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

爱范儿
爱范儿
大猫的无限游戏
大猫的无限游戏
J
Java Code Geeks
MongoDB | Blog
MongoDB | Blog
Martin Fowler
Martin Fowler
GbyAI
GbyAI
Microsoft Azure Blog
Microsoft Azure Blog
Recent Announcements
Recent Announcements
F
Fortinet All Blogs
B
Blog
U
Unit 42
B
Blog RSS Feed
D
DataBreaches.Net
Google DeepMind News
Google DeepMind News
人人都是产品经理
人人都是产品经理
腾讯CDC
量子位
酷 壳 – CoolShell
酷 壳 – CoolShell
V
Visual Studio Blog
博客园 - 聂微东
MyScale Blog
MyScale Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
博客园 - 三生石上(FineUI控件)
Engineering at Meta
Engineering at Meta

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
Practical Low Latency Proof of Work Consensus
Lei Yang, Xuechao Wang, Vivek Bagaria, Gerui Wang, Mohammad Aliz · 2019-09-25 · via cs.CR updates on arXiv.org

Bitcoin is the first fully-decentralized permissionless blockchain protocol to achieve a high level of security, but at the expense of poor throughput and latency. Scaling the performance of Bitcoin has a been a major recent direction of research. One successful direction of work has involved replacing proof of work (PoW) by proof of stake (PoS). Proposals to scale the performance in the PoW setting itself have focused mostly on parallelizing the mining process, scaling throughput; the few proposals to improve latency have either sacrificed throughput or the latency guarantees involve large constants rendering it practically useless. Our first contribution is to design a new PoW blockchain Prism++ that has provably low latency and high throughput; the design retains the parallel-chain approach espoused in Prism but invents a new confirmation rule to infer the permanency of a block by combining information across the parallel chains. We show security at the level of Bitcoin with very small confirmation latency (a small constant factor of block interarrival time). A key aspect to scaling the performance is to use a large number of parallel chains, which puts significant strain on the system. Our second contribution is the design and evaluation of a practical system to efficiently manage the memory, computation, and I/O imperatives of a large number of parallel chains. Our implementation of Prism++ achieves a throughput of over 80,000 transactions per second and confirmation latency of tens of seconds on networks of up to 900 EC2 Virtual Machines.