Differential Privacy Trajectory Data Protection Algorithm Based on Polar Coordinate Transformation

被引:0
作者
Zhang, Zhenzhen [1 ]
Cai, Jianping [1 ]
Sun, Lan [1 ]
Guo, Yongyi [1 ]
Qiu, Yubing [1 ]
Wu, Yingjie [1 ]
机构
[1] Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350108, Peoples R China
来源
FUZZY SYSTEMS AND DATA MINING VI | 2020年 / 331卷
关键词
Trajectory data protection; Differential privacy; Polar coordinates; Position type;
D O I
10.3233/FAIA200745
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Differential privacy technology has been widely used in the issue of trajectory data release. Improving the availability of data release under the premise of ensuring privacy and security is one of its basic research goals. At present, most trajectory data release methods use a rectangular coordinate system to represent location information. Research has shown that the availability of published data cannot be optimized through the rectangular coordinate system. In order to improve the effect of trajectory data release, this paper proposes a differential privacy trajectory data protection algorithm based on polar coordinates. First, the stay point detection method is used to find frequent stay points in the trajectory and the key location points related to personal privacy are detected by the type of location points. Then, this paper converts the rectangular coordinate system representation of the key position points to the polar coordinate system representation, and implement differential privacy trajectory data release by adding noise to the key position points represented by the polar coordinates. Experiments show that the algorithm proposed in this paper effectively improves the usability of trajectory data on real data sets.
引用
收藏
页码:671 / 681
页数:11
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