Unimodal-Bio-GAN: Keyless biometric salting scheme based on generative adversarial network

Cancellable biometrics enabled us to develop robust authentication systems by replacing
the storage of the original biometric template with another secured version. A technique
called biometric salting uses a parameter (key) and an invertible function to transform the
human biometrics features into a secured format that can be protected and stored
securely in a biometric database system. The salting key plays a main role in the success of
this transformation, which makes it robust or vulnerable to many security attacks. One of
the main challenges that faces biometrics' researchers currently is how to design and
protect such a salting key considering two basic measures: security and recognition accuracy. In this article, we propose unimodal-Bio-GAN, a reliable keyless biometric salting
technique based on standard generative adversarial network (GAN). In unimodal-BioGAN, a random permuted version of the human biometric data is implicitly considered as a salting key and required only during the enrolment stage, which increases the
system reliability to overcome different security attacks. The experimental results of
unimodal-Bio-GAN using the CASIA Iris-V3-Internal database outperform the previous
methods and its security efficiency is analysed using different attack types.