Spotting Faked Identities via Mouse Dynamics Using Complex Questions

Abstract

The increment of criminals, including terrorists, crossing international borders using faked identities is a crucial issue. This paper validates a computerized technique to spot people who declare false identity information. Forty participants were asked to answer complex questions about their identity, clicking with the mouse on the correct alternative response on the computer screen. Half of the participants answered truthfully, while the others were instructed to lie. As long as the subject responded to questions, mouse dynamics were recorded. Because lying is cognitively demanding, liars had fewer cognitive resources available to analyse complex questions and to compute the response. As result, they showed a bad performance in the task compared with truth-tellers, revealing a greater number of errors, slower reaction times and larger mouse trajectories. Different machine learning classifiers were trained by a cross validation procedure, achieving a classification accuracy up to 90% in detecting liars.

Use of mouse-tracking software to detect faking-good behavior on personality questionnaires: an explorative study

“…During the experimental task, the MouseTracker software 25 automatically recorded a number of features relating to the response of the mouse in spatial and temporal terms. Mouse parameters that the literature reported to be the most sensitive to deception detection were collected 5,33,35,47 . Specifically, the following features were captured for each mouse trajectory: The idealized trajectory represented the virtual straight line connecting the starting point to the endpoint (the response label).…”

“…Although RTs recorded by mouse tracking do not necessarily overlap with the RTs registered in the aforementioned studies, the mouse tracking technique has nonetheless proven useful for lie detection 33 . Previous studies [33][34][35] have shown that, when half of a sample answered an autobiographical questionnaire truthfully and the other half answered according to fake profiles that had been learned just prior to testing, honest participants followed the more direct trajectory to the desired answer while fakers showed trajectories that initially converged towards the actual autobiographical information and then switched to the opposite direction to select the relevant alternative.The present study aimed at generating insight into the relationship between different approaches to identifying faking-good behaviour on the underreporting validity scales of two widely used personality questionnaires: the L, K, and S underreporting scales of the MMPI-2 and the Virtuous Responding (VR) scale of the PPI-R. These scales were chosen because they were designed to detect the acknowledgment of uncommon virtues and the tendency to omit negative features of personality in order to present oneself in a better light.…”

“…Although RTs recorded by mouse tracking do not necessarily overlap with the RTs registered in the aforementioned studies, the mouse tracking technique has nonetheless proven useful for lie detection 33 . Previous studies [33][34][35] have shown that, when half of a sample answered an autobiographical questionnaire truthfully and the other half answered according to fake profiles that had been learned just prior to testing, honest participants followed the more direct trajectory to the desired answer while fakers showed trajectories that initially converged towards the actual autobiographical information and then switched to the opposite direction to select the relevant alternative.…”

Detecting faking-good response style in personality questionnaires with four choice alternatives

“…Similarly, it has been shown that the analysis of movement trajectories of participants engaged in mouse-tracking (Pfister et al, 2016) and finger-tracking paradigms (Wirth et al, 2016) can reveal the on-going conflicts caused by a voluntary and deliberate rule violation. More recently, a series of studies conducted by Monaro et al have suggested that, when completing autobiographical inventories, honest respondents follow a direct trajectory from the starting point to the desired answer, whereas fakers show larger and less straight trajectories that initially point towards the actual autobiographical information and then switch in the direction of the alternative (Monaro, Gamberini, and Sartori, 2017;Monaro et al, 2018). Other studies have demonstrated that it is possible to identify patients simulating symptoms of depression and amnesia with accuracies ranging from 80 to 90% by analyzing their mouse dynamics when responding to questions about their symptoms (Monaro et al, 2018Zago et al, 2019).…”

The Detection of Malingered Amnesia: An Approach Involving Multiple Strategies in a Mock Crime

“…A recent technique, also referred to as kinematic technique , has been introduced by Monaro et al (42, 43) to detect fake responses regarding identity. It is based on recording motor response of subjects involved in a computer task while using a mouse.…”