• Corpus ID: 236924628

Fairness Properties of Face Recognition and Obfuscation Systems

@article{Rosenberg2021FairnessPO,
  title={Fairness Properties of Face Recognition and Obfuscation Systems},
  author={Harrison Rosenberg and Brian Tang and Kassem Fawaz and Somesh Jha},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.02707}
}
  • Harrison Rosenberg, Brian Tang, +1 author Somesh Jha
  • Published 5 August 2021
  • Computer Science
  • ArXiv
The proliferation of automated facial recognition in various commercial and government sectors has caused significant privacy concerns for individuals. A recent and popular approach to address these privacy concerns is to employ evasion attacks against the metric embedding networks powering facial recognition systems. Face obfuscation systems generate imperceptible perturbations, when added to an image, cause the facial recognition system to misidentify the user. The key to these approaches is… 
SoK: Anti-Facial Recognition Technology
TLDR
This paper creates a systematic framework for analyzing the benefits and tradeoffs of different AFR approaches and considers both technical and social challenges facing AFR tools and proposes directions for future research in this field.

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