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K-anonymity privacy-preserving for trajectory in uncertain environment
ZHU Lin, HUANG Shengbo
Journal of Computer Applications    2015, 35 (12): 3437-3441.   DOI: 10.11772/j.issn.1001-9081.2015.12.3437
Abstract457)      PDF (784KB)(344)       Save
To comprehensively consider the factors influencing the moving objects in uncertain environment, a k-anonymity privacy-preserving method for the trajectory recorded by automatic identification system was presented. Firstly, an uncertain spatial index model was established which was stored in grid quadtree. Then the continuous k-Nearest Neighbor ( KNN) query method was used to find the trajectory which had the similar area to the current trajectory, and the trajectory was added to the anonymous candidate set. By considering the network scale influence on the effectiveness of the anonymous information and the probability of attacker's attack on trajectory, the optimal exploit chain of trajectory was generated by using the heuristic algorithm to strengthen the trajectory privacy-preserving. Finally, the experimental results show that, compared with the traditional method, the proposed method can decrease the information loss by 20% to 50%,while the information distortion can maintain below 50% with the enlarge of query range and the cost loss is cut down by 10% to 30%.The proposed method can effectively prevent malicious attackers from the information access of trajectory,and can be applied for the official boat to law enforcement at sea.
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