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Protecting location privacy: Optimal strategy against localization attacks

Shokri, Reza, Theodorakopoulos, Georgios ORCID:, Troncoso, Carmela, Hubaux, Jean-Pierre and Le Boudec, Jean-Yves 2012. Protecting location privacy: Optimal strategy against localization attacks. Presented at: 19th ACM Conference on Computer and Communications Security (CCS 2012), Raleigh, NC, USA, 16-18 October 2012. Published in: Yu, Ting, Danezis, George and Gligor, Virgil D. eds. Proceedings of the 2012 ACM Conference on Computer and Communications Security, CCS'12, Raleigh, NC, USA, October 16-18, 2012. ACM 2012. New York, NY: ACM, pp. 617-627. 10.1145/2382196.2382261

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The mainstream approach to protecting the location-privacy of mobile users in location-based services (LBSs) is to alter the users' actual locations in order to reduce the location information exposed to the service provider. The location obfuscation algorithm behind an effective location-privacy preserving mechanism (LPPM) must consider three fundamental elements: the privacy requirements of the users, the adversary's knowledge and capabilities, and the maximal tolerated service quality degradation stemming from the obfuscation of true locations. We propose the first methodology, to the best of our knowledge, that enables a designer to find the optimal LPPM for a LBS given each user's service quality constraints against an adversary implementing the optimal inference algorithm. Such LPPM is the one that maximizes the expected distortion (error) that the optimal adversary incurs in reconstructing the actual location of a user, while fulfilling the user's service-quality requirement. We formalize the mutual optimization of user-adversary objectives (location privacy vs. correctness of localization) by using the framework of Stackelberg Bayesian games. In such setting, we develop two linear programs that output the best LPPM strategy and its corresponding optimal inference attack. Our optimal user-centric LPPM can be easily integrated in the users' mobile devices they use to access LBSs. We validate the efficacy of our game theoretic method against real location traces. Our evaluation confirms that the optimal LPPM strategy is superior to a straightforward obfuscation method, and that the optimal localization attack performs better compared to a Bayesian inference attack.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA76 Computer software
Publisher: ACM
ISBN: 9781450316514
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Last Modified: 21 Oct 2022 10:01

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