Biometric authentication based on pupillary light reflex using neural networks

Abstract

Many different biometric traits can be used for human identification, and each one has specific advantages over the others. However, there is a common problem for most of them: the spoofing vulnerability of the features. The authentication based on human reflexes is a recent proposal against frauds at the biometric level. The involuntary responses of the body cannot be removed from the person, naturally mimicked or reproduced by artificial means. This paper presents a proposal for the use of the features of the Pupillary Light Reflex for user authentication, using artificial neural networks for classification. © 2013 Springer-Verlag.