Two-party and multi-party private matching for proximity-based mobile social networks

Proximity-based mobile social networks (PMSNs) are a novel type of social networks, where mobile users can choose potential friends in vicinity by comparing the similarity degree between their private attributes and make new connections through the WiFi/Bluetooth interfaces on their mobile devices. Since users´ personal attributes usually contain some sensitive information, users may have increasing privacy concerns and do not want to reveal their attributes to others in the process of friend discovery. In this paper, we first propose a two-party private matching algorithm, which achieves a fine-grained match and protects users´ privacy preferably without reliance on any Trusted Third Party (TTP). Based on the two-party protocol, we then present a multi-party matching protocol, where a responder who satisfies the pre-defined threshold can match with a group of users without breaching their privacy. By the detailed analysis and simulations, we evaluate our two matching schemes in terms of security, communication overhead and computation overhead, which show a better performance than other related protocols.