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cs.CR updates on arXiv.org

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
HTTPA/2: a Trusted End-to-End Protocol for Web Services
Gordon King, Hans Wang · 2022-05-03 · via cs.CR updates on arXiv.org

With the advent of cloud computing and the Internet, the commercialized website becomes capable of providing more web services, such as software as a service (SaaS) or function as a service (FaaS), for great user experiences. Undoubtedly, web services have been thriving in popularity that will continue growing to serve modern human life. As expected, there came the ineluctable need for preserving privacy, enhancing security, and building trust. However, HTTPS alone cannot provide a remote attestation for building trust with web services, which remains lacking in trust. At the same time, cloud computing is actively adopting the use of TEEs and will demand a web-based protocol for remote attestation with ease of use. Here, we propose HTTPA/2 as an upgraded version of HTTP-Attestable (HTTPA) by augmenting existing HTTP to enable end-to-end trusted communication between endpoints at layer 7 (L7). HTTPA/2 allows for L7 message protection without relying on TLS. In practice, HTTPA/2 is designed to be compatible with the in-network processing of the modern cloud infrastructure, including L7 gateway, L7 load balancer, caching, etc. We envision that \acs{httpa}/2 will further enable trustworthy web services and trustworthy AI applications in the future, accelerating the transformation of the web-based digital world to be more trustworthy.