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

V
V2EX
小众软件
小众软件
GbyAI
GbyAI
B
Blog RSS Feed
月光博客
月光博客
A
About on SuperTechFans
Microsoft Security Blog
Microsoft Security Blog
Blog — PlanetScale
Blog — PlanetScale
U
Unit 42
云风的 BLOG
云风的 BLOG
P
Proofpoint News Feed
Recent Announcements
Recent Announcements
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Vercel News
Vercel News
F
Fortinet All Blogs
Apple Machine Learning Research
Apple Machine Learning Research
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
雷峰网
雷峰网
Google DeepMind News
Google DeepMind News
MongoDB | Blog
MongoDB | Blog
Engineering at Meta
Engineering at Meta
aimingoo的专栏
aimingoo的专栏
博客园_首页
G
Google Developers 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
Zero Trust Architecture: A Systematic Literature Review
Muhammad Liman Gambo, Ahmad Almulhem · 2025-02-07 · via cs.CR updates on arXiv.org

The increasing complexity of digital ecosystems and evolving cybersecurity threats have highlighted the limitations of traditional perimeter-based security models, leading to the growing adoption of Zero Trust Architecture (ZTA). ZTA operates on the principle of "never trust, always verify", enforcing continuous authentication, conditional access, dynamic trust evaluation, and the principle of least privilege to enhance security across diverse domains. This study applies the PRISMA framework to analyze 10 years of research (2016-2025) on ZTA, presenting a systematic literature review (SLR) that synthesizes its applications, enabling technologies, and associated challenges. It provides a detailed taxonomy that organizes ZTA's application domains, together with the emerging technologies that facilitate its implementation, and critically examines the barriers to ZTA adoption. Additionally, the study traces the historical evolution of ZTA alongside notable events and publications trends while highlighting some potential factors for the surge over the past few years. This comprehensive analysis serves as a practical guide for researchers and practitioners seeking to leverage ZTA for stronger, more adaptive security frameworks in a rapidly shifting threat landscape.