Artikel in Tagungsband INPROC-2016-11

Riaz, Zohaib; Dürr, Frank; Rothermel, Kurt: On the Privacy of Frequently Visited User Locations.
In: Proceedings of the Seventeenth International Conference on Mobile Data Management: MDM'16; Porto, Portugal, June 13-16, 2016.
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 1-10, englisch.
Porto, Portugal: IEEE Computer Society, 13. Juni 2016.
Artikel in Tagungsband (Konferenz-Beitrag).
KörperschaftIEEE International Conference on Mobile Data Management
CR-Klassif.K.4.1 (Computers and Society Public Policy Issues)
C.2.4 (Distributed Systems)
KeywordsLocation Privacy, Location-based Applications, Semantic Locations, Visit-Frequency, Frequent locations, Geo-social networking, Location Servers, Non-trusted systems

With the fast adoption of location-enabled devices, Location-based Applications (LBAs) have become widely popular. While LBAs enable highly useful concepts such as geo-social networking, their use also raises serious privacy concerns as it involves sharing of location data with non-trusted third parties. In this respect, we propose an approach that protects the frequently visited locations of users, e.g., a bar, against inferences from longterm monitoring of their location data. Such inferences equate a privacy leak as they reveal a user’s personal behavior and interests to possibly malicious non-trusted parties.

To this end, we first present a study of a dataset of location check-ins to show the existence of this threat among users of LBAs. We then propose our approach to protect visit-frequency of the users to different locations by distributing their location data among multiple third-party Location Servers. This distribution not only serves to avoid a single point of failure for privacy in our system, it also allows the users to control which LBA accesses what information about them. We also describe a number of possible attacks against our privacy approach and evaluate them on real-data from the check-ins dataset. Our results show that our approach can effectively hide the frequent locations while supporting good quality-of-service for the LBAs.

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Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Verteilte Systeme
Eingabedatum11. April 2016
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