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

IT之家
IT之家
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
A
About on SuperTechFans
博客园 - 聂微东
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
B
Blog RSS Feed
U
Unit 42
Stack Overflow Blog
Stack Overflow Blog
Recent Announcements
Recent Announcements
雷峰网
雷峰网
罗磊的独立博客
Microsoft Security Blog
Microsoft Security Blog
Hugging Face - Blog
Hugging Face - Blog
L
LangChain Blog
人人都是产品经理
人人都是产品经理
The GitHub Blog
The GitHub Blog
F
Fortinet All Blogs
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
H
Help Net Security
P
Proofpoint News Feed
The Cloudflare Blog
D
Docker
大猫的无限游戏
大猫的无限游戏

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
Location-Enhanced Authenticated Key Exchange
Marcos Portnoi, Chien-Chung Shen · 2015-10-28 · via cs.CR updates on arXiv.org

We introduce LOCATHE (Location-Enhanced Authenticated Key Exchange), a generic protocol that pools location, user attributes, access policy and desired services into a multi-factor authentication, allowing two peers to establish a secure, encrypted session and perform mutual authentication with pre-shared keys, passwords and other authentication factors. LOCATHE contributes to: (1) forward secrecy through ephemeral session keys; (2) security through zero-knowledge password proofs (ZKPP), such that no passwords can be learned from the exchange; (3) the ability to use not only location, but also multiple authentication factors from a user to a service; (4) providing a two-tiered privacy authentication scheme, in which a user may be authenticated either based on her attributes (hiding her unique identification), or with a full individual authentication; (5) employing the expressiveness and flexibility of Decentralized or Multi-Authority Ciphertext-Policy Attribute-Based Encryption, allowing multiple service providers to control their respective key generation and attributes.