# Generating Master Faces for Use in Performing Wolf Attacks on Face Recognition Systems

arXiv: https://arxiv.org/abs/2006.08376 · HTML: https://mlsanity.com/paper/2006.08376/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jun 2020.

## Built on by (most cited first, 13 of 13)

- [Synthetic Data for Face Recognition: Current State and Future Prospects](https://mlsanity.com/paper/2305.01021/) (2023)
- [Synthetic Data in Human Analysis: A Survey](https://mlsanity.com/paper/2208.09191/) (2022)
- [Generating Master Faces for Dictionary Attacks with a Network-Assisted Latent Space Evolution](https://mlsanity.com/paper/2108.01077/) (2021)
- [Master Face Attacks on Face Recognition Systems](https://mlsanity.com/paper/2109.03398/) (2021)
- [On the (Limited) Generalization of MasterFace Attacks and Its Relation to the Capacity of Face Representations](https://mlsanity.com/paper/2203.12387/) (2022)
- [Universal Adversarial Spoofing Attacks against Face Recognition](https://mlsanity.com/paper/2110.00708/) (2021)
- [Dictionary Attacks on Speaker Verification](https://mlsanity.com/paper/2204.11304/) (2022)
- [Generating 2D and 3D Master Faces for Dictionary Attacks with a Network-Assisted Latent Space Evolution](https://mlsanity.com/paper/2211.13964/) (2022)
- [Deep Learning in the Field of Biometric Template Protection: An Overview](https://mlsanity.com/paper/2303.02715/) (2023)
- [Diversity and Novelty MasterPrints: Generating Multiple DeepMasterPrints for Increased User Coverage](https://mlsanity.com/paper/2209.04909/) (2022)
- [Analysis of Master Vein Attacks on Finger Vein Recognition Systems](https://mlsanity.com/paper/2210.10667/) (2022)
- [Generalized Attacks on Face Verification Systems](https://mlsanity.com/paper/2309.05879/) (2023)
- [Casting the Net! Revisiting MasterFace Impersonation Attacks](https://mlsanity.com/paper/2608.06952/) (2026)

## Abstract (arXiv)

Due to its convenience, biometric authentication, especial face authentication, has become increasingly mainstream and thus is now a prime target for attackers. Presentation attacks and face morphing are typical types of attack. Previous research has shown that finger-vein- and fingerprint-based authentication methods are susceptible to wolf attacks, in which a wolf sample matches many enrolled user templates. In this work, we demonstrated that wolf (generic) faces, which we call "master faces," can also compromise face recognition systems and that the master face concept can be generalized in some cases. Motivated by recent similar work in the fingerprint domain, we generated high-quality master faces by using the state-of-the-art face generator StyleGAN in a process called latent variable evolution. Experiments demonstrated that even attackers with limited resources using only pre-trained models available on the Internet can initiate master face attacks. The results, in addition to demonstrating performance from the attacker's point of view, can also be used to clarify and improve the performance of face recognition systems and harden face authentication systems.