Trading Optimality for Performance in Location Privacy

Konstantinos Chatzikokolakis; Serge Haddad; Ali Kassem; Catuscia Palamidessi

11th EAI International Conference on Performance Evaluation Methodologies and Tools

Research Article

Trading Optimality for Performance in Location Privacy

Cite: BibTeX Plain Text

@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

Konstantinos Chatzikokolakis¹, Serge Haddad², Ali Kassem³^,*, Catuscia Palamidessi³

1: CNRS and Ecole Polytechnique
2: ENS Cachan
3: INRIA and Ecole Polytechnique

*Contact email: ali.kassem@inria.fr

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.

Keywords: performance

Published: 2018-08-10
Publisher: ACM

: http://dx.doi.org/10.4108/eai.5-12-2017.2274579