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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
Synchro: Block-generation Protocol to Synchronously Proce...
Takaki Asanuma, Takeshi Miyamae, Yuji Yamaoka · 2023-09-04 · via cs.CR updates on arXiv.org

Traditional blockchains cannot achieve the same transaction throughput as Web2, so their use cases are limited. Therefore, state sharding has been proposed to improve transaction throughput by dividing the blockchain network and managing states and transactions in parallel. However, Nightshade in the NEAR Protocol, a type of state sharding, provides a rollback protocol to cancel the generation of blocks containing inconsistent transaction results because processing cross-shard transactions (CSTXs) in a 2-phase commit may cause state inconsistency. We present a new attack that interferes with the generation of new blocks by repeatedly executing CSTXs that certainly causes state inconsistency, causing continuous rollback. We also propose a block-generation protocol called Synchro to incorporate all the state changes of each CSTX into the same block by coordinating the block prior to approving transactions in each shard. Synchro eliminates the occurrence of the state inconsistency caused by the CSTXs and the necessity of the rollback protocol. We use zero-knowledge proof to make Synchro scalable in the global validation phase. Although the actual overhead of the zero-knowledge proof has not yet been evaluated, we show that Synchro could achieve the same transaction throughput as Nightshade theoretically, depending on the future innovations in zero-knowledge proof techniques.