Robust Model-Based Data Management
Main Article Content
Abstract
Making new connections according to personal preferences is a crucial service in mobile social networking, where the initiating user can find matching users within physical proximity of him/her. In existing systems for such services, usually all the users directly publish their complete profiles for others to search. However, in many applications, the users’ personal profiles may contain sensitive information that they do not want to make public. In this paper, we propose Find U, the first privacy-preserving personal profile matching schemes for mobile social networks. In Find U, an initiating user can find from a group of users the one whose profile best matches with his/her; to limit the risk of privacy exposure, only necessary and minimal information about the private attributes of the participating users is exchanged. Matching user profiles using their physical proximity via mobile social networking is a critical thing. We propose Find U, the concept used to limit the privacy levels and also to find the best matching profiles. To realize the user privacy levels here we are using secure multiparty computation (SMC) techniques. We also propose protocols such as PSI, PCSI to prove their security proofs. We evaluate the efficiency of the protocols by adopting the total run time and energy consumption.
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