Self-Healing AI-Driven Networks for Automated Cyber Threat Detection and Recovery

Modern networked systems are increasingly vulnerable to sophisticated cyberattacks that compromise operational integrity, disrupt services, and create economic and reputational losses. Traditional recovery approaches are often manual, slow, and insufficient for the scale of cloud and edge environments. This paper presents an architecture for self-healing networks that detect, diagnose, and recover from cyber-induced disruptions using AI-driven root-cause analysis and automated remediation workflows.

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