enough: Response-Path Attacks on LLM Agents RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs Checkerboard: A Simple, Effective, Efficient and Learning-free Clean Label Backdoor Attack with Low Poisoning Budget Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Secret Stealing Attacks on Local LLM Fine-Tuning through Supply-Chain Model Code Backdoors Enhancing Linux Privilege Escalation Attack Capabilities of Local LLM Agents Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning FlexServe: A Fast and Secure LLM Serving System for Mobile Devices with Flexible Resource Isolation Breaking MCP with Function Hijacking Attacks: Novel Threats for Function Calling and Agentic Models Text Steganography with Dynamic Codebook and Multimodal Large Language Model An AI Agent Execution Environment to Safeguard User Data TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD 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 QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits 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 One Word at a Time: Incremental Completion Decomposition Breaks LLM Safety Measuring and Exploiting Contextual Bias in LLM-Assisted Security Code Review
Token-based Vehicular Security System (TVSS): Scalable, S...
Abdulrahman Bin Rabiah, Anas Alsoliman, Yugarshi Shashwat, Silas · 2024-02-28 · via cs.CR updates on arXiv.org

Connected and Autonomous vehicles stand to drastically improve the safety and efficiency of the transportation system in the near future while also reducing pollution. These systems leverage communication to coordinate among vehicles and infrastructure in service of a number of safety and efficiency driver assist and even fully autonomous applications. Attackers can compromise these systems in a number of ways including by falsifying communication messages, making it critical to support security mechanisms that can operate and scale in dynamic scenarios. Towards this end, we present TVSS, a new VPKI system which improves drastically over prior work in the area (including over SCMS; the US department of transportation standard for VPKI). TVSS leverages the idea of unforgeable tokens to enable rapid verification at the road side units (RSUs), which are part of the road infrastructure at the edge of the network. This edge based solution enables agile authentication by avoiding the need for back-end servers during the potentially short contact time between a moving vehicle and the infrastructure. It also results in several security advantages: (1) Scalable Revocation: it greatly simplifies the revocation problem, a difficult problem in large scale certificate systems; and (2) Faster Refresh: Vehicles interact more frequently with the system to refresh their credentials, improving the privacy of the system. We provide a construction of the system and formally prove its security. Field experiments on a test-bed we develop consisting of on-board units (OBUs) and RSUs shows substantial reduction in the latency of refreshing credentials compared to SCMS, allowing the system to work even with smaller window of connectivity when vehicles are moving at higher speeds. Notably, we are able to execute the bottleneck operation of our scheme with a stationary RSU while traveling at highway speeds .