2024 International Symposium on Insider Threat Mitigation

March 5–7, 2024
Brussels, Belgium

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Exploring Predictive Analytic Threat Assessment Models

Based on two decades of research on insider threats, the 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.

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Cogynt provides a fundamentally different approach to detecting and countering insider threat risk. Other solutions primarily rely on user activity monitoring, which only provides half of the picture since this approach discovers technical indicators of risk only. Cogynt by contrast takes a whole-person approach to detecting risks by ingesting both technical and social indicators of risk, mapping and weighting these risk indicators to behaviors, and creating a whole-person profile.


By taking this approach, Cogynt allows organizations to have a more accurate and holistic picture of insider threat risks - providing a window of opportunity to get left of harm.


Please contact us if you’re interested in piloting Cogynt.

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