EXP-LA: Deceit Indication Through Person Specific Behavioral Dynamics

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One of the most important goals for our military and homeland security personnel is to catch people who are planning to attack our military and civilian facilities before they strike. This project proposes to identify, interpret, and develop procedures for automatically measuring the types of behavioral clues exhibited by people who intend on attacking, particularly when they attempt to conceal or fabricate their true intentions. Although research has shown that there is no one signal or behavior that reveals whether a person is concealing his or her intentions or telling a lie, researchers agree that most behavioral clues to deceit are person specific, which require determining a baseline reading of the person's normal behavior and calibrating changes from that baseline. This project improves on prior research because it will examine behaviors that are elicited in more realistic, high stake scenarios, and will do it without attaching any instruments to the person, while applying automatic machine learning systems to take each indicator behavior and identify which changes are best able to identify a person as truthful or lying. This procedure will then produce a prototype that examines video of both checkpoint and 'sit down' interrogation sessions and automatically produces a single integrated score of deception/malfeasance likelihood. The broader impact of this project is that it will bring together behavioral, computer, and engineering scientists to apply their state of the art tools to creating a system with the potential for identifying a potential terrorist before he or she attacks. The synergy generated by this rare combination of skills and knowledge between the researchers will advance knowledge not only in this specific topic but also in areas of research such as social psychology, computer vision and automatic machine learning. Finally, this project will maintain this synergy momentum by training future generations of not only Ph.D. and Postdoctoral students, but will also be applied to ongoing counter-terrorism training programs.