Security News > 2021 > August > Using “Master Faces” to Bypass Face-Recognition Authenticating Systems
Abstract: A master face is a face image that passes face-based identity-authentication for a large portion of the population.
These faces can be used to impersonate, with a high probability of success, any user, without having access to any user-information.
We optimize these faces, by using an evolutionary algorithm in the latent embedding space of the StyleGAN face generator.
Multiple evolutionary strategies are compared, and we propose a novel approach that employs a neural network in order to direct the search in the direction of promising samples, without adding fitness evaluations.
The results we present demonstrate that it is possible to obtain a high coverage of the population with less than 10 master faces, for three leading deep face recognition systems.