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

I
InfoQ
G
Google Developers Blog
Engineering at Meta
Engineering at Meta
月光博客
月光博客
博客园 - 聂微东
博客园 - Franky
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
有赞技术团队
有赞技术团队
A
About on SuperTechFans
Microsoft Azure Blog
Microsoft Azure Blog
Blog — PlanetScale
Blog — PlanetScale
U
Unit 42
T
Tailwind CSS Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
云风的 BLOG
云风的 BLOG
S
SegmentFault 最新的问题
F
Fortinet All Blogs
H
Help Net Security
J
Java Code Geeks
酷 壳 – CoolShell
酷 壳 – CoolShell
博客园 - 叶小钗
L
LangChain Blog
Martin Fowler
Martin Fowler
N
Netflix TechBlog - Medium

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
When Autonomous Intelligent Goodware will Fight Autonomou...
Paul Théron, Alexander Kott · 2019-11-26 · via cs.CR updates on arXiv.org

In the coming years, the future of military combat will include, on one hand, artificial intelligence-optimized complex command, control, communications, computers, intelligence, surveillance and reconnaissance (C4ISR) and networks and, on the other hand, autonomous intelligent Things fighting autonomous intelligent Things at a fast pace. Under this perspective, enemy forces will seek to disable or disturb our autonomous Things and our complex infrastructures and systems. Autonomy, scale and complexity in our defense systems will trigger new cyber-attack strategies, and autonomous intelligent malware (AIM) will be part of the picture. Should these cyber-attacks succeed while human operators remain unaware or unable to react fast enough due to the speed, scale or complexity of the mission, systems or attacks, missions would fail, our networks and C4ISR would be heavily disrupted, and command and control would be disabled. New cyber-defense doctrines and technologies are therefore required. Autonomous cyber defense (ACyD) is a new field of research and technology driven by the defense sector in anticipation of such threats to future military infrastructures, systems and operations. It will be implemented via swarms of autonomous intelligent cyber-defense agents (AICAs) that will fight AIM within our networks and systems. This paper presents this cyber-defense technology of the future, the current state of the art in this field and its main challenges. First, we review the rationale of the ACyD concept and its associated AICA technology. Then, we present the current research results from NATO's IST-152 Research Task Group on the AICA Reference Architecture. We then develop the 12 main technological challenges that must be resolved in the coming years, besides ethical and political issues.