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

Adriano Di Luzio 1 Aline Carneiro Viana 2 Konstantinos Chatzikokolakis 3 Georgi Dikov 4 Catuscia Palamidessi 3 Julinda Stefa 1
2 TRiBE - inTeRnet BEyond the usual
Inria Saclay - Ile de France
3 COMETE - Concurrency, Mobility and Transactions
Inria Saclay - Ile de France, LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
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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Submitted on : Tuesday, December 24, 2019 - 2:44:52 AM
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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. SIGSPATIAL 2019 - 7th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Nov 2019, Chicago, United States. pp.1-10, ⟨10.1145/3356994.3365498⟩. ⟨hal-02423337⟩

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