Using AI/ML for threat detection and prevention

Abstract

This paper explores the application of artificial intelligence (AI) and machine learning (ML) technologies in detecting and preventing cybersecurity threats. It reviews AI/ML methodologies, their practical cybersecurity applications, presents real-world case studies illustrating their effectiveness, and outlines existing challenges. The paper emphasizes the importance of continuous model improvement, data quality, adversarial robustness, explainability, and integration into security workflows. The conclusion underlines AI/ML’s transformative potential in cybersecurity, suggesting future trends toward proactive and predictive threat management