Grid Anonymous Trajectory Privacy Protection Algorithm Based on Differential Privacy

被引：0

作者：

Dai, Hong ^{[1
]}

Wu, Zijian ^{[2
]}

Wang, Shuang ^{[2
]}

Wu, Ke ^{[2
]}

机构：

[1] School of Computer Science and Software Engineering, University of Science and Technology Liaoning, CO, Anshan,114051, China

[2] School of Computer Science and Software Engineering, University of Science and Technology Liaoning, CO, Anshan,114051, China

来源：

IAENG International Journal of Applied Mathematics | 2023年 / 53卷 / 03期

关键词：

Budget control - Data privacy - K-means clustering - Text processing;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Attackers can use data analysis to learn about the user's regular habits if the current trajectory data is shared and used without being processed. It will lead to the user's private information being revealed. To meet the trajectory k-anonymity, the method of anonymity protection that considers the entire trajectory as a unit frequently needs ample anonymity space and noise addition. Research has focused on finding practical and effective ways to protect trajectory data. As a result, the article suggests the Differential Privacy for Grid Anonymous Trace Privacy (DP-GATP) method. First, Term Frequency and Inverse Document Frequency (TF-IDF) technology extracts the crucial dwell point data from the user trajectory. Different weights are then assigned based on the authorization level for privacy protection. The exponential technique is used to reduce noise and fairly distribute the privacy budget. The geographical grid then changes the trajectory data coordinates. For k-clustering, the grid weight greedy clustering technique is employed. The experimental findings demonstrate that the strategy may safeguard the privacy of critical dwell spots in trajectory data under the assumption of assuring data availability. The amount of anonymous space needed to publish data significantly decreases after grid processing. When compared to algorithms of a similar nature, the availability of the data published is higher. © (2023), (International Association of Engineers). All Rights Reserved.

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