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

月光博客
月光博客
Stack Overflow Blog
Stack Overflow Blog
L
LangChain Blog
Jina AI
Jina AI
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
雷峰网
雷峰网
T
Tailwind CSS Blog
MongoDB | Blog
MongoDB | Blog
博客园 - 【当耐特】
博客园 - 聂微东
V
Visual Studio Blog
博客园_首页
Engineering at Meta
Engineering at Meta
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
The Cloudflare Blog
人人都是产品经理
人人都是产品经理
Apple Machine Learning Research
Apple Machine Learning Research
阮一峰的网络日志
阮一峰的网络日志
Microsoft Security Blog
Microsoft Security Blog
GbyAI
GbyAI
F
Fortinet All Blogs
C
Check Point Blog
罗磊的独立博客
H
Hackread – Cybersecurity News, Data Breaches, AI and More

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
SEDAT:Security Enhanced Device Attestation with TPM2.0
Avani Dave, Monty Wiseman, David Safford · 2021-01-16 · via cs.CR updates on arXiv.org

Remote attestation is one of the ways to verify the state of an untrusted device. Earlier research has attempted remote verification of a devices' state using hardware, software, or hybrid approaches. Majority of them have used Attestation Key as a hardware root of trust, which does not detect hardware modification or counterfeit issues. In addition, they do not have a secure communication channel between verifier and prover, which makes them susceptible to modern security attacks. This paper presents SEDAT, a novel methodology for remote attestation of the device via a security enhanced communication channel. SEDAT performs hardware, firmware, and software attestation. SEDAT enhances the communication protocol security between verifier and prover by using the Single Packet Authorization (SPA) technique, which provides replay and Denial of Service (DoS) protection. SEDAT provides a way for verifier to get on-demand device integrity and authenticity status via a secure channel. It also enables the verifier to detect counterfeit hardware, change in firmware, and software code on the device. SEDAT validates the manufacturers` root CA certificate, platform certificate, endorsement certificate (EK), and attributes certificates to perform platform hardware attestation. SEDAT is the first known tool that represents firmware, and Integrity Measurement Authority (IMA) event logs in the Canonical Event Logs (CEL) format (recommended by Trusted Computing Group). SEDAT is the first implementation, to the best of our knowledge, that showcases end to end hardware, firmware, and software remote attestation using Trusted Platform Module (TPM2.0) which is resilient to DoS and replay attacks. SEDAT is the first remote verifier that is capable of retrieving a TPM2.0 quote from prover and validate it after regeneration, using a software TPM2.0 quote check.