Hunting the Invisible: Harnessing UEBA to Unmask Insider Threats
Subhash Parimalla, Chelumala Sreshta, M. Haarika, Ch. Sowmya, Adiba Sania, Y. Leela Vaishnavi · IntechOpen eBooks · 2025
Insider threats pose a major threat to most organizations. It usually avoids all types of traditional cybersecurity controls and defenses. In this chapter, “Hunting the Invisible: Harnessing UEBA to Unmask Insider Threats,” focus will be given on where AI, machine learning, and User and Entity Behavior Analytics (UEBA) are completely changing the mechanism of detection of insider threats. UEBA identifies real-time anomalous user behavior that signature-based systems miss. The chapter would discuss the kind of behavioral data that is analyzed by UEBA as well as the development of AI and machine learning in helping continuously improve detection. Using case studies in finance and healthcare, it explains the preventive activities regarding insider attacks and gives an overview of future roles of UEBA as an analytics tool and emerging strategy in security.