Trust-based and privacy-preserving fine-grained data retrieval scheme for MSNs

In this paper, we propose a trust-based and privacy-preserving fine-grained data retrieval scheme for mobile social networks (MSNs). The scheme enables users to create a log of trusted users who store (or are interested in) some topics related to a subject of interest. A subject is a broad term that can cover many fine-grained topics. In creating logs, we leverage friends-of-friends relationships and transferrable trust concept. Each user trusts its friends and the friends of friends. If a friend is not interested in a subject, he can help his friend in creating the log by linking the friend to his friends without knowing the subject to preserve privacy. In order to reduce the storage and computation overhead, we use Bloom filters to store the topics. A distinctive feature in our scheme is that it can query users who possess a fine-grained topic, rather than querying users who are interested in the broad subject but they may not have the specific topic of interest. We analyze the security and privacy of our scheme and evaluate the communication and computation overhead.