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336 Tue, 8/9/2022, 2:00 PM - 3:50 PM CC-142
Statistical Modeling and Machine Learning for National Security Applications — Contributed Papers
Section on Statistics in Defense and National Security, Caucus for Women in Statistics, Text Analysis Interest Group
Chair(s): Daniel Ries, Sandia National Labs
2:05 PM Advancements in Characterizing Warhead Fragmentation Events
John Haman, Inst. for Defense Analyses; Thomas Johnson, Inst. for Defense Analyses
2:20 PM Anomaly Detection for Controller Area Network
Kelly Toppin, ICF / US Army ARL; Frederica Nelson, US Army ARL; Nandi Leslie, Raytheon/ US Army ARL
2:35 PM Estimation of Score-Based Likelihood Ratios in the Presence of Covariates, with Application to Forensics and Biometric Recognition
He Qi, George Mason University; Martin Slawski, George Mason University; Larry Tang, University of Central Florida
2:50 PM Malicious URL Detection Using Machine Learning for Security Traffic
Aritra Guha, Data Science & AI Research, AT&T Chief Data Office; Srivathsan Srinivasagopalan, Data Science & AI Research, AT&T Chief Data Office; Mani Subramaniam, Data Science & AI Research, AT&T Chief Data Office
3:05 PM Interpretation of Handwriting Evidence Using Error Rates and Score-Based Likelihood Ratios
Danica Ommen, Iowa State University; Larry Tang, University of Central Florida
3:20 PM Using Risk-Adjusted Measurement Models to Understand the Threat of Ransomware in the U.S
Divya Ramjee, American University
3:35 PM Complex-Valued Signal Denoising for Detection of Synthetic Opioids
Natalie Klein, Los Alamos National Laboratory; Michael Malone, Los Alamos National Laboratory