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Blind evaluation of location based queries using space transformation to preserve location privacy / Ali Khshgozaran in Geoinformatica, vol 17 n° 4 (October 2013)  

Public [article]  inGeoinformatica > vol 17 n° 4 (October 2013) . - pp 599 - 634 Titre : Blind evaluation of location based queries using space transformation to preserve location privacy Type de document : Article/Communication Auteurs : Ali Khshgozaran, Auteur ; Houtan Shirani-Mehr, Auteur ; Cyrus Shahabi, Auteur Année de publication : 2013 Article en page(s) : pp 599 - 634 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] espace de Hilbert [Termes IGN] géopositionnement [Termes IGN] plus proche voisin, algorithme du [Termes IGN] protection de la vie privée [Termes IGN] requête spatiale [Termes IGN] service fondé sur la position [Termes IGN] utilisateur Résumé : (Auteur) In this paper, we propose a fundamental approach to perform the class of Range and Nearest Neighbor (NN) queries, the core class of spatial queries used in location-based services, without revealing any location information about the query in order to preserve users’ private location information. The idea behind our approach is to utilize the power of one-way transformations to map the space of all objects and queries to another space and resolve spatial queries blindly in the transformed space. Traditional encryption based techniques, solutions based on the theory of private information retrieval, or the recently proposed anonymity and cloaking based approaches cannot provide stringent privacy guarantees without incurring costly computation and/or communication overhead. In contrast, we propose efficient algorithms to evaluate KNN and range queries privately in the Hilbert transformed space. We also propose a dual curve query resolution technique which further reduces the costs of performing range and KNN queries using a single Hilbert curve. We experimentally evaluate the performance of our proposed range and KNN query processing techniques and verify the strong level of privacy achieved with acceptable computation and communication overhead. Numéro de notice : A2013-511 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-012-0172-9 Date de publication en ligne : 29/11/2012 En ligne : https://doi.org/10.1007/s10707-012-0172-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32649 [article]

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