Identity Verification Using a Kinematic Memory Detection Technique
We present a new method that allows the identification of false self-declared identity, based on indirect measures of the memories relating the affirmed personal details. This method exploits kinematic analysis of mouse as implicit measure of deception, w
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Abstract We present a new method that allows the identification of false self-declared identity, based on indirect measures of the memories relating the affirmed personal details. This method exploits kinematic analysis of mouse as implicit measure of deception, while the user is answering to personal information. Results show that using mouse movement analysis, it is possible to reach a high rate of accuracy in detecting the veracity of self-declared identities. In fact, we obtained an average accuracy of 88 % in the classification of single answers as truthful or untruthful, that corresponds overall to 9.7/10 participants correctly classified as true tellers or liars. The advantage of this method is that it does not requires any knowledge about the real identity of the declarant. Keywords Identity verification
Lie detection Memory detection
1 Introduction Nowadays the security concerning the identity has become a very sensitive issue. In particular, the increase of terrorist attacks in the last decades imposes the need to recognize declarants of false identity. Usually migrants from Middle East entering Europe or USA do not have any documents and personal details are frequently self-declared. Among them, a high number of terrorists giving false identities are believed to be hidden. Because terrorists move across countries using fake identities, the identity detection is now a major target in anti-terrorism [1]. M. Monaro (&) L. Gamberini G. Sartori University of Padova, Human Inspired Technolgy Research Centre, via Luzzati 4, 35122 Padua, Italy e-mail: [email protected] L. Gamberini e-mail: [email protected] G. Sartori e-mail: [email protected] © Springer International Publishing Switzerland 2017 K.S. Hale and K.M. Stanney (eds.), Advances in Neuroergonomics and Cognitive Engineering, Advances in Intelligent Systems and Computing 488, DOI 10.1007/978-3-319-41691-5_11
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Deception is cognitively more complex than truth telling and this higher complexity reflects itself in a lengthening of the reaction times (RT) during a response [2]. According to literature, two memory detection techniques based on RT have been proposed to identify liars. These are the autobiographical Implicit Association Test (aIAT) [3] and the RT-based Concealed Information Test (RT-CIT) [4]. These techniques may be used also as tools for identity verification [5]. RT based techniques have a number of advantages compared to the traditional psychophysiological techniques to detect deception, as the polygraph [6]. First, RT are not subjected to strong individual and environmental changes, such as in the case of physiological parameters. Secondly, these techniques are inexpensive and suitable to be used on large scale. However, these techniques are not without limitations. Even though RTs are implicit measures, during the aIAT or CIT examination the lie detection purpose is explicit (overt detection of deception). Furthermore, RT based techniques only studied the latency in the response
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