Personalized trajectory data perturbation algorithm based on quadtree indexing

doi:10.19682/j.cnki.1005-8885.2024.1014

中国邮电高校学报(英文) ›› 2024, Vol. 31 ›› Issue (4): 17-27.doi: 10.19682/j.cnki.1005-8885.2024.1014

Personalized trajectory data perturbation algorithm based on quadtree indexing

刘琨,靳军辉,王辉,申自浩,刘沛骞

河南理工大学

收稿日期:2023-06-26 修回日期:2024-03-28 出版日期:2024-08-31 发布日期:2024-08-31
通讯作者: 王辉 E-mail:wanghui_jsj@hpu.edu.cn
基金资助:
国家自然科学基金项目;河南省高等学校重点科研项目;河南理工大学博士基金

Personalized trajectory data perturbation algorithm based on quadtree indexing

Received:2023-06-26 Revised:2024-03-28 Online:2024-08-31 Published:2024-08-31

摘要/Abstract

摘要： To solve the privacy leakage problem of truck trajectories in intelligent logistics, this paper proposes a Quadtree-based Personalized Joint location Perturbation (QPJLP) algorithm using location generalization and local differential privacy techniques. Firstly, a flexible position encoding mechanism based on the spatial quadtree indexing is designed, and the length of the encoding can be adjusted freely according to data availability. Secondly, to meet the privacy needs of different locations of users, location categories are introduced to classify locations as sensitive and ordinary locations. Finally, the truck invokes the corresponding mechanism in the QPJLP algorithm to locally perturb the code according to the location category, allowing the protection of non-sensitive locations to be reduced without weakening the protection of sensitive locations, thereby improving data availability. Simulation experiments demonstrate that the proposed algorithm effectively meets the personalized trajectory privacy requirements while also exhibiting good performance in trajectory proportion estimation and Top-K classification.

关键词: intelligent logistics, quadtree indexing, local differential privacy, trajectory privacy protection, location categories

Abstract: To solve the privacy leakage problem of truck trajectories in intelligent logistics, this paper proposes a Quadtree-based Personalized Joint location Perturbation (QPJLP) algorithm using location generalization and local differential privacy techniques. Firstly, a flexible position encoding mechanism based on the spatial quadtree indexing is designed, and the length of the encoding can be adjusted freely according to data availability. Secondly, to meet the privacy needs of different locations of users, location categories are introduced to classify locations as sensitive and ordinary locations. Finally, the truck invokes the corresponding mechanism in the QPJLP algorithm to locally perturb the code according to the location category, allowing the protection of non-sensitive locations to be reduced without weakening the protection of sensitive locations, thereby improving data availability. Simulation experiments demonstrate that the proposed algorithm effectively meets the personalized trajectory privacy requirements while also exhibiting good performance in trajectory proportion estimation and Top-K classification.

Key words: intelligent logistics, quadtree indexing, local differential privacy, trajectory privacy protection, location categories

中图分类号:

TP309

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Personalized trajectory data perturbation algorithm based on quadtree indexing

Personalized trajectory data perturbation algorithm based on quadtree indexing

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