Crisis Management Days

Cyber-Physical Resilience: Integrating AI-Driven Threat Detection in Critical National Infrastructure

Jurica Đurić

Igor Znika

Krunoslav Bilić

Aleksandar Skendžić

Keywords: Critical Infrastructure Protection, Artificial Intelligence, Cyber-Physical Systems, National Security, Corporate Resilience, Information Security

---

Abstract

The rapid digitalization and interconnectedness of Critical National Infrastructure (CNI), including power grids, water supplies, and transportation networks, have fundamentally blurred the boundaries between physical and cyber security. This paper examines the evolving landscape of cyber-physical threats targeting CNI and evaluates the integration of Artificial Intelligence (AI) and Machine Learning (ML) as essential components for proactive threat detection and mitigation. By analyzing high-profile incidents, the discussion highlights how failures in corporate information security can cascade into national security crises through service disruption, economic destabilization, and public safety risks. The paper proposes a unified, cross-sector resilience framework centered on risk-based governance, Zero Trust principles, continuous diagnostics, and structured public-private collaboration. It argues that protecting modern CNI requires a strategic shift from primarily reactive defenses to predictive, AI-enabled security operations that reduce attacker dwell time and limit blast radius. The study concludes with actionable recommendations for policymakers and corporate security leaders to strengthen cyber-physical resilience against sophisticated criminal, state-sponsored, and increasingly autonomous threats.