Paper Title
Securing Photo Sharing Mechanism with User Granted Permissions on Social Network Data
Abstract
Photo sharing is an attractive feature which popularizes Online Social Networks (OSNs). Unfortunately, it may
leak users’ privacy if they are allowed to post, comment, and tag a photo freely. In this paper, we attempt to address this
issue and study the scenario when a user shares a photo containing individuals other than himself/herself (termed co-photo
for short). To prevent possible privacy leakage of a photo, we design a mechanism to enable each individual in a photo be
aware of the posting activity and participate in the decision making on the photo posting. For this purpose, we need an
efficient facial recognition (FR) system that can recognize everyone in the photo. However, more demanding privacy setting
may limit the number of the photos publicly available to train the FR system[1]. To deal with this dilemma, our mechanism
attempts to utilize users’ private photos to design a personalized FR system specifically trained to differentiate possible
photo co-owners without leaking their privacy. We also develop a distributed consensus based method to reduce the
computational complexity and protect the private training set. We show that our system is superior to other possible
approaches in terms of privacy using encryption algorithm and opensource. Our mechanism is implemented as a proof of
concept Android application on Face book’s platform.
Keywords - online social networks, FR system, open social, privacy, homomorphic encryption