LAUSR

Mobile social network (MSN) is getting immense popularity these days. MSN enables people to make social relationship online as well as offline. Proximity based mobile social network (PMSN) is a subset of MSN where people in near proximity interact with each other. One of the famous applications of MSN (or PMSN) is profile matchmaking. In this application, users in near proximity run a matchmaking protocol in order to compute the similarity between their profiles. However, revealing such information may cause significant privacy threat due to the presence of an attacker in near proximity. The attacker can be an outsider as well as a malicious insider. This paper presents a privacy-aware interests similarity protocol (PAISP) in order to facilitate the users computing the similarity between profiles. PAISP proposes different levels of privacy that allow users to have control over information revelation during matchmaking. Towards the end of the paper, we present the security analysis to show the resilience of our proposed protocol against various threats. Furthermore, we implement our proposed protocol for performance evaluation. The results show that our protocol is feasible, effective and performs better in comparison to existing approaches.