Privacy preserving queries for LBS: Hash function secured (HFS)

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dc.contributor.authorAlbelaihy, Abdullah
dc.contributor.authorCazalas, Jonathan
dc.date.accessioned2022-06-25T21:26:19Z
dc.date.available2022-06-25T21:26:19Z
dc.date.issued2017
dc.description.abstractLocation-based services can be seen everywhere today in our smartphones and devices that use GPS, and this service has become invaluable to customers. LBSs, however, do have their flaws. Users are forced to reveal location data if they want to use the service, which can be a risk for their own privacy and security. Therefore, several techniques have been proposed in literature in order to provide an optimal solution for privacy preserving queries in LBS. This paper will firstly explore the use of bloom filters in existing research and their inherent limitation. While using Bloom Filers can be straightforward, finding good hash functions can be challenging. We propose a method to automatically generate good, independent hash functions, with the goal of reducing information leakage while also creating an automated performance measure.en_US
dc.identifier.citationAlbelaihy, A. & Cazalas, J. (2017, March 26-27). Privacy preserving queries for LBS: Hash function secured (HFS) [Conference paper]. 2017 2nd International Conference on Anti-Cyber Crimes (ICACC), Abha, Saudi Arabia. https://www.doi.org/10.1109/Anti-Cybercrime.2017.7905254en_US
dc.identifier.doihttps://doi.org/10.1109/Anti-Cybercrime.2017.7905254
dc.identifier.urihttp://hdl.handle.net/11416/655
dc.identifier.urihttps://doi.org/10.1109/Anti-Cybercrime.2017.7905254
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.subjectData privacyen_US
dc.subjectLocation-based servicesen_US
dc.subjectMobile computingen_US
dc.titlePrivacy preserving queries for LBS: Hash function secured (HFS)en_US
dc.typeOtheren_US

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