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

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Location-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.
Data privacy, Location-based services, Mobile computing
Albelaihy, 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.