Explainable Presentation Attack Detection of Digital Fingerprints

Biometric systems are used in our daily life but are subject to attacks to bypass them as a security solution. Presentation attacks in digital fingerprints occur when an imposter tries to use a fake sample at the acquisition step to impersonate another individual or not to be identified. Providing an explanation for the operator (who is not an expert in biometrics) could be of great interest for many applications (border control, physical access control). In this paper, we propose a fingerprint presentation attack detection method with explainability feedback that can be understood by any user. The experiments has been realized on the Fingerprint Liveness Detection Competition (LivDet) dataset in 2015 and contains more than 58,000 bona fide and attack fingerprint images. The proposed method reaches an accuracy rate of $95.7 \%$ on LivDet2015 with feedback that can be understood by any user.