Strategy for Enhancing the Security of Critical Infrastructure Using Artificial Intelligence

Document Type : Original Article

Authors

1 Master's degree in crisis management, non-operating engineering and defense university complex, Malik Ashtar University of Technology

2 Professor at the Engineering and Passive Defense Academic Complex, Malek Ashtar University of Technology

Abstract

Critical Infrastructure (CI) includes the essential systems, assets, and services that are vital for the functioning and well-being of society and the economy. However, the rapid growth of cyber threats in digital environments poses serious risks to the efficiency of these infrastructures and presents significant challenges to public safety, economic stability, and national security. This growing threat landscape highlights the urgent need for effective cybersecurity solutions, particularly in the domains of automation and intelligent decision-making, where AI-based modeling can play a crucial role. In this regard, our discussion focuses on comparing rule-based artificial intelligence systems, as this approach offers greater transparency, interpretability, and trustworthiness compared to deep learning methods, enabling human analysts to examine and validate decisions—a critical and unavoidable requirement in cybersecurity. This research analyzes multi-layer rule-based AI systems designed to facilitate human-understandable decision-making alongside automated processes in critical infrastructure environments. It also categorizes various rule generation techniques and explores both knowledge-based and data-driven approaches for extracting meaningful insights from data. Such insights empower security analysts to identify threats, investigate attacks, and make informed decisions across various sectors. Furthermore, the study examines how these methods can address cybersecurity challenges in key sectors such as energy, defense, transportation, healthcare, water resources, and agriculture, thereby contributing to the enhancement of security measures. The paper concludes by identifying existing challenges, outlining future research opportunities, and proposing innovative strategies for countering emerging cyber threats.

Keywords

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Passive Defense
Volume 16, Issue 3 - Serial Number 63
Serial number 63. Autumn 2025
October 2025
Pages 1-20

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  • Receive Date: 24 November 2024
  • Revise Date: 18 May 2025
  • Accept Date: 20 September 2025
  • Publish Date: 22 October 2025

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