Query Privacy in Sensing-as-a-Service Platforms - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2017

Query Privacy in Sensing-as-a-Service Platforms

Résumé

The Internet of Things (IoT) promises to revolutionize the way we interact with the physical world. Even though this paradigm is still far from being completely realized, there already exist Sensing-as-a-Service (S$$^2$$2aaS) platforms that allow users to query for IoT data. While this model offers tremendous benefits, it also entails increasingly challenging privacy issues. In this paper, we concentrate on the protection of user privacy when querying sensing devices through a semi-trusted S$$^2$$2aaS platform. In particular, we build on techniques inspired by proxy re-encryption and k-anonymity to tackle two intertwined problems, namely query privacy and query confidentiality. The feasibility of our solution is validated both analytically and empirically.
Fichier principal
Vignette du fichier
449885_1_En_10_Chapter.pdf (235.39 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01648989 , version 1 (27-11-2017)

Licence

Paternité

Identifiants

Citer

Ruben Rios, David Nuñez, Javier Lopez. Query Privacy in Sensing-as-a-Service Platforms. 32th IFIP International Conference on ICT Systems Security and Privacy Protection (SEC), May 2017, Rome, Italy. pp.141-154, ⟨10.1007/978-3-319-58469-0_10⟩. ⟨hal-01648989⟩
89 Consultations
90 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More