惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

WordPress大学
WordPress大学
B
Blog
M
MIT News - Artificial intelligence
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
P
Proofpoint News Feed
C
Check Point Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
J
Java Code Geeks
博客园 - 叶小钗
S
SegmentFault 最新的问题
Last Week in AI
Last Week in AI
T
The Blog of Author Tim Ferriss
Microsoft Security Blog
Microsoft Security Blog
小众软件
小众软件
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园 - 【当耐特】
腾讯CDC
博客园 - Franky
博客园 - 聂微东
V
Visual Studio Blog
GbyAI
GbyAI
Martin Fowler
Martin Fowler
罗磊的独立博客
Y
Y Combinator Blog

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
Cloak: Transitioning States on Legacy Blockchains Using S...
Qian Ren, Yingjun Wu, Han Liu, Yue Li, Anne Victor, Hong Lei, Le · 2021-06-26 · via cs.CR updates on arXiv.org

In recent years, the confidentiality of smart contracts has become a fundamental requirement for practical applications. While many efforts have been made to develop architectural capabilities for enforcing confidential smart contracts, a few works arise to extend confidential smart contracts to Multi-Party Computation (MPC), i.e., multiple parties jointly evaluate a transaction off-chain and commit the outputs on-chain without revealing their secret inputs/outputs to each other. However, existing solutions lack public verifiability and require O(n) transactions to enable negotiation or resist adversaries, thus suffering from inefficiency and compromised security. In this paper, we propose Cloak, a framework for enabling Multi-Party Transaction (MPT) on existing blockchains. An MPT refers to transitioning blockchain states by an publicly verifiable off-chain MPC. We identify and handle the challenges of securing MPT by harmonizing TEE and blockchain. Consequently, Cloak secures the off-chain nondeterministic negotiation process (a party joins an MPT without knowing identities or the total number of parties until the MPT proposal settles), achieves public verifiability (the public can validate that the MPT correctly handles the secret inputs/outputs from multiple parties and reads/writes states on-chain), and resists Byzantine adversaries. According to our proof, Cloak achieves better security with only 2 transactions, superior to previous works that achieve compromised security at O(n) transactions cost. By evaluating examples and real-world MPTs, the gas cost of Cloak reduces by 32.4% on average.