Research Article
Trading Optimality for Performance in Location Privacy
@INPROCEEDINGS{10.4108/eai.5-12-2017.2274579, author={Konstantinos Chatzikokolakis and Serge Haddad and Ali Kassem and Catuscia Palamidessi}, title={Trading Optimality for Performance in Location Privacy}, proceedings={11th EAI International Conference on Performance Evaluation Methodologies and Tools}, publisher={ACM}, proceedings_a={VALUETOOLS}, year={2018}, month={8}, keywords={performance}, doi={10.4108/eai.5-12-2017.2274579} }- Konstantinos Chatzikokolakis
Serge Haddad
Ali Kassem
Catuscia Palamidessi
Year: 2018
Trading Optimality for Performance in Location Privacy
VALUETOOLS
ACM
DOI: 10.4108/eai.5-12-2017.2274579
Abstract
Location-Based Services (LBSs) provide invaluable assistance in our everyday activities, however they also pose serious threats to our privacy. Location data can, in fact, expose sensitive aspects of the user’s private life, see for instance [4]. There is, therefore, a growing interest in the development of mechanisms to protect location privacy during the use of LBSs. Most of the approaches in the literature are based on perturbing the user’s location, see, for instance, [1, 2, 5, 6]. Obviously, the perturbation must be done with care, in order to preserve the utility of the service.
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