Generating Master Faces for Dictionary Attacks with a Network-Assisted Latent Space Evolution

• URL: http://arxiv.org/abs/2108.01077v1
• Date: Sun, 1 Aug 2021 12:55:23 GMT
• Title: Generating Master Faces for Dictionary Attacks with a Network-Assisted Latent Space Evolution
• Authors: Ron Shmelkin, Tomer Friedlander, Lior Wolf
• Abstract summary: A master face is a face image that passes face-based identity-authentication for a large portion of the population. We optimize these faces, by using an evolutionary algorithm in the latent embedding space of the StyleGAN face generator.
• Score: 68.8204255655161
• License: http://creativecommons.org/licenses/by/4.0/
• 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 (over 40%) with less than 10 master faces, for three leading deep face recognition systems.

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