AI-DRIVEN THREAT INTELLIGENCE FOR REAL-TIME NETWORK SECURITY OPTIMIZATION

Abstract

Artificial Intelligence (AI) revolutionizes network security through advanced threat intelligence and automated response mechanisms. This article investigates the integration of AI-driven frameworks in cybersecurity, examining their impact on threat detection, incident response, and overall security posture. The article demonstrates significant improvements in security operations through a comprehensive analysis of enterprise implementations, including reduced false positives, enhanced threat detection accuracy, and streamlined incident response processes. The article presents a multi-layered framework incorporating data collection, analysis, decision-making, and response components, validated through multiple case studies across financial, healthcare, and e-commerce sectors. The findings highlight how AI-driven security solutions effectively address the limitations of traditional security approaches while introducing new considerations for implementation and optimization.