Generating Dummies Based on Gravity Model for User's Trajectory Privacy

doi:10.13190/j.jbupt.2017.02.009

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2017, Vol. 40 ›› Issue (2): 57-66.doi: 10.13190/j.jbupt.2017.02.009

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Generating Dummies Based on Gravity Model for User's Trajectory Privacy

ZHANG Cui

1. The State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100195, China;
2. School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100195, China

Received:2016-10-25 Online:2017-04-28 Published:2017-04-26

Abstract

Abstract: The real-time location privacy preserving is a hotspot in continuous Location-Based Services (LBSs). A client-based dummy trajectory generation method is proposed. Based on the spatial grid partition, the history data in each cell of this grid is analyzed. Using the gravity model, a prediction model for users' movement pattern is built. Combined with the movement pattern model and the history query probability, the author defines a trajectory entropy to metric the trajectory privacy level. Based on k-anonymity principle, a limited velocity dummy trajectory generation algorithm with maximum trajectory entropy is proposed. Experiments from synthesis data and real-world data validate the effectiveness of our proposed method.

Key words: continuous location-based services, gravity model, trajectory privacy, inference attack

CLC Number:

TN929.5

ZHANG Cui. Generating Dummies Based on Gravity Model for User's Trajectory Privacy[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2017, 40(2): 57-66.

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Generating Dummies Based on Gravity Model for User's Trajectory Privacy

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