West Point Insider Threat Program

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Working Together
to be Safer

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Diverse, Multidisciplinary
Teamwork

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National, DoD, Army,
DHS Partnerships

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Enhancing Knowledge
in Training

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We Work, Relax,
and Have a Good Time

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Our Team…2023

MIROR Journal Summer 2024

Read the Full Issue

CADET MaRS RESEARCH PROJECTS

Cadet 1, 2, 3

Cadet Saleem Ali (Draper Fellowship, NSF Fellowship), COL Lindquist, MAJ Deverill, Dr. Roginski

NATURAL LANGUAGE PROCESSING OF ARMY INSIDER THREAT HUB DATA

This paper presents a case prioritization system that utilizes a deep learning classification model trained on expert evaluated insider threat cases to label cases as “negligible”, “low”, “medium”, or “high” threat level. This classification model enables a partnership between machine and human that focuses human effort for the greatest impact.

Cadet Joshua Blackmon (GEM Scholarship), Dr. Roginski, Dr. Wolf, AAG RFL

INSIDER THREAT:
CRIMINAL RECIDIVISM

This research delves into the relationship between criminal recidivism and insider threat risk, particularly within the U.S. Army. The methodology employed in this research focused on machine learning techniques but now emphasizes Generalized Linear Models (GLMs), to analyze the data and identify predictors of recidivism, which we then relate to Insider Threat.

Cadet Sydney Watson, Dr. Roginski, LTC Moore, Dr. Babin, Army University

PARTICIPATION OF WOMEN IN THE WORKFORCE: AN INDICATOR OF INVISIBLE BARRIERS

A study attempting to understand the current landscape of women’s participation in the U.S. workforce, in 2022 by examining factors like means of transportation, state, and government assistance. Gaining insight into factors that impact women’s workforce participation serves to better guide policy and inform leaders on how to facilitate an inclusive workplace.

Cadet 4, 5

Cadet Kayla Teuscher, Dr. Roginski, Dr. Hoge (USUH). Maj Donoho & Dr. Wolf (AAG RFL)

THE OCCUPATIONAL BURDEN OF MENTAL HEALTH DISORDERS IN THE U.S. MILITARY

We analyze the Army’s separation landscape from 2008-present for the office of the surgeon general in a way that enables understanding of the mental health diagnosis – readiness relationship so that we improve recruiting and retention to reduce first term attrition, burdens on the health care system, and impact on Army units.

Cadet Samin Kim, LTC Nelson, Dr. Roginski, Dr. Horio, LMI

DATA FUSION ENTERPRISE: BUILD AN ARCHITECTURE FOR AUTOMATING HUB PROCESSES

This research provides a comprehensive proof of concept for automating hub processing in the Insider Threat Hub by developing a pipeline that harmonizes sensor-based decision support for soldiers in battlefield conditions. The model ingests data from several wearable technology stream for real-time health monitoring, analogous to hub processes ingesting disparate data streams for analysis and report of Insider risk likelihood.