A Review of Recent Advances, Challenges, and Opportunities in Malicious Insider Threat Detection Using Machine Learning Methods

Insider threat detection has become a paramount concern in modern times where organizations strive to safeguard their sensitive information and critical assets from malicious actions by individuals with privileged access. This survey paper provides a comprehensive overview of insider threat detection, highlighting its significance in the current landscape of cybersecurity. The review encompasses a broad spectrum of methodologies and techniques, with a particular focus on classical machine-learning approaches and their limitations in effectively addressing the intricacies of insider threats. Furthermore, the survey explores the utilization of modern deep learning and natural language processing (NLP) based…