Designing a facial spoofing database for processed image attacks

Omar, Luma; Ivrissimtzis, Ioannis

Abstract

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.

Citation

Omar, L., & Ivrissimtzis, I. (2016, November). Designing a facial spoofing database for processed image attacks. Presented at 7th International Conference on Imaging for Crime Detection and Prevention., Madrid, Spain

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 7th International Conference on Imaging for Crime Detection and Prevention.
• Start Date: Nov 23, 2016
• End Date: Nov 25, 2016
• Acceptance Date: Oct 3, 2016
• Online Publication Date: Nov 7, 2016
• Publication Date: Nov 23, 2016
• Deposit Date: Nov 4, 2016
• Publicly Available Date: Nov 7, 2016
• Publisher: IET
• Series Title: IET conference proceedings
• Book Title: 7th International Conference on Imaging for Crime Detection and Prevention (ICDP 2016) : Madrid, Spain, 23-25 November 2016 ; proceedings.
• DOI: https://doi.org/10.1049/ic.2016.0073
• Public URL: https://durham-repository.worktribe.com/output/1150035