May the privacy be with us: Correlated differential privacy in location data for ITS

Chong, Kah Meng and Malip, Amizah (2024) May the privacy be with us: Correlated differential privacy in location data for ITS. Computer Networks, 241. ISSN 1389-1286, DOI https://doi.org/10.1016/j.comnet.2024.110214.

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Official URL: https://doi.org/10.1016/j.comnet.2024.110214

Abstract

With the development of Intelligent Transportation Systems (ITS), a vast amount of location data is being generated from various IoT devices equipped with location positioning sensors. Preserving the privacy of location data release is a critical concern, as the publication of aggregated data often reveals private information about the users. Differential Privacy (DP) has recently emerged as a robust framework to guarantee privacy in this context. However, conventional DP mechanisms commonly make no assumption about the distribution of the input data, which could lead to unexpected privacy leakage if the data are correlated. In this paper, we investigate the complex simultaneous impact of user correlation, spatial–temporal correlation and prior knowledge of an adversary on the privacy leakage of a DP mechanism, which has not been addressed in prior work. We derive several closed-form expressions that demonstrate and quantify the privacy leakage under correlated location data, followed by the design of efficient algorithms to compute such privacy leakage. Then, we propose a Δ-CDP (Correlated Differential Privacy) to provide a formal privacy guarantee against the additional privacy leakage incurred by these factors. Extensive comparisons, theoretical analysis, and experimental simulations are presented to validate the correctness and efficiency of the proposed work. © 2024 Elsevier B.V.

Item Type: Article
Funders: Ministry of Education, Malaysia [FRGS/1/29/STG06/2019/UM/02/7], MyBrainSc Scholarship
Uncontrolled Keywords: Data privacy; Intelligent systems; Intelligent vehicle highway systems; Aggregated datum; Data correlations; Data release; Differential privacies; Input datas; Intelligent transportation systems; Location data; Privacy leakages; Privacy mechanisms; Private information; Location
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 11 Jul 2024 01:22
Last Modified: 11 Jul 2024 01:22
URI: http://eprints.um.edu.my/id/eprint/44740

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