Facial recognition systems, computational tools that can recognize individuals in images or video footage, are now widely employed worldwide. Some users and developers, however, have raised privacy-related concerns, as by definition facial recognition techniques rely on images that capture people’s faces. It is possible to use facial recognition techniques to identify the person by his/her face without authorization.
Some recent computer science studies have thus been exploring the possibility of preventing unauthorized facial recognition recognizing users by obfuscating, synthesizing or changing images, to increase the privacy of users. This field of research is now broadly referred to as anti-facial recognition (AFR).
Researchers at USSLAB at Zhejiang University recently developed CamPro, a new technique designed to achieve AFR at the camera sensor level, producing images that can protect users’ facial privacy without influencing other applications, such as activity recognition. Their paper, accepted by NDSS 2024 and pre-published on the arXiv preprint server, demonstrates their proposed technique using images taken by widely available cameras.
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