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Influence of tracking duration on the privacy of individual mobility graphs

Wiedemann, N; Martin, H; Suel, E; Hong, Y; Xin, Y; (2023) Influence of tracking duration on the privacy of individual mobility graphs. Journal of Location Based Services pp. 1-19. 10.1080/17489725.2023.2239190. (In press). Green open access

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Abstract

Location graphs, compact representations of human mobility without geocoordinates, can be used to personalise location-based services. While they are more privacy-preserving than raw tracking data, it was shown that they still hold a considerable risk for users to be re-identified solely by the graph topology. However, it is unclear how this risk depends on the tracking duration. Here, we consider a scenario where the attacker wants to match the new tracking data of a user to a pool of previously recorded mobility profiles, and we analyse the dependence of the re-identification performance on the tracking duration. We find that the re-identification accuracy varies between 0.41% and 20.97% and is affected by both the pool duration and the test-user tracking duration, it is greater if both have the same duration, and it is not significantly affected by socio-demographics such as age or gender, but can to some extent be explained by different mobility and graph features. Overall, the influence of tracking duration on user privacy has clear implications for data collection and storage strategies. We advise data collectors to limit the tracking duration or to reset user IDs regularly when storing long-term tracking data.

Type: Article
Title: Influence of tracking duration on the privacy of individual mobility graphs
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/17489725.2023.2239190
Publisher version: https://doi.org/10.1080/17489725.2023.2239190
Language: English
Additional information: © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/).
Keywords: Privacy, tracking datamobility graphstime dependencelocation privacy
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis
URI: https://discovery.ucl.ac.uk/id/eprint/10175356
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