Countermeasures and Eye Tracking Deception Detection

A new development in the field of deception detection is been the development of rapid, noncontact tools for automated detection. This research in progress paper describes a method for assessing the robustness of eye tracker-based deception detection to countermeasures employed by knowledgeable participants

Eye Gazing Behaviors in Online Deception

Psychophysiological behaviors of deceivers have been used as an effective leakage channel of face-to-face deception. Among various psychophysiological behaviors, eye movement has been identified as one of the most reliable sources of deception behavior in face-to-face communication. However, empirical studies of eye movement behavior in online deception remain scarce. In this research, we investigated eye gazing behaviors of deceivers in online video chatting. Based on the findings of previous deception studies and the unique characteristics of online video chatting, we hypothesized that online deception has an impact on eye gazing behaviors. In addition, we innovatively operationalized eye gazing behaviors in terms of areas of interest. We conducted a lab-based experiment to test the hypotheses. The results supported the effect of deception on eye gazing behaviors. The findings of this study provide insights on how to improve the performance of online deception detection and how to apply eye tracking technologies to understand emerging human behaviors in online communication

The Viability of Using Rapid Judgments as a Method of Deception Detection

Rapid Judgments (RJs) are quick assessments based on indirect verbal and nonverbal cues that are known to be associated with deception. RJs are advantageous because they eliminate the need for expensive detection equipment and only require minimal training for coders with relatively accurate judgments. Results of testing on two different datasets showed that trained coders were reliably making RJs after watching both long and short interaction segments but their judgments were not more accurate than the expert interviewers. The RJs did not discriminate between truth and deception as hypothesized. This raises more questions about the conditions under which making RJs from verbal and nonverbal cues achieves accurate detection of veracity.18 month embargo; published online: 25 January 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Leader Member Exchange: An Interactive Framework to Uncover a Deceptive Insider as Revealed by Human Sensors

This study intends to provide a theoretical ground that conceptualizes the prospect of detecting insider threats based on leader-member exchange. This framework specifically corresponds to two propositions raised by Ho, Kaarst-Brown et al. [42]. Team members that are geographically co-located or dispersed are analogized as human sensors in social networks with the ability to collectively “react” to deception, even when the act of deception itself is not obvious to any one member. Close interactive relationships are the key to afford a network of human sensors an opportunity to formulate baseline knowledge of a deceptive insider. The research hypothesizes that groups unknowingly impacted by a deceptive leader are likely to use certain language-action cues when interacting with each other after a leader violates group trust

Establishing a Foundation for Automated Human Credibility Screening

Automated human credibility screening is an emerging research area that has potential for high impact in fields as diverse as homeland security and accounting fraud detection. Systems that conduct interviews and make credibility judgments can provide objectivity, improved accuracy, and greater reliability to credibility assessment practices, need to be built. This study establishes a foundation for developing automated systems for human credibility screening

Design Principles for Special Purpose, Embodied, Conversational Intelligence with Environmental Sensors (SPECIES) Agents

As information systems increase their ability to gather and analyze data from the natural environment and as computational power increases, the next generation of human-computer interfaces will be able to facilitate more lifelike and natural interactions with humans. This can be accomplished by using sensors to non-invasively gather information from the user, using artificial intelligence to interpret this information to perceive users’ emotional and cognitive states, and using customized interfaces and responses based on embodied-conversational-agent (avatar) technology to respond to the user. We refer to this novel and unique class of intelligent agents as Special Purpose Embodied Conversational Intelligence with Environmental Sensors (SPECIES) agents. In this paper, we build on interpersonal communication theory to specify four essential design principles of all SPECIES agents. We also share findings of initial research that demonstrates how SPECIES agents can be deployed to augment human tasks. Results of this paper organize future research efforts in collectively studying and creating more robust, influential, and intelligent SPECIES agents

Sleight of Hand: Identifying Concealed Information by Monitoring Mouse-Cursor Movements

Organizational members who conceal information about adverse behaviors present a substantial risk to that organization. Yet the task of identifying who is concealing information is extremely difficult, expensive, error-prone, and time-consuming. We propose a unique methodology for identifying concealed information: measuring people’s mouse-cursor movements in online screening questionnaires. We theoretically explain how mouse-cursor movements captured during a screening questionnaire differ between people concealing information and truth tellers. We empirically evaluate our hypotheses using an experiment during which people conceal information about a questionable act. While people completed the screening questionnaire, we simultaneously collected mouse-cursor movements and electrodermal activity—the primary sensor used for polygraph examinations—as an additional validation of our methodology. We found that mouse-cursor movements can significantly differentiate between people concealing information and people telling the truth. Mouse-cursor movements can also differentiate between people concealing information and truth tellers on a broader set of comparisons relative to electrodermal activity. Both mouse-cursor movements and electrodermal activity have the potential to identify concealed information, yet mouse-cursor movements yielded significantly fewer false positives. Our results demonstrate that analyzing mouse-cursor movements has promise for identifying concealed information. This methodology can be automated and deployed online for mass screening of individuals in a natural setting without the need for human facilitators. Our approach further demonstrates that mouse-cursor movements can provide insight into the cognitive state of computer users

Automated Human Screening for Detecting Concealed Knowledge

Screening individuals for concealed knowledge has traditionally been the purview of professional interrogators investigating a crime. But the ability to detect when a person is hiding important information would be of high value to many other fields and functions. This dissertation proposes design principles for and reports on an implementation and empirical evaluation of a non-invasive, automated system for human screening. The screening system design (termed an automated screening kiosk or ASK) is patterned after a standard interviewing method called the Concealed Information Test (CIT), which is built on theories explaining psychophysiological and behavioral effects of human orienting and defensive responses. As part of testing the ASK proof of concept, I propose and empirically examine alternative indicators of concealed knowledge in a CIT. Specifically, I propose kinesic rigidity as a viable cue, propose and instantiate an automated method for capturing rigidity, and test its viability using a traditional CIT experiment. I also examine oculomotor behavior using a mock security screening experiment using an ASK system design. Participants in this second experiment packed a fake improvised explosive device (IED) in a bag and were screened by an ASK system. Results indicate that the ASK design, if implemented within a highly controlled framework such as the CIT, has potential to overcome barriers to more widespread application of concealed knowledge testing in government and business settings