Large Language Models in Autonomous Cyber-Defense: Proactive Threat Mitigation and Response

This paper presents a framework for integrating large language models into existing cybersecurity infrastructures. By training models on extensive intrusion detection datasets and leveraging their reasoning capabilities, we demonstrate a 25% increase in threat detection accuracy and a 50% reduction in incident response time compared to traditional rule-based systems.