Threat Lab Summit

 

Insider Threat Social and Behavioral Sciences Summit 2024: DETECT

 

The Defense Personnel and Security Research Center’s (PERSEREC) Threat Lab is proud to share content from the fifth annual Insider Threat Social and Behavioral Sciences Summit (InT SBS Summit). The 2024 NITAM theme was Deter, Detect, Mitigate. To kick-off NITAM, the InT SBS Summit focused on Detect. Detection is about identifying and investigating signs or actions that could signal an insider threat, using a blend of technology, psychology, and procedural checks.


BELOW ARE SELECT PRESENTATIONS MADE AVAILABLE FOR DOWNLOAD

•    Dr. Michele Borynski, National Geospatial-Intelligence Agency (NGA)
     Spies at Los Alamos Insider Threats at the Manhattan Project (PDF)

•    Dr. Kurt Braddock, American University
     Using Deep Learning Neural Networks to Predict Violent vs. Nonviolent Extremist Behaviors (PDF)

•    Dr. Denise Bulling & Dr. Mario Scalaro, University of Nebraska
     Recent Research in Threat Assessment and Its Application to Insider Threat (PDF)

•    Dr. Deanna Caputo, The MITRE Corporation
     Observable Measures of Psychological Financial Strain (not Debt) (PDF)

•    Dr. James Doodson, The MITRE Corporation
     Data-Driven Cyber Indicators of Malicious Insider Threats on a Live Network (PDF)

•    Dr. William “Chuck” Isler, Air Force Counter-Insider Threat Hub
     Detection and Responding to Red Flags in the Hybrid Workplace (PDF)

•    Mr. Ryan Mayfield, Koshka Foundation
     Why Doesn't Someone Say Something Empowering People to Ask for Help (PDF)

•    Dr. Leissa Nelson, Threat Lab @ PERSEREC
     From Awareness to Expertise Equipping Teams to Detect Insider Threats (PDF)

•    Mr. James Rowley, Yahoo
     Ideation to Proliferation Enabling Insider Teams to Enable Detection Engineers (PDF)

•    Mr. Zachary Taylor, NAVFAC Engineering & Expeditionary Warfare Center
     Opposing Force Advancing Physical Security Through Offensive Security (PDF)

•    Dr. Vincent Verdult, Netherlands Police
     Using Protective Monitoring to Detect and Prevent Misuse of Police Information (PDF)