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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
Proofs of Proof-of-Stake with Sublinear Complexity
Shresth Agrawal, Joachim Neu, Ertem Nusret Tas, Dionysis Zindros · 2022-09-19 · via cs.CR updates on arXiv.org

Popular Ethereum wallets (like MetaMask) entrust centralized infrastructure providers (e.g., Infura) to run the consensus client logic on their behalf. As a result, these wallets are light-weight and high-performant, but come with security risks. A malicious provider can mislead the wallet by faking payments and balances, or censoring transactions. On the other hand, light clients, which are not in popular use today, allow decentralization, but are concretely inefficient, often with asymptotically linear bootstrapping complexity. This poses a dilemma between decentralization and performance. We design, implement, and evaluate a new proof-of-stake (PoS) superlight client with concretely efficient and asymptotically logarithmic bootstrapping complexity. Our proofs of proof-of-stake (PoPoS) take the form of a Merkle tree of PoS epochs. The verifier enrolls the provers in a bisection game, in which honest provers are destined to win once an adversarial Merkle tree is challenged at sufficient depth. We provide an implementation for mainnet Ethereum: compared to the state-of-the-art light client construction of Ethereum, our client improves time-to-completion by 9x, communication by 180x, and energy usage by 30x (when bootstrapping after 10 years of consensus execution). As an important additional application, our construction can be used to realize trustless cross-chain bridges, in which the superlight client runs within a smart contract and takes the role of an on-chain verifier. We prove our construction is secure and show how to employ it for other PoS systems such as Cardano (with fully adaptive adversary), Algorand, and Snow White.