Extended Privacy in Crowdsourced Location-Based Services Using Mobile Cloud Computing

Abstract : Crowdsourcing mobile applications are of increasing importance due to their suitability in providing personalized and better matching replies. The competitive edge of crowdsourcing is twofold; the requestors can achieve better and/or cheaper responses while the crowd contributors can achieve extra money by utilizing their free time or resources. Crowdsourcing location-based services inherit the querying mechanism from their legacy predecessors and this is where the threat lies. In this paper, we are going to show that none of the advanced privacy notions found in the literature except for í µí°¾-anonymity is suitable for crowdsourced location-based services. In addition, we are going to prove mathematically, using an attack we developed, that í µí°¾-anonymity does not satisfy the privacy level needed by such services. To respond to this emerging threat, we will propose a new concept, totally different from existing resource consuming privacy notions, to handle user privacy using Mobile Cloud Computing.
Type de document :
Article dans une revue
Mobile Information Systems, Hindawi/IOS Press, 2016, pp.7867206. 〈10.1155/2016/7867206〉
Liste complète des métadonnées

https://hal.sorbonne-universite.fr/hal-01365364
Contributeur : Gestionnaire Hal-Upmc <>
Soumis le : mardi 13 septembre 2016 - 14:00:29
Dernière modification le : jeudi 21 mars 2019 - 14:40:39
Document(s) archivé(s) le : mercredi 14 décembre 2016 - 13:31:13

Fichier

7867206.pdf
Publication financée par une institution

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Jacques Bou Abdo, Thomas Bourgeau, Jacques Demerjian, Hakima Chaouchi. Extended Privacy in Crowdsourced Location-Based Services Using Mobile Cloud Computing. Mobile Information Systems, Hindawi/IOS Press, 2016, pp.7867206. 〈10.1155/2016/7867206〉. 〈hal-01365364〉

Partager

Métriques

Consultations de la notice

559

Téléchargements de fichiers

320