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    潘 晓 郝 兴 孟小峰. 基于位置服务中的连续查询隐私保护研究[J]. 计算机研究与发展, 2010, 47(1): 121-129.
    引用本文: 潘 晓 郝 兴 孟小峰. 基于位置服务中的连续查询隐私保护研究[J]. 计算机研究与发展, 2010, 47(1): 121-129.
    Pan Xiao, Hao Xing, and Meng Xiaofeng. Privacy Preserving Towards Continuous Query in Location-Based Services[J]. Journal of Computer Research and Development, 2010, 47(1): 121-129.
    Citation: Pan Xiao, Hao Xing, and Meng Xiaofeng. Privacy Preserving Towards Continuous Query in Location-Based Services[J]. Journal of Computer Research and Development, 2010, 47(1): 121-129.

    基于位置服务中的连续查询隐私保护研究

    Privacy Preserving Towards Continuous Query in Location-Based Services

    • 摘要: 近年来,伴随着移动计算技术和无限设备的蓬勃发展,位置服务中的隐私保护研究受到了学术界的广泛关注,提出了很多匿名算法以保护移动用户的隐私信息.但是现有方法均针对snapshot查询,不能适用于连续查询.如果将现有的静态匿名算法直接应用于连续查询,将会产生隐私泄露、匿名服务器工作代价大等问题.针对这些问题,提出了δp-隐私模型和δq-质量模型来均衡隐私保护与服务质量的矛盾,并基于此提出了一种贪心匿名算法.该算法不仅适用于snapshot查询,也适用于连续查询.实验结果证明了算法的有效性.

       

      Abstract: With advances in wireless communication and mobile positioning technologies, location-based mobile services have been gaining increasingly popularity in recent years. Privacy preservation, including location privacy and query privacy, has recently received considerable attention for location-based mobile services. A lot of location cloaking approaches have been proposed for protecting the location privacy of mobile users. However, they mostly focus on anonymizing snapshot queries based on proximity of locations at query issued time. Therefore, most of them are ill-suited for continuous queries. In view of the privacy disclosure (including location and query privacy) and poor quality of service under continuous query anonymization, a δp-privacy model and a δq-distortion model are proposed to balance the tradeoff between privacy preserving and quality of service. Meanwhile a temporal distortion model is proposed to measure the location information loss during a time interval, and it is mapped to a temporal similar distance between two queries. Finally, a greedy cloaking algorithm (GCA) is proposed, which is applicable to both anonymizing snapshot queries and continuous queries. Average cloaking success rate, cloaking time, processing time and anonymization cost for successful requests are evaluated with increasing privacy level (k). Experimental results validate the efficiency and effectiveness of the proposed algorithm.

       

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