A sybil attack detection scheme for privacy-preserving mobile social networks

With the pervasiveness of smart phones, mobile social networking (MSN) has received extensive attention in recent years. However, while providing many opportunities to mobile users, MSN also poses new security challenges, and sybil attack is one of such challenges, in which a malicious user can interact with other mobile users multiple times by creating fake identities and misleading them into making decisions that benefit the malicious user himself. In this paper, we consider a privacy-preserving MSN and propose a sybil attack detection scheme, called SADS, to effectively prevent sybil attack and allow all mobile users to detect malicious users while the user's privacy is still preserved in MSN. Specifically, based on Paillier homomorphic encryption technique, the proposed SADS scheme can efficiently detect sybil attack in MSN. Detailed security analysis shows that the user's privacy can be well-protected in the proposed SADS scheme. In addition, the system optimizing design is further proposed to improve the system performance.