Modern face recognition biometrics widely rely on deep neural networks that are usually trained on large collections of wild face images of celebrities. This choice of the data is related with its public availability in a situation when existing ID document compliant face image datasets (usually stored by national ...

Look-alikes, a.k.a. doppelgängers, increase the probability of false matches in a facial recognition system, in contrast to random face image pairs selected for non-mated comparison trials. In order to analyse and improve the robustness of automated face recognition, datasets of doppelgänger face image pairs are needed. ...

Modern biometric systems establish their decision based on the outcome of machine learning (ML) classifiers trained to make accurate predictions. Such classifiers are vulnerable to diverse adversarial attacks, altering the classifiers' predictions by adding a crafted perturbation. According to ML literature, those attacks ...

This paper proposes an efficient face template protection system based on homomorphic encryption. By developing a message packing method suitable for the calculation of the square Euclidean distance, the proposed system computes the squared Euclidean distance between facial features by a single homomorphic multiplication. ...