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中文摘要：
随着移动设备和定位技术的发展,产生了大量的移动对象轨迹数据.轨迹数据含有丰富的时空信息,对其分析和挖掘可以支持多种与移动对象相关的应用.然而,针对轨迹数据的攻击性推理可能导致个人的兴趣爱好、行为模式、社会习惯等隐私信息暴露.另一方面,在基于位置的服务中,由于现有位置隐私保护技术并不能解决轨迹隐私泄露的问题,移动对象的个人隐私很可能通过实时运行轨迹而暴露.针对上述两种场景,轨迹隐私保护的研究提出了明确的要求：在轨迹数据发布中,隐私保护技术既要保护轨迹数据的隐私,又要保证数据有较高的可用性;在基于位置的服务中,隐私保护技术既要保护移动对象的实时轨迹隐私,又要保证用户获得较高的服务质量.该文针对上述两个问题分析了轨迹隐私保护中存在的挑战性问题,针对不同的隐私保护方法分析了现有的研究工作,介绍了当前该领域的研究热点,指明了未来的研究方向.
英文摘要：
As the high up development of Location-Based Service （LBS） and location-aware devices, the amount of locations and trajectories of moving objects collected by service providers is continuously increasing. The collected trajectories with wealth spatio-temporal information will be published for novel applications. However, directly publishing trajectories may present serious threats to individuals＇ privacy, since trajectories enable intrusive inferences, which may reveal individual＇s habits, behavioral patterns, social customs, etc. On the other hand, individuals＇ real time trajectories may be exposed when they are requiring for location-based services even if their location privacy have been protected. Moreover, specific requirements for trajectory privacy-preserving methods are proposed based on different application scenarios： In trajectory data publishing scenario, privacy-preserving techniques must preserve data utility; in LBS scenario, privacypreserving techniques must guarantee high quality of services that users acquired. All these re quirements make trajectory privacy-preserving more challenging. According to the above problems, the key challenges in trajectory privacy-preserving are analyzed; recent research works on both trajectory data publishing and trajectory privacy in LBS are analyzed in this paper. At last, suggestions for future research works are put forward.
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