A Cloud Aided Privacy-Preserving Profile Matching Scheme in Mobile Social Networks
Qiong Cheng, Chong-Zhi Gao · 2017
Mobile social networks (MSN) provide services for mobile users to discover and interact with potential friends. Now, more and more people begin to pay attention to looking for a friend who has similar interests. However, when they manage to measure the proximity between their own and other people's profile, they may do not want to reveal their private data. In this paper, we design a cloud aided privacy-preserving profile matching scheme to efficiently compute social proximity between two users to discover potential friends without disclosing the personal privacy to others. Compared to existing profile matching scheme, our scheme uses cloud computing to do most of the computation, which effectively reduces the user's computation and doesn't disclose the personal privacy to cloud.