Loading…

A trajectory privacy protection method using cached candidate result sets

A trajectory privacy protection method using cached candidate result sets (TPP-CCRS) is proposed for the user trajectory privacy leakage problem. First, the user's area is divided into a grid to lock the user's trajectory range, and a cache area is set on the user's mobile side to cac...

Full description

Saved in:
Bibliographic Details
Published in:Journal of parallel and distributed computing 2024-11, Vol.193, p.104965, Article 104965
Main Authors: Shen, Zihao, Tang, Yuyu, Wang, Hui, Liu, Peiqian, Zheng, Zhenqing
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A trajectory privacy protection method using cached candidate result sets (TPP-CCRS) is proposed for the user trajectory privacy leakage problem. First, the user's area is divided into a grid to lock the user's trajectory range, and a cache area is set on the user's mobile side to cache the candidate result sets queried from the user's area. Second, a security center is deployed to register users securely and assign public and private keys for verifying location information. The same user's location information is randomly divided into M copies and sent to multi-anonymizers. Then, the random concurrent k-anonymization mechanism with multi-anonymizers is used to concurrently k-anonymize M copies of location information. Finally, the prefix tree is added on the location-based service (LBS) server side, and the location information is encrypted using the clustered data fusion privacy protection algorithm. The optimal binary tree algorithm queries user interest points. Security analysis and experimental verification show that the TPP-CCRS can effectively protect user trajectory privacy and improve location information query efficiency. •Adds a cache area on the user's mobile side to cache the candidate result set.•Deploys Security Center and multi-anonymizers between the user and the LBS server.•Adds prefix trees on the LBS server side.•Uses the clustered data fusion privacy protection algorithm to protect the location information.
ISSN:0743-7315
DOI:10.1016/j.jpdc.2024.104965