Abstract
In the recent years, with the rapid development of social networks and mobile devices, mobile users can exchange the information and find the potential friends in vicinity through comparing the similarity degree between their personal attributes and make a connection via Wi-Fi/Bluetooth. The personal attributes, however, usually contain some private information, and users are not willing to reveal these to others in the process of friend discovery. In this paper, we proposed a novel efficient private matching scheme, which adopts an asymmetric scalar-preserving encryption according to the idea of k-nearest neighbor (kNN) queries. The personal profile of users will be processed in different ways, which is not recoverable. Moreover, our scheme relies on no Trusted Third Party (TTP). Detailed security and performance analysis demonstrate that our scheme can protect users’ private information and resist outside attack during the matching process.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China under Grant No. 61103035 and the Science and Technology Program of Hunan Province under Grant No. 2014GK3029.
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Qi, F., Wang, W. (2015). Efficient Private Matching Scheme for Friend Information Exchange. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9530. Springer, Cham. https://doi.org/10.1007/978-3-319-27137-8_36
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DOI: https://doi.org/10.1007/978-3-319-27137-8_36
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