Biometric presentation attack detection using stimulated pupillary movements

Biometric systems can be subverted using presentation attack artefacts. This work presents a way to deal with the vulnerability to such spoofing attacks. In this work we propose the use of pupillary movements to detect such presentation attacks. The pupillary movements were stimulated by presentation of a moving visual challenge to ensure that some pupillary motion can be captured. Photo, 2D mask and 3D mask attack artefacts were evaluated based on data captured from 80 volunteers performing genuine attempts and spoofing attempts. The results indicate the effectiveness of the proposed pupillary movement feature to stop presentation attacks.