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Generative AI and LLMs for Critical Infrastructure Protection: Evaluation Benchmarks, Agentic AI, Challenges, and

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This summary is machine-generated.

Artificial intelligence (AI) enhances critical national infrastructure (CNI) protection against cyber threats. This review explores AI, including Large Language Models (LLMs), for securing vital systems and outlines future AI integration strategies.

Keywords:
critical infrastructure protectioncritical national infrastructurereliabilitysecurity

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Area of Science:

  • Cybersecurity
  • Artificial Intelligence
  • Critical National Infrastructure Protection

Background:

  • Critical National Infrastructures (CNIs) are vital for society but vulnerable to cyber threats.
  • Existing cybersecurity measures require enhancement to address sophisticated threats.
  • The reliability and security of CNIs are paramount for national stability.

Purpose of the Study:

  • To comprehensively analyze AI-driven approaches for Critical Infrastructure Protection (CIP).
  • To evaluate the role of Large Language Models (LLMs) and Generative AI in enhancing CIP.
  • To provide a strategic roadmap for integrating advanced AI into national infrastructure security.

Main Methods:

  • Review of current AI methodologies applied to cybersecurity.
  • Examination of benchmarks for evaluating Large Language Models (LLMs) in cybersecurity.
  • Analysis of core cybersecurity issues: trust, privacy, resilience, and securability in CNIs.

Main Results:

  • Generative AI and LLMs show significant potential in bolstering CIP.
  • Agentic AI offers promising avenues for proactive defense mechanisms.
  • Established benchmarks are crucial for assessing AI tool reliability in cybersecurity.

Conclusions:

  • Advanced AI methodologies are essential for fortifying national infrastructures against emerging cyber threats.
  • A strategic integration of AI, including LLMs and Agentic AI, is recommended for future CIP.
  • Further research is needed to guide the effective implementation of AI in protecting critical national infrastructures.