%0 Conference Proceedings
%T Uniform Obfuscation for Location Privacy
%+ Dipartimento di Ingegneria dell'Informazione [Pisa]
%A Dini, Gianluca
%A Perazzo, Pericle
%Z Part 3: Confidentiality and Privacy
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 26th Conference on Data and Applications Security and Privacy (DBSec)
%C Paris, France
%Y Nora Cuppens-Boulahia
%Y Frédéric Cuppens
%Y Joaquin Garcia-Alfaro
%I Springer
%3 Data and Applications Security and Privacy XXVI
%V LNCS-7371
%P 90-105
%8 2012-07-11
%D 2012
%R 10.1007/978-3-642-31540-4_7
%K location-based services
%K privacy
%K obfuscation
%K perturbation
%K uniformity
%Z Computer Science [cs]Conference papers
%X As location-based services emerge, many people feel exposed to high privacy threats. Privacy protection is a major challenge for such applications. A broadly used approach is perturbation, which adds an artificial noise to positions and returns an obfuscated measurement to the requester. Our main finding is that, unless the noise is chosen properly, these methods do not withstand attacks based on probabilistic analysis. In this paper, we define a strong adversary model that uses probability calculus to de-obfuscate the location measurements. Such a model has general applicability and can evaluate the resistance of a generic location-obfuscation technique. We then propose UniLO, an obfuscation operator which resists to such an adversary. We prove the resistance through formal analysis. We finally compare the resistance of UniLO with respect to other noise-based obfuscation operators.
%G English
%Z TC 11
%Z WG 11.3
%2 https://inria.hal.science/hal-01534755/document
%2 https://inria.hal.science/hal-01534755/file/978-3-642-31540-4_7_Chapter.pdf
%L hal-01534755
%U https://inria.hal.science/hal-01534755
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC11
%~ IFIP-WG11-3
%~ IFIP-DBSEC
%~ IFIP-LNCS-7371