AI-Augmented Cyber Resilience in Critical Infrastructures: Implementing Automated Threat Recovery Mechanisms
Keywords:
cyber resilience, artificial intelligence, critical infrastructures, threat recoveryAbstract
The increasing digitization of critical infrastructures, such as energy grids, healthcare systems, and transportation networks, has amplified their vulnerability to cyber threats. Traditional defense mechanisms often fall short in addressing the complexity and velocity of modern cyberattacks. This paper explores the implementation of AI-augmented automated threat recovery mechanisms to bolster cyber resilience in critical infrastructures. These mechanisms leverage machine learning, anomaly detection, and predictive analytics to detect, respond to, and recover from cyber incidents with minimal human intervention. The study highlights key technologies, case studies, challenges, and future directions in integrating AI-driven solutions into critical systems. By ensuring rapid recovery and minimizing downtime, these mechanisms hold promise for safeguarding essential services against evolving cyber threats.
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