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Protecting query privacy in location-based services / Xihui Chen in Geoinformatica, vol 18 n° 1 (January 2014)  

Public [article]  inGeoinformatica > vol 18 n° 1 (January 2014) . - pp 95 - 133 Titre : Protecting query privacy in location-based services Type de document : Article/Communication Auteurs : Xihui Chen, Auteur ; Jun Pang, Auteur Année de publication : 2014 Article en page(s) : pp 95 - 133 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Société de l'information [Termes IGN] métrique [Termes IGN] protection de la vie privée [Termes IGN] requête spatiale [Termes IGN] service fondé sur la position Résumé : (Auteur) The popularity of location-based services (LBSs) leads to severe concerns on users’ privacy. With the fast growth of Internet applications such as online social networks, more user information becomes available to the attackers, which allows them to construct new contextual information. This gives rise to new challenges for user privacy protection and often requires improvements on the existing privacy-preserving methods. In this paper, we classify contextual information related to LBS query privacy and focus on two types of contexts—user profiles and query dependency: user profiles have not been deeply studied in LBS query privacy protection, while we are the first to show the impact of query dependency on users’ query privacy. More specifically, we present a general framework to enable the attackers to compute a distribution on users with respect to issuing an observed request. The framework can model attackers with different contextual information. We take user profiles and query dependency as examples to illustrate the implementation of the framework and their impact on users’ query privacy. Our framework subsequently allows us to show the insufficiency of existing query privacy metrics, e.g., k-anonymity, and propose several new metrics. In the end, we develop new generalisation algorithms to compute regions satisfying users’ privacy requirements expressed in these metrics. By experiments, our metrics and algorithms are shown to be effective and efficient for practical usage. Numéro de notice : A2014-029 Affiliation des auteurs : non IGN Thématique : SOCIETE NUMERIQUE Nature : Article DOI : 10.1007/s10707-013-0192-0 Date de publication en ligne : 18/10/2013 En ligne : https://doi.org/10.1007/s10707-013-0192-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32934 [article]

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