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Open Access

A Local Differential Privacy Trajectory Protection Method Based on Temporal and Spatial Restrictions for Staying Detection

College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
School of Computer Science and Technology, Shandong University, Qingdao 266237, China
Department of Computer Science, Georgia State University, Atlanta, GA 30303, USA
College of Information Science and Technology, Jinan University, Guangzhou 510632, China
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Abstract

The widespread availability of GPS has opened up a whole new market that provides a plethora of location-based services. Location-based social networks have become very popular as they provide end users like us with several such services utilizing GPS through our devices. However, when users utilize these services, they inevitably expose personal information such as their ID and sensitive location to the servers. Due to untrustworthy servers and malicious attackers with colossal background knowledge, users’ personal information is at risk on these servers. Unfortunately, many privacy-preserving solutions for protecting trajectories have significantly decreased utility after deployment. We have come up with a new trajectory privacy protection solution that contraposes the area of interest for users. Firstly, Staying Points Detection Method based on Temporal-Spatial Restrictions (SPDM-TSR) is an interest area mining method based on temporal-spatial restrictions, which can clearly distinguish between staying and moving points. Additionally, our privacy protection mechanism focuses on the user’s areas of interest rather than the entire trajectory. Furthermore, our proposed mechanism does not rely on third-party service providers and the attackers’ background knowledge settings. We test our models on real datasets, and the results indicate that our proposed algorithm can provide a high standard privacy guarantee as well as data availability.

Keywords

trajectory datalocal-differential privacystay points detectionareas of interest, temporal-spatial clustering

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Tsinghua Science and Technology
Volume 29 Issue 2,
April 2024
Pages 617-633
DOI: 10.26599/TST.2023.9010072
Cite this article:
Zhang W, Xie Z, Sai AMVV, et al. A Local Differential Privacy Trajectory Protection Method Based on Temporal and Spatial Restrictions for Staying Detection. Tsinghua Science and Technology, 2024, 29(2): 617-633. https://doi.org/10.26599/TST.2023.9010072

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Received: 21 June 2023
Revised: 12 July 2023
Accepted: 15 July 2023
Published: 22 September 2023
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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