SoK: Anti-Facial Recognition Technology

TL;DR

This paper provides a comprehensive analysis of anti-facial recognition (AFR) tools, exploring their design space, benefits, challenges, and future research directions to address privacy concerns associated with facial recognition technology.

Contribution

It offers the first systematic framework for analyzing AFR approaches, considering technical and social challenges, and identifying future research directions.

Findings

Wide-ranging AFR tools with diverse approaches

Tradeoffs between effectiveness and privacy protection

Identification of key challenges and future research areas

Abstract

The rapid adoption of facial recognition (FR) technology by both government and commercial entities in recent years has raised concerns about civil liberties and privacy. In response, a broad suite of so-called "anti-facial recognition" (AFR) tools has been developed to help users avoid unwanted facial recognition. The set of AFR tools proposed in the last few years is wide-ranging and rapidly evolving, necessitating a step back to consider the broader design space of AFR systems and long-term challenges. This paper aims to fill that gap and provides the first comprehensive analysis of the AFR research landscape. Using the operational stages of FR systems as a starting point, we create a systematic framework for analyzing the benefits and tradeoffs of different AFR approaches. We then consider both technical and social challenges facing AFR tools and propose directions for future research in this field.