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Home > Archive>Volume 30, Issue 12, 2019 >3798-3814. DOI:10.13328/j.cnki.jos.005601
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Privacy Preserving Friend Discovery of Matrix Confusion Encryption in Mobile Social Networks
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TP393

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National Natural Science Foundation of China (61632009, 61472451, 61402543, 61272151, 61502163); Natural Science Foundation of Hu'nan Province of China (2018JJ2147, 2018JJ3203); Hu'nan Provincial Education Department of China (2015C0589, 17C0679); Construct Program of Applied Characteristic Discipline in Hu'nan University of Science and Engineering

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    Abstract:

    With the rapid developments of mobile devices and online social networks, users of mobile social networks (MSNs) can easily discover and make new social interactions with others by profiles matching. However, personal profiles usually contain sensitive information of individuals, while the emerging requirement of profile matching in proximity mobile social networks may occasionally leak the sensitive information and hence violate people's privacy. A profile matching protocol in MSNs is proposed, users utilize the confusion matrix transformation algorithm and dot product to achieve secure and efficient matching results; at the same time, users can customize the matching metrics to involve their own matching preference and to make the matching results more precise. In addition, opportunistic computing is adopted to simulate the real friend making senario to guarantee the effectiveness. Security analysis shows that the proposed scheme possesses higher privacy, serviceability, and lower computation and communication cost. Assessed by real social network data, the results demonstrate that the proposed scheme is superior to the existing works.

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    附中文参考文献:
    [1] 付艳艳,张敏,冯登国,陈开渠.基于节点分割的社交网络属性隐私保护.软件学报,2014,25(4):768-780. http://www.jos.org.cn/1000-9825/4565.htm[doi:10.13328/j.cnki.jos.004565]
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罗恩韬,王国军,刘琴,孟大程,唐雅媛.移动社交网络中矩阵混淆加密交友隐私保护策略.软件学报,2019,30(12):3798-3814

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History
  • Received:September 04,2016
  • Revised:March 18,2018
  • Online: January 23,2019
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