Location privacy without mutual trust: The spatial Bloom filter

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dc.contributor.authorCalderoni, Luca
dc.contributor.authorPalmieri, Paolo
dc.contributor.authorMaio, Dario
dc.date.accessioned2017-09-21T14:42:32Z
dc.date.available2017-09-21T14:42:32Z
dc.date.issued2015-06-25
dc.date.updated2017-09-20T15:29:33Z
dc.description.abstractLocation-aware applications are one of the biggest innovations brought by the smartphone era, and are effectively changing our everyday lives. But we are only starting to grasp the privacy risks associated with constant tracking of our whereabouts. In order to continue using location-based services in the future without compromising our privacy and security, we need new, privacy-friendly applications and protocols. In this paper, we propose a new compact data structure based on Bloom filters, designed to store location information. The spatial Bloom filter (SBF), as we call it, is designed with privacy in mind, and we prove it by presenting two private positioning protocols based on the new primitive. The protocols keep the user’s exact position private, but allow the provider of the service to learn when the user is close to specific points of interest, or inside predefined areas. At the same time, the points and areas of interest remain oblivious to the user. The two proposed protocols are aimed at different scenarios: a two-party setting, in which communication happens directly between the user and the service provider, and a three-party setting, in which the service provider outsources to a third party the communication with the user. A detailed evaluation of the efficiency and security of our solution shows that privacy can be achieved with minimal computational and communication overhead. The potential of spatial Bloom filters in terms of generality, security and compactness makes them ready for deployment, and may open the way for privacy preserving location-aware applications.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationCalderoni, L., Palmieri, P. and Maio, D. (2015) 'Location privacy without mutual trust: The spatial Bloom filter', Computer Communications, 68(Supplement C), pp. 4-16. doi:10.1016/j.comcom.2015.06.011en
dc.identifier.doi10.1016/j.comcom.2015.06.011
dc.identifier.endpage16en
dc.identifier.issn0140-3664
dc.identifier.journaltitleComputer Communicationsen
dc.identifier.startpage4en
dc.identifier.urihttps://hdl.handle.net/10468/4762
dc.identifier.volume68en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urihttp://www.sciencedirect.com/science/article/pii/S0140366415002273
dc.rights© 2015 Elsevier B.V. This manuscript version is made available under the CC-BY-NC-ND 4.0 licenseen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectLocation privacyen
dc.subjectBloom filtersen
dc.subjectSecure multi-party computationen
dc.titleLocation privacy without mutual trust: The spatial Bloom filteren
dc.typeArticle (peer-reviewed)en
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