Catch Me If You Can: How Geo-indistinguishability Affects Utility in Mobility-based Geographic Datasets - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2019

Catch Me If You Can: How Geo-indistinguishability Affects Utility in Mobility-based Geographic Datasets

Abstract

This paper sheds light on the trade-os between privacy and utility in mobility-based geographic datasets. We aim at nd-ing out whether it is possible to protect the privacy of the users in a dataset while, at the same time, maintaining intact the utility of the information that it contains. In particular, we focus on geo-indistinguishability as a privacy-preserving sanitization methodology, and we evaluate its eects on the utility of the Geolife dataset. We test the sanitized dataset in two real world scenarios: 1. Deploying an infrastructure of WiFi hotspots to ooad the mobile trac of users living, working, or commuting in a wide geographic area; 2. Simulating the spreading of a gossip-based epidemic as the outcome of a device-to-device communication protocol. We show the extent to which the current geo-indistinguishability techniques trade privacy for utility in real world applications and we focus on their eects at the levels of the population as a whole and of single individuals.
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Dates and versions

hal-02423337 , version 1 (24-12-2019)

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Adriano Di Luzio, Aline Carneiro Viana, Konstantinos Chatzikokolakis, Georgi Dikov, Catuscia Palamidessi, et al.. Catch Me If You Can: How Geo-indistinguishability Affects Utility in Mobility-based Geographic Datasets. LocalRec2019 workshop, jointly with ACM SIGSPATIAL 2019, Nov 2019, Chicago, United States. pp.1-10, ⟨10.1145/3356994.3365498⟩. ⟨hal-02423337⟩
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