A Study Of Matrix Transformation-based Private Matching For Proximity-based Mobile Social Networks

In recent years, the increasing popularity of mobile devices and the explosive advancement of Mobile Social Networks enable proximity-based mobile social networks (PMSNs) a vital part in our daily life. Among these applications, an important service is Proximity-based Mobile Social Networks (PMSNs), which refers to the social interaction among physically proximate mobile users directly through the Bluetooth/WIFI interfaces on their smartphones. A user can find a best matching friend in vicinity through profile matching. PMSNs provide users more chances to make new social interactions with their neighbors, and they are the only way to do social networking when there is lack of Internet access, e.g., due to the very weak signals from cellular base station or some natural disaster scenarios like earthquake. To enjoy these activities, the first step is to choose potential friends from nearby users. A straightforward way is that an initiator broadcasts her interests directly to all the nearby users, and then the responder makes decision according to the common interests. This scheme works well but conflicts with the mobile users’privacy, since they would not want to reveal their interests to strangers before deciding to interact with them. To achieve privacy preserving friend discovery, many schemes are proposed based on traditional cryptographic methods, such as homomorphic and commutative encryption, which inevitably introduce tremendous overhead to the system and are not practical for the resource-limited mobile devices. In this paper, we propose an Efficient Weight-based Private Matching protocol, which provides a realistic matching approach considering both the number of common interests and the corresponding weights on them. In Efficient Weight-based Private Matching protocol, we utilize the Confusion Matrix Transformation algorithm to achieve a secure and efficient matching.Research works of this paper are as follows:1. In this paper, we summarize the shortage of existing matching shceme, and propose an Efficient Weight-based Private Matching (EWPM) protocol. In EWPM, we utilize the Confusion Matrix Transformation (CMT) algorithm instead of complex cryptographic computations in EWPM, which can not only ensure a high-level privacy of users’profile information, but also greatly improve the efficiency of the matching process.2. We carry out our private matching with considering both the number of common attributes and the related weights on them.3. In terms of current popular problem of group matching, we give a novel private matching protocol, based on our two party private matching. We also analyze some common problems in existing schemes.4. We utlize a third party to do the signature and authentication, to prevent malicious users’exhaustive attack.5. The security and performance analysis indicate that our scheme can achieve the privacy preserving goal with a higher efficiency. It needs less execution time and energy consumption...