Protego: User-Centric Pose-Invariant Privacy Protection Against Face Recognition-Induced Digital Footprint Exposure

TL;DR

Protego is a novel user-centric method that creates pose-invariant, natural-looking facial masks to protect individuals' privacy from face recognition-based digital footprint exposure, outperforming existing techniques.

Contribution

Protego introduces a dynamic 3D mask generation approach that enhances privacy by significantly reducing face recognition accuracy and ensuring visual coherence in videos.

Findings

Reduces retrieval accuracy of face recognition models by over 50%

Performs at least 2x better than existing privacy protection methods

Maintains natural appearance and temporal consistency in videos

Abstract

Face recognition (FR) technologies are increasingly used to power large-scale image retrieval systems, raising serious privacy concerns. Services like Clearview AI and PimEyes allow anyone to upload a facial photo and retrieve a large amount of online content associated with that person. This not only enables identity inference but also exposes their digital footprint, such as social media activity, private photos, and news reports, often without their consent. In response to this emerging threat, we propose Protego, a user-centric privacy protection method that safeguards facial images from such retrieval-based privacy intrusions. Protego encapsulates a user's 3D facial signatures into a pose-invariant 2D representation, which is dynamically deformed into a natural-looking 3D mask tailored to the pose and expression of any facial image of the user, and applied prior to online sharing. Motivated by a critical limitation of existing methods, Protego amplifies the sensitivity of FR models so that protected images cannot be matched even among themselves. Experiments show that Protego significantly reduces retrieval accuracy across a wide range of black-box FR models and performs at least 2x better than existing methods. It also offers unprecedented visual coherence, particularly in video settings where consistency and natural appearance are essential. Overall, Protego contributes to the fight against the misuse of FR for mass surveillance and unsolicited identity tracing.