Exploring Predictive Analytic Threat Assessment Models for Proactive Insider Threat Mitigation

Based on two decades of research, this presentation discusses technical challenges and recent insights in developing and testing behavioral science-based models for proactive insider threat mitigation. Dr. Greitzer describes the SOFIT insider threat indicator ontology, which provides a foundation for hierarchical, pattern-based models; reviews what expert knowledge elicitation studies have revealed about dynamic properties of potential risk indicators; and discusses recent approaches for developing and testing models that reflect how human experts think about and analyze this complex threat assessment problem.