Harnessing AI for Insider Threat Detection: Strategies for Proactive Mitigation in Corporate Networks

Abstract

Insider threats pose significant challenges to corporate networks, often leading to data breaches and financial losses. Traditional detection methods, while useful, often fail to identify these threats in a timely manner. This paper explores the role of artificial intelligence (AI) in enhancing insider threat detection and mitigation strategies. By leveraging advanced AI techniques, organizations can proactively monitor user behavior, identify anomalies, and reduce the risk of insider threats. Key strategies discussed include behavioral analysis, machine learning models, continuous monitoring, risk assessment, and employee training. The paper also addresses the challenges and ethical considerations associated with implementing AI in this context, ultimately highlighting the importance of a proactive approach to insider threat management.