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Designing a facial spoofing database for processed image attacks.

Omar, Luma and Ivrissimtzis, Ioannis (2016) 'Designing a facial spoofing database for processed image attacks.', in 7th International Conference on Imaging for Crime Detection and Prevention (ICDP 2016) : Madrid, Spain, 23-25 November 2016 ; proceedings. , 5 (6 .). IET conference proceedings.


Face recognition systems are used for user authentication in everyday applications such as logging into a laptop or smartphone without need to memorize a password. However, they are still vulnerable to spoofing attacks, as for example when an imposter gains access to a system by holding a printed photo of the rightful user in front of the camera. In this paper we are concerned with the design of face image databases for evaluating the performance of anti-spoofing algorithms against such attacks. We present a new database, supporting testing against an enhancement of the attack, where the imposter processes the stolen image before printing it. By testing a standard antispoofing algorithm on the new database we show a significant decrease in its performance and, as a simple remedy to this problem, we propose the inclusion of processed imposter images into the training set.

Item Type:Book chapter
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Publisher statement:This paper is a postprint of a paper submitted to and accepted for publication in 7th International Conference on Imaging for Crime Detection and Prevention (ICDP 2016) and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.
Date accepted:03 October 2016
Date deposited:07 November 2016
Date of first online publication:07 November 2016
Date first made open access:No date available

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