Rossi, L;
Walker, J;
Musolesi, M;
(2015)
Spatio-temporal techniques for user identification by means of GPS mobility data.
EPJ Data Science
, 4
(11)
10.1140/epjds/s13688-015-0049-x.
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Abstract
One of the greatest concerns related to the popularity of GPS-enabled devices and applications is the increasing availability of the personal location information generated by them and shared with application and service providers. Moreover, people tend to have regular routines and be characterized by a set of “significant places”, thus making it possible to identify a user from his/her mobility data. In this paper we present a series of techniques for identifying individuals from their GPS movements. More specifically, we study the uniqueness of GPS information for three popular datasets, and we provide a detailed analysis of the discriminatory power of speed, direction and distance of travel. Most importantly, we present a simple yet effective technique for the identification of users from location information that are not included in the original dataset used for training, thus raising important privacy concerns for the management of location datasets.
| Type: | Article |
|---|---|
| Title: | Spatio-temporal techniques for user identification by means of GPS mobility data |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1140/epjds/s13688-015-0049-x |
| Publisher version: | http://dx.doi.org/10.1140/epjds/s13688-015-0049-x |
| Additional information: | © 2015 Rossi et al. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| Keywords: | GPS, privacy, identification |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1478184 |
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