Mobile social networks represent a promising cyber-physical system, which connects mobile nodes within a local physical proximity using mobile smart phones as well as wireless communication. In mobile social networks, the mobile users may, however, face the risk of leaking their personal information and location privacy. In this paper, we first model the secure friend discovery process as a generalized privacypreserving interest and profile matching problem. We identify a new security threat arising from existing secure friend discovery protocols, coined as runaway attack, which can introduce a serious unfairness issue. To thwart this new threat, we introduce a novel blind vector transformation technique, which could hide the correlation between the original vector and transformed results. Based on this, we propose our privacypreserving and fairness-aware interest and profile matching protocol, which allows one party to match its interest with the profile of another, without revealing its real interest and profile and vice versa. The detailed security analysis as well as real-world implementations demonstrate the effectiveness and efficiency of the proposed protocol.
CITATION STYLE
Zhu, H., Du, S., Li, M., & Gao, Z. (2013). Fairness-aware and privacy-preserving friend matching protocol in mobile social networks. IEEE Transactions on Emerging Topics in Computing, 1(1), 192–200. https://doi.org/10.1109/TETC.2013.2279541
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