An Empirical Exploration of Countermeasures in HCI-Based Deception Research
AuthorByrd, Michael David
Psycho-Physiological Deception Detection
Attentional Control Theory
Signal Detection Theory
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractThis paper addresses three objectives: first, the extent of the theoretical understanding of countermeasures that is present in the deception detection literature to date was mapped out by conducting a literature review of countermeasures related work in the deception detection discipline. Second, after evaluating and analyzing this literature, Signal Detection Theory (SDT) was leveraged to generate an enhanced and extended theory-based framework for countermeasures. Third, an experiment was designed and conducted to explore the implications of this theory-based framework in the context of an HCI-based deception detection system based on tracking mouse movements and Attentional Control Theory (ACT) in an empirical experiment. The experiment was designed to learn more about what happens when users are aware they are being monitored and identify potential ways to mitigate any such countermeasures they may employ. In the experiment, participants were able to decide to perform and unsanctioned malicious act. In addition, we were able to definitively establish the ground truth about their behavior without imposing monitoring that was too overly invasive to the point of discouraging them from performing the malicious act. Mouse tracking was then used to attempt to detect who chose to perform the act, in a manner similar to how such a system would be deployed in practice. We manipulated the level of user awareness of the tracking and trained the users in strategies that can function as countermeasures to detection. Our analysis let us see how effective the system is at the varying levels of awareness and explore explanations and data analysis techniques to detect and mitigate the countermeasures. Results are discussed and considerations for future research are presented.
Degree ProgramGraduate College
Management Information Systems
Degree GrantorUniversity of Arizona
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