Behavioral Intelligence at Scale: Implementing UEBA for Enhanced Security Posture

Kumrashan Indranil Iyer

Abstract: In today?s digital era, where data holds immense value and the internet spans globally, the proliferation of digital transactions and assets has imposed greater security responsibilities on technology companies and financial institutions. Simultaneously, the exponential advancement of artificial intelligence (AI) has introduced a dual-use technology that, if exploited by cybercriminals, can significantly undermine cybersecurity. Traditional signature-based defense mechanisms are increasingly inadequate against evolving threats, positioning User and Entity Behavior Analytics (UEBA) as a vital component in modern cybersecurity frameworks. By identifying deviations from baseline user and device behavior, UEBA solutions enhance the detection of anomalous and malicious activities that often bypass conventional defenses. This paper presents a comprehensive analysis of UEBA?s role in fortifying enterprise cybersecurity, detailing its architectural design, deployment strategies, and integration within contemporary environments. Furthermore, the paper addresses the challenges of large-scale UEBA implementation and outlines prospective avenues for future research.

Keywords: Cybersecurity, User and Entity Behavior Analytics (UEBA), Artificial Intelligence (AI), Anomaly Detection, Enterprise Security, Threat Detection, Behavioral Analytics, Cyber Threats, Security Architecture, Insider Threat Detection, Insider Threat Analytics