实时检测新型AI安全威胁，集成日志分析与机器学习
CyberSentinel: An Emergent Threat Detection System for AI Security
- 单智能体系统融合日志分析、黑名单与异常检测
- 可实时识别SSH暴力破解、钓鱼链接及未知攻击
- 适合需要主动防御的AI系统安全团队使用
人工智能的快速发展显著扩大了AI驱动的网络安全威胁攻击面，亟需适应性防御策略。本文提出CyberSentinel，一种统一的单智能体系统，用于实时发现并缓解新兴安全风险。该系统集成三项能力：(1) 通过分析SSH日志检测暴力破解攻击，(2) 利用域名黑名单和启发式URL评分评估钓鱼威胁，(3) 基于机器学习的异常检测实现新兴威胁识别。通过持续适应不断演变的对抗策略，CyberSentinel强化了主动式网络安全防御，有效应对AI安全中的关键漏洞。
原文摘要 · Abstract (English)
The rapid advancement of artificial intelligence (AI) has significantly expanded the attack surface for AI-driven cybersecurity threats, necessitating adaptive defense strategies. This paper introduces CyberSentinel, a unified, single-agent system for emergent threat detection, designed to identify and mitigate novel security risks in real time. CyberSentinel integrates: (1) Brute-force attack detection through SSH log analysis, (2) Phishing threat assessment using domain blacklists and heuristic URL scoring, and (3) Emergent threat detection via machine learning-based anomaly detection. By continuously adapting to evolving adversarial tactics, CyberSentinel strengthens proactive cybersecurity defense, addressing critical vulnerabilities in AI security.
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