Protecting Moving Trajectories with Dummies
Protecting Moving Trajectories with Dummies
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DOI：
10.1109/mdm.2007.58
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发表时间：
2007-05
期刊：
影响因子：
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通讯作者：
Tun-Hao You;Wen-Chih Peng-;Wang-Chien Lee
中科院分区：
文献类型：
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作者：
Tun-Hao You;Wen-Chih Peng-;Wang-Chien Lee
在文献中已经提出了用于保护移动的用户的位置隐私的基于虚拟的匿名化技术。通过生成的假人，在人类的轨迹移动，表明移动的用户的位置隐私可以得到保护。然而，通过监视用户的长期移动模式，仍然可以暴露移动的用户的轨迹。我们认为，一旦用户的轨迹被识别，用户的位置被暴露。因此，保护移动的用户的移动轨迹以保护用户位置隐私是至关重要的。我们提出了两个方案，从长远来看，产生一致的运动模式。在用户指定的隐私配置文件中的三个参数，即短期披露，长期披露和距离偏差的指导下，所提出的方案推导出的运动轨迹的假人。初步的性能研究表明，我们的方法是更有效地保护移动轨迹的移动的用户和他们的位置隐私比现有的工作。
Dummy-based anonymization techniques for protecting location privacy of mobile users have been proposed in the literature. By generating dummies that move in humanlike trajectories, shows that location privacy of mobile users can be preserved. However, by monitoring long-term movement patterns of users, the trajectories of mobile users can still be exposed. We argue that, once the trajectory of a user is identified, locations of the user is exposed. Thus, it's critical to protect the moving trajectories of mobile users in order to preserve user location privacy. We propose two schemes that generate consistent movement patterns in a long run. Guided by three parameters in user specified privacy profile, namely, short- term disclosure, long-term disclosure and distance deviation, the proposed schemes derive movement trajectories for dummies. A preliminary performance study shows that our approach is more effective than existing work in protecting moving trajectories of mobile users and their location privacy.