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

Martin Fowler
Martin Fowler
Blog — PlanetScale
Blog — PlanetScale
Vercel News
Vercel News
L
LangChain Blog
Google DeepMind News
Google DeepMind News
H
Hackread – Cybersecurity News, Data Breaches, AI and More
F
Fortinet All Blogs
The GitHub Blog
The GitHub Blog
Recent Announcements
Recent Announcements
D
DataBreaches.Net
云风的 BLOG
云风的 BLOG
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
A
About on SuperTechFans
博客园_首页
N
Netflix TechBlog - Medium
Y
Y Combinator Blog
Hugging Face - Blog
Hugging Face - Blog
Last Week in AI
Last Week in AI
酷 壳 – CoolShell
酷 壳 – CoolShell
B
Blog
Apple Machine Learning Research
Apple Machine Learning Research
罗磊的独立博客
美团技术团队
V
V2EX

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
Smart Contract Development from the Perspective of Develo...
Afiya Ayman, Shanto Roy, Amin Alipour, Aron Laszka · 2019-05-16 · via cs.CR updates on arXiv.org

Blockchain-based platforms are emerging as a transformative technology that can provide reliability, integrity, and auditability without trusted entities. One of the key features of these platforms is the trustworthy decentralized execution of general-purpose computation in the form of smart contracts, which are envisioned to have a wide range of applications. As a result, a rapidly growing and active community of smart-contract developers has emerged in recent years. A number of research efforts have investigated the technological challenges that these developers face, introducing a variety of tools, languages, and frameworks for smart-contract development, focusing on security. However, relatively little is known about the community itself, about the developers, and about the issues that they face and discuss. To address this gap, we study smart-contract developers and their discussions on two social media sites, Stack Exchange and Medium. We provide insight into the trends and key topics of these discussions, into the developers' interest in various security issues and security tools, and into the developers' technological background.