Intelligent Deception Detection through Machine Based Interviewing

O'Shea, Jim ORCID: https://orcid.org/0000-0001-5645-2370, Crockett, KA ORCID: https://orcid.org/0000-0003-1941-6201, Khan, Wasiq ORCID: https://orcid.org/0000-0002-7511-3873, Kindynis, Philippos, Antoniades, Athos and Boultadakis, Georgios (2018) Intelligent Deception Detection through Machine Based Interviewing. In: IEEE World Congress on Computational intelligence 2018 (IEEE IJCNN), 08 July 2018 - 13 July 2018, Brazil.

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Abstract

In this paper an automatic deception detection system, which analyses participant deception risk scores from non-verbal behaviour captured during an interview conducted by an Avatar, is demonstrated. The system is built on a configuration of artificial neural networks, which are used to detect facial objects and extract non-verbal behaviour in the form of micro gestures over short periods of time. A set of empirical experiments was conducted based a typical airport security scenario of packing a suitcase. Data was collected through 30 participants participating in either a truthful or deceptive scenarios being interviewed by a machine based border guard Avatar. Promising results were achieved using raw unprocessed data on un-optimized classifier neural networks. These indicate that a machine based interviewing technique can elicit non-verbal interviewee behavior, which allows an automatic system to detect deception.