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On the Security of Research Artifacts SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety 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 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
FairRelay: Fair and Cost-Efficient Peer-to-Peer Content D...
Jingyu Liu, Yingjie Xue, Zifan Peng, Chao Lin, Xinyi Huang · 2024-05-05 · via cs.CR updates on arXiv.org

Peer-to-Peer (P2P) content delivery, known for scalability and resilience, offers a decentralized alternative to traditional centralized Content Delivery Networks (CDNs). A significant challenge in P2P content delivery remains: the fair compensation of relayers for their bandwidth contributions. Existing solutions employ blockchains for payment settlements, however, they are not practical due to high on-chain costs and over-simplified network assumptions. In this paper, we introduce FairRelay, a fair and cost-efficient protocol that ensures all participants get fair payoff in complex content delivery network settings. We introduce a novel primitive, Enforceable Accumulative Hashed TimeLock Contract (Enforceable A-HTLC), designed to guarantee payment atomicity - ensuring all participants receive their payments upon successful content delivery. The fairness of FairRelay is proved using the Universal Composability (UC) framework. Our evaluation demonstrates that, in optimistic scenarios, FairRelay employs zero on-chain costs. In pessimistic scenarios, the on-chain dispute costs for relayers and customers are constant, irrespective of the network complexity. Specifically, empirical results indicate that the on-chain dispute costs for relayers and customers are 24,902 gas (equivalent to 0.01 USD on Optimism L2) and 290,797 gas (0.07 USD), respectively. In a 10-hop relay path, FairRelay introduces less than 1.5% additional overhead compared to pure data transmission, showcasing the efficiency of FairRelay.