Pseudo Anonymous and Hidden Attribute Comparison Based on Quick Friend Matching in Mobile Social Networks

Abstract

With the development of smart terminals and mobile social networks, users can find potential friends who have similar interests by sharing personal attribute profile in mobile social networks (MSN). However, the personal attribute profile usually contains sensitive information, and if this information is captured by attackers, it may cause unexpected consequences. In this paper, we propose a privacy-preserving matching scheme which is based on both identity authentication and key agreement. The scheme relies on trusted third party which has powerful computation ability and can reduce the workload on intelligent terminal. Moreover, the scheme uses encryption and authentication techniques to guarantee that the attacker fails to get the real information of user's attribute profile, so the personal privacy can be protected during friend matching process. Security analysis shows that the proposed scheme can protect the user's privacy. The simulation result shows that the scheme is more efficient than existing works.