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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
RSMS: Towards Reliable and Secure Metaverse Service Provi...
Yanwei Gong, Xiaolin Chang, Jelena Mišić, Vojislav B. Mišić, Yin · 2023-10-08 · via cs.CR updates on arXiv.org

Establishing and sustaining Metaverse service necessitates an unprecedented scale of resources. This paper considers the deployment of Metaverse service in a cloud-edge resource architecture, which can satisfy the escalating demand for Metaverse service resources while ensuring both high bandwidth and low latency. We propose a novel mechanism, named Reliable and Secure Metaverse Service (RSMS), to ensure Metaverse service reliability and security without sacrificing performance. RSMS consists of two protocols: (1) One is a blockchain-based lightweight mutual authentication protocol concerning heterogeneous Metaverse service resource nodes (RNs) dynamically joining a Metaverse service resource pool while guaranteeing their trustworthiness, which guarantees the security of Metaverse service. (2) The other is a group authentication protocol used to form and maintain a stable and secure Metaverse service group composed by RNs, which ensures the reliability and enhances the security of Metaverse service. The reliability and security of Metaverse service under RSMS are thoroughly discussed, and informal and formal security analysis are conducted. Additionally, we study the impact of RSMS on Metaverse service throughput, demonstrating its lightweight feature.