THE ROLE OF ARTIFICIAL INTELLIGENCE IN CYBERSECURITY: THREATS, DEFENSE MECHANISMS, AND FUTURE PERSPECTIVES

Abstract

This paper examines the transformative impact of artificial intelligence (AI) on cybersecurity systems and practices. As cyber threats become increasingly sophisticated and automated, traditional security measures are proving inadequate. AI-powered cybersecurity solutions offer enhanced threat detection, automated response mechanisms, and predictive analytics that significantly improve organizational security postures. This study explores the integration of machine learning, deep learning, and neural networks into cybersecurity frameworks, analyzing their applications in intrusion detection, malware analysis, phishing prevention, and behavioral analytics. The research also addresses the dual-edged nature of AI in cybersecurity, where the same technologies used for defense can be weaponized by malicious actors. Key challenges including adversarial AI, algorithmic bias, false positives, and the skills gap in AI-cybersecurity expertise are thoroughly discussed. The findings demonstrate that organizations implementing AI-driven security systems experience faster threat detection, reduced response times, and improved overall security effectiveness, though success requires careful implementation, continuous model training, and human oversight.