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  • 标题:A User-Defined Location-Sharing Scheme with Efficiency and Privacy in Mobile Social Networks
  • 本地全文:下载
  • 作者:Tao Peng ; Jierong Liu ; Guojun Wang
  • 期刊名称:Scientific Programming
  • 印刷版ISSN:1058-9244
  • 出版年度:2020
  • 卷号:2020
  • 页码:1-13
  • DOI:10.1155/2020/7832875
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    The popularity of the modern smart devices and mobile social networks (MSNs) brings mobile users better experiences and services by taking advantage of location-aware capabilities. Location sharing, as an important function of MSNs, has attracted attention with growing popularity. While the users get great benefits and conveniences from MSNs, they also have high concerns about the privacy of location. However, in the existing solution, the privacy of users can hardly be guaranteed without the assumption of full trust in the service provider (SP), and few previous research studies have discussed the individual requirement of mobile users in MSNs. In this paper, we propose a user-defined location-sharing scheme (ULSS) to achieve enhanced privacy preservation under different contexts. We present a coarse-grained proximity detection method and a lightweight order-preserving encryption- (OPE-) based method to provide the users with flexible privacy preservation at different privacy levels. The proposed scheme preserves user’s location privacy with respect to SP, friends, and other adversaries, getting rid of the introduction of fully trusted party (TTP). Extensive experiments were conducted to verify the effectiveness and efficiency of our proposed scheme.

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