The Role of Artificial Intelligence in Safeguarding Critical National Infrastructure against Cyberattacks

Abstract

The increasing digitalization of critical national infrastructure has significantly expanded the cyber threat surface of essential sectors such as energy, water, transportation, healthcare, and finance. Traditional rule-based and signature-driven cybersecurity mechanisms are increasingly inadequate against sophisticated, adaptive, and stealthy cyberattacks targeting industrial control systems and operational technology environments. This article examines the role of artificial intelligence (AI) as a strategic enabler for safeguarding critical national infrastructure against evolving cyber threats. The study adopts a structured narrative review approach, synthesizing peer reviewed literature, empirical case studies, and internationally recognized cybersecurity standards to evaluate how AI-driven techniques enhance threat detection, prediction, and response capabilities. The analysis focuses on machine learning and deep learning applications in intrusion detection, anomaly detection, predictive analytics, and automated incident response within cyber-physical and industrial control systems (Bhamare et al., 2020; Umer et al., 2022).  Key findings indicate that AI-based cybersecurity solutions significantly improve detection accuracy, reduce response latency, and enable proactive defense by identifying previously unknown attack patterns (Sowmya & Anita, 2023). However, the study also highlights critical limitations, including data quality challenges, adversarial manipulation of AI models, explainability concerns, and integration difficulties with legacy infrastructure (Biggio & Roli, 2018; Papernot et al., 2017). The article further discusses governance and policy implications, emphasizing the alignment of AI-enabled cybersecurity with established frameworks such as the NIST Cybersecurity Framework and Zero Trust Architecture (Rose et al., 2020; NIST, 2024). The study contributes to existing literature by providing a consolidated perspective on AI-driven protection strategies for critical national infrastructure and identifying priority areas for future research and policy development.