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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A cultural model of nonverbal deceptive communication: The independent and interdependent self-construals as predictors of deceptive communication motivation and nonverbal behaviors under deceptionKim, Min-Sun; Kam, Karadeen Y. (The University of Arizona., 2003)Findings from a host of prior cross-cultural studies suggest that those of differing cultural orientations are likely to possess differing motivations for deceiving and truthtelling, and as a consequence, are likely to exhibit differing patterns of behavior when engaging in deceptive communication. Thus, this investigation examined: (a) the impact of cultural identity on one's motivation for deceptive communication, and (b) the impact of cultural orientation on overt manifestations of behavior. In addition, this study investigated the effects of culture and relational familiarity (i.e., strangers versus friends) on truth bias and deception detection accuracy. To test the proposed theoretical relationships, participants from two cultures (i.e., United States and Japan) were employed in an experimental study. Results of the current investigation revealed that degree of independence was the single best predictor of one's motivation to tell the truth and one's motivation to protect the self, whereas degree of interdependence was the best predictor of one's motivation to protect the other. In terms of deceivers'/truthtellers' perceptions of the self under deception, higher interdependence scores were found to be related to self-perceptions of less positive affect, less fluency, and less psychological involvement under truth conditions, but were associated with greater positive affect, greater fluency, and more psychological involvement under conditions of deception. When considering partner perceptions of truthtellers'/deceivers' behavior, higher degrees of independence were found to be associated with less positive affect under deception. When outside-observers viewed the behaviors of truthtellers/deceivers, higher degrees of independence were found to be associated with greater kinesic involvement and pleasantness, less nervousness, and greater vocal pleasantness and vocal relaxation under truth. Conversely, higher scores on independence were found to be related to less kinesic involvement, less pleasantness, greater nervousness, and less vocal pleasantness and vocal relaxation under conditions of deception. Finally, relationship type was not found to be a significant predictor of either accuracy or truth bias, although, higher degrees of interdependence were associated with lower detection accuracy and greater truth bias. The findings of the current investigation strongly suggest that behavioral differences indeed become manifest when research is conducted employing samples of varying cultural orientations.
Augmenting Human Intellect: Automatic Recognition of Nonverbal Behavior with Application in Deception DetectionNunamaker, Jr., Jay F.; Burgoon, Judee K.; Meservy, Thomas Oliver; Nunamaker, Jr., Jay F.; Burgoon, Judee K.; Fong, Sandiway; Kruse, W. John (The University of Arizona., 2007)Humans have long sought to use technology to augment human abilities and intellect. However, technology is traditionally employed only to create speedier solutions or more-rapid comprehension. A more challenging endeavor is to enable humans with technology to gain additional or enhanced comprehension that may not be possible to acquire otherwise. One such application is the use of technology to augment human abilities in detecting deception using nonverbal cues. Detecting deception is often critical, whether an individual is communicating with a close friend, negotiating a business deal, or screening individuals at a security checkpoint.The detection of deception is a challenging endeavor. A variety of studies have shown that humans have a hard time accurately discriminating deception from truth, and only do so slightly better than chance. Several deception detection methods exist; however, most of these are invasive and require a controlled environment.This dissertation presents a technological approach to detecting deception based on kinesic (i.e., movement-based) and vocalic (i.e., sounds associated with the voice) cues that is firmly grounded in deception theory and past empirical studies. This noninvasive approach overcomes some of the weaknesses of other deception detection methods as it can be used in a natural environment without cooperation from the individual of interest.The automatable approach demonstrates potential for increasing humans' ability to correctly identify those who display behaviors indicative of deception. The approach was evaluated using experimental and field data. The results of repeated measures analysis of variance, linear regression and discriminant function analysis suggest that the use of such a system could augment human abilities in detecting deception by as much as 15-25%. While there are a number of technical challenges that need to be addressed before such a system could be deployed in the field, there are numerous environments where it would be potentially useful.
Identification of Reliable Cues for an Automatic Deception Detection SystemNunamaker, Jr., Jay F.; Burgoon, Judee K.; Qin, Tiantian; Nunamaker, Jr., Jay F.; Burgoon, Judee K.; Zhao, J. Leon (The University of Arizona., 2007)An automatic deception detection system (ADDS) is to detect deceptive human behavior with machine extractable evidences (i.e., cues). One of the most prominent challenges for building a ADDS is the availability of reliable cues. This study represents one of the first attempts to address the system's reliability by identifying the set of reliable cues in order to improve the system performance (detection accuracy).This study addresses two critical challenges of existing machine cues, irreproducibility and inconsistency. First, in order to mitigate the irreproducibility, the study introduces a set of machine measurable cues to estimate the commonality of related machine cues. These more reproducible cues are referred to as the macro cues which can be applied for automatic pattern recognition. Second, in order to address the consistency, the study separates cues based on the controllability, and defines the strategic cues as those can easily be manipulated by deceivers during interaction. The strategic cues fluctuate during deception and thus are less consistently reliable as predictors for the ADDS. On the contrary, the nonstrategic cues are more consistent. This study also considers other moderator effects that influencing the ADDS performance: time and the condition of interviewer's immediacy (ERIMD).The macro cues are automatically estimated from the micro cues based on the predefined relational models. The empirical data support the relationship models between macro and micro cues. Results show that macro cues mitigate the irreproducibility problem by reducing the variability in the single cues. However, the results also show that using macro cues as predictors in the discriminant analysis does not perform better than micro cues, and thus imply the needs to adjust weights of important components when constructing the macro cues. In terms of the consistent cues, results show that the nonstrategic cues are relatively more consistent than strategic ones in ADDS performance. Furthermore, the study suggests that particular detection methods must be tailored according to the feature of strategic and nonstrategic cues. The findings have many potential implications. One is to use the macro cues to recognize the dynamic patterns in deceptive behaviors. Specifically, truthtellers increase the certainty, immediacy, and tend to decrease the cognitive load; but deceivers behave the opposite. The other is to rely on the characteristics of strategic cues to manipulate the communication environment to improve the ADDS performance. This concept is also referred to as the Proactive Deception Detection (PDD). In the current study, the interviewer's immediacy is a controllable environment factor for PDD. The high ERIMD increase the system performance because it has higher overhead added to the deceptive behavior to trigger more abnormal cues. In sum, methods and results of this study have multiple impacts in information assurance and human-computer interaction.