#359: Do you know you are tracked by photos that you didn't take: Large-scale location-aware multi-party image privacy protection

J. Morris, S. Newman, K. Palaniappan, J. Fan, and D. Lin

IEEE Transactions on Dependable and Secure Computing, pgs. In Press, 2022

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Most existing image privacy protection works focus mainly on the privacy of photo owners and their friends, but lack the consideration of other people who are in the background of the photos and the related location privacy issues. When a person is in the background of someone else's photos, he/she may be unintentionally exposed to the public when the photo owner shares the photo online. Not only a single visited place could be exposed, attackers may also be able to piece together a person's travel route from images. In this paper, we propose a novel image privacy protection system, called LAMP, which aims to light up the location awareness for people during online image sharing. The LAMP system is based on a newly designed location-aware multi-party image access control model. Unlike previous works on small scales, the LAMP system is highly efficient and scalable as it can enforce privacy protection for billions of users on social networks in real time. The system automatically detects the user's occurrences on photos and replace the user's face with a synthetic face if he/she has location privacy concern at the photo location. A prototype was implemented to demonstrate its applicability in the real world.