Fairness Properties of Face Recognition and Obfuscation Systems


Harrison Rosenberg, University of Wisconsin–Madison; Brian Tang, University of Michigan; Kassem Fawaz and Somesh Jha, University of Wisconsin–Madison


The proliferation of automated face recognition in the commercial and government sectors has caused significant privacy concerns for individuals. One approach to address these privacy concerns is to employ evasion attacks against the metric embedding networks powering face recognition systems: Face obfuscation systems generate imperceptibly perturbed images that cause face recognition systems to misidentify the user. Perturbed faces are generated on metric embedding networks, which are known to be unfair in the context of face recognition. A question of demographic fairness naturally follows: are there demographic disparities in face obfuscation system performance? We answer this question with an analytical and empirical exploration of recent face obfuscation systems. Metric embedding networks are found to be demographically aware: face embeddings are clustered by demographic. We show how this clustering behavior leads to reduced face obfuscation utility for faces in minority groups. An intuitive analytical model yields insight into these phenomena.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

@inproceedings {285485,
author = {Harrison Rosenberg and Brian Tang and Kassem Fawaz and Somesh Jha},
title = {Fairness Properties of Face Recognition and Obfuscation Systems},
booktitle = {32nd USENIX Security Symposium (USENIX Security 23)},
year = {2023},
isbn = {978-1-939133-37-3},
address = {Anaheim, CA},
pages = {7231--7248},
url = {https://www.usenix.org/conference/usenixsecurity23/presentation/rosenberg},
publisher = {USENIX Association},
month = aug

Presentation Video