关键基础设施保护的生成AI和LLM:评估基准,代理AI,挑战和机遇
Yagmur Yigit1, Mohamed Amine Ferrag2, Mohamed C Ghanem3,4
1School of Computing, Engineering and the Built Environment, Edinburgh Napier University, 10 Colinton Road, Edinburgh EH10 5DT, UK.
Sensors (Basel, Switzerland)
|April 28, 2025
概括
人工智能 (AI) 增强了对网络威胁的关键国家基础设施 (CNI) 保护. 本综述探讨了人工智能,包括大型语言模型 (LLM),以确保重要系统的安全,并概述了未来的人工智能集成策略.
科学领域:
- 网络安全 网络安全
- 人工智能的人工智能
- 关键国家基础设施保护保护
背景情况:
- 国家关键基础设施 (CNI) 对社会至关重要,但易受网络威胁的影响.
- 现有的网络安全措施需要加强,以应对复杂的威胁.
- 国家标识符的可靠性和安全性对国家稳定至关重要.
研究的目的:
- 综合分析人工智能驱动的关键基础设施保护 (CIP) 方法.
- 评估大型语言模型 (LLM) 和生成AI在增强CIP中的作用.
- 为将先进的人工智能纳入国家基础设施安全提供战略路线图.
主要方法:
- 对当前应用于网络安全的AI方法的审查.
- 检查评估网络安全中的大型语言模型 (LLM) 的基准.
- 分析核心网络安全问题:信任,隐私,NNI的弹性和可靠性.
主要成果:
- 生成性AI和LLM显示出在加强CIP方面的巨大潜力.
- 代理人工智能为主动防御机制提供了有前途的途径.
- 确立的基准对于评估AI工具在网络安全中的可靠性至关重要.
结论:
- 先进的AI方法对于加强国家基础设施以应对新出现的网络威胁至关重要.
- 建议对未来的CIP进行人工智能的战略整合,包括LLM和AgenticAI.
- 需要进一步的研究来指导人工智能在保护关键国家基础设施方面的有效实施.
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