Crisis Management Days

Intelligent Automation Frameworks for Securing Critical Infrastructure During Crisis Events

Igor Znika

Krunoslav Bilić

Jurica Đurić

Keywords: Intelligent Automation, Artificial Intelligence, Critical Infrastructure Protection, Crisis Management, Cyber-Physical Systems, Risk Mitigation, Predictive Analytics, Incident Response, Operational Resilience, Security Governance

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Abstract

Safeguarding essential services such as energy, transportation, healthcare, and communication systems is becoming a greater challenge during crisis events. By integrating artificial intelligence with automated operational processes, these frameworks enable real-time monitoring, anomaly detection, and rapid response to both cyber and physical threats. In highly complex and distributed environments, intelligent automation reduces dependence on manual intervention and enhances the speed and accuracy of incident handling. The incorporation of predictive analytics and machine learning models allows organizations to anticipate potential disruptions, assess vulnerabilities, and proactively implement mitigation strategies. Furthermore, such frameworks support coordinated responses across multiple stakeholders, including government agencies, private sector operators, and emergency services. A key aspect of these systems is their ability to ensure operational continuity through redundancy, fault tolerance, and automated recovery mechanisms. They also contribute to improved situational awareness by aggregating and analyzing data from diverse sources in real time. Ensuring compliance with security regulations and protecting sensitive data are essential components of these frameworks. Additionally, ethical considerations and trust in automated decision-making processes must be addressed to ensure acceptance and reliability. Overall, intelligent automation enhances the resilience, adaptability, and security of critical infrastructure in the face of increasingly complex crisis scenarios.