• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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A trajectory (k,e)anonymous algorithm
against trajectory similarity attacks

JIA Junjie,HUANG He   

  1. (College of Computer Science and Engineering,Northwest Normal University,Lanzhou 730070,China)
  • Received:2018-02-27 Revised:2018-09-21 Online:2019-05-25 Published:2019-05-25

Abstract:

Aiming at the problem of trajectory privacy leakage caused by the high similarity between the anonymous centralized trajectories, we propose a trajectory (k,e)anonymous algorithm to resist trajectory similarity attacks.  In the preprocessing process, the algorithm adopts trajectory synchronization to reduce information loss. In clustering process, the trajectory slope is regarded as the sensitive value of trajectory data, and at least k trajectories with different trajectory slopes are selected to satisfy the trajectory k-anonymity. To prevent the privacy leakage caused by the high slope similarity of trajectories in the set, the trajectory slope difference value in each class should be at least e. Experimental results show that the proposal can effectively resist trajectory similarity attacks, reduce information loss while enhancing the availability of trajectory data, and achieve better trajectory privacy protection.
 

Key words: privacy preservation;trajectory anonymity;slope diversity;trajectory(k, e) anonymous algorithm