INMM Annual Meeting
August 2–6, 2026
Austin, Texas
Thank you for your interest in Cogility and the Institute of Nuclear Materials Management Annual Meeting.
Below are materials from the INMM meeting and other related events that can help you stay informed on the latest advancements in insider risk management and to learn more about Cogility.
Cogility Insider Risk Management and Threat Assessment Resources
Miss the sessions? See the descriptions and materials below.
Presentation: Behavioral Analytic Modeling for Insider Threat Assessment and Mitigation in the Nuclear Power Industry
Speakers: Frank L. Greitzer, PhD, Cogility & Christine F. Noonan, PNNL
This technical presentation and associated paper explain why the nuclear sector is uniquely vulnerable — insider access, IT/OT convergence, and safety-critical operations — and why traditional controls and siloed, reactive programs fall short. Presenting the argument that insider risk and cybersecurity defense are as much human factors issues as technical ones, the presentation reviews the SOFIT knowledge base of psychosocial and technical insider risk indicators and describes the Cogynt.ai Expert AI behavioral analytics platform, which delivers a powerful insider risk management solution that is explainable by design, unlike other AI/machine-learning "black box" approaches.
Presentation: Trusted AI Decision Intelligence Support for Nuclear Material Accountability and Control
Speaker: Frank L. Greitzer, PhD, Cogility
This Lightning talk and associated paper argue that despite strong technical safeguards, nuclear Material Control & Accountability programs remain exposed to human-centric insider risks — theft, diversion, sabotage, and error — that evade early detection. Drawing on cases like San Onofre and SL-1, it presents Cogility's approach: fusing technical, behavioral, and organizational indicators through the SOFIT taxonomy and Cogynt.ai's HCEP engine into explainable, auditable decision support that improves early detection and reduces false positives.
More Resources
To learn more, the buttons below will help you navigate to various resources and presentations on related topics that are available in the Cogility Resource Center, blog articles, and training videos.
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Cogynt.ai provides a fundamentally different approach to detecting and countering insider threat risk. Other solutions primarily rely on user activity monitoring, which primarily reveals only technical risk indicators, failing to provide a comprehensive “whole person” picture of risk. In contrast, Cogynt.ai takes a holistic approach, ingesting and analyzing both technical and behavioral indicators of risk, and then mapping and weighting these risk indicators to insider risk behaviors to create a whole-person risk profile. This provides greater contextual insight that enables a more accurate, proactive risk mitigation approach to get “left of harm.”
Please contact us if you’re interested in piloting Cogynt.ai.