用AI实时防御关键基础设施的网络攻击
Autonomous AI-based Cybersecurity Framework for Critical Infrastructure: Real-Time Threat Mitigation
- 结合AI实现漏洞检测、威胁建模与自动修复
- 可应对勒索软件、DoS攻击和高级持续性威胁
- 适合电网、医疗等关键系统安全团队参考
关键基础设施系统（如能源电网、医疗设施、交通网络和供水系统）对社会稳定和经济韧性至关重要。然而，这些系统的日益互联使其面临多种网络威胁，包括勒索软件、拒绝服务（DoS）攻击和高级持续性威胁（APTs）。本文分析了关键基础设施中的网络安全漏洞，重点阐述威胁态势、攻击路径以及人工智能（AI）在缓解风险中的作用。我们提出一种混合AI驱动的网络安全框架，以增强实时漏洞检测、威胁建模与自动化修复能力。本研究还探讨了对抗性AI、合规性要求及系统集成的复杂性。研究结果为提升关键基础设施系统应对新兴网络威胁的安全性与韧性提供了可操作的见解。
原文摘要 · Abstract (English)
Critical infrastructure systems, including energy grids, healthcare facilities, transportation networks, and water distribution systems, are pivotal to societal stability and economic resilience. However, the increasing interconnectivity of these systems exposes them to various cyber threats, including ransomware, Denial-of-Service (DoS) attacks, and Advanced Persistent Threats (APTs). This paper examines cybersecurity vulnerabilities in critical infrastructure, highlighting the threat landscape, attack vectors, and the role of Artificial Intelligence (AI) in mitigating these risks. We propose a hybrid AI-driven cybersecurity framework to enhance real-time vulnerability detection, threat modelling, and automated remediation. This study also addresses the complexities of adversarial AI, regulatory compliance, and integration. Our findings provide actionable insights to strengthen the security and resilience of critical infrastructure systems against emerging cyber threats.
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