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This collection includes scholarly output from both faculty and students in Computer Science.
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Browsing Computer Science by Subject "Mobile computing"
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Item Correlation analysis for geo-indistinguishability based continuous LBS queries(IEEE, 2017) Al-Dhubhani, Raed Saeed; Cazalas, JonathanThe popularity of mobile devices with positioning capability and Internet accessibility in recent years has caused a revolution in the Location Based Services (LBS) market. Unfortunately, without preserving the user's location privacy, LBS providers can collect and log the accurate locations of the service users. Many mechanisms have been developed to preserve the LBS user's location privacy. While said mechanisms have had demonstrable effectiveness with snapshot queries, the shortcoming of supporting continuous queries is their main drawback. Geo-indistinguishability represents an obfuscation-based location privacy notion, which preserves the user's accurate location while allowing an adequate amount of information to be released. Despite its effectiveness and simplicity, geo-indistinguishability notion does not address the potential correlation of the subsequent locations reported within the continuous queries. In this paper, we report our progress on developing an adaptive geo-indistinguishability mechanism for continuous LBS queries. We show the effect of exploiting the correlation of the user's obfuscated locations on the location privacy level. The initial results show the need for an adaptive mechanism that adjusts the amount of noise required to obfuscate the user's location based on the correlation level with its previous obfuscated locations.Item Leveraging computation sharing and parallel processing in location-based services(IEEE, 2009) Cazalas, Jonathan; Hua, KienA variety of research exists for the processing of continuous queries in large, mobile environments. Each method tries, in its own way, to address the computational bottleneck of constantly processing so many queries. In this paper, we introduce an efficient and scalable system for monitoring continuous queries by leveraging the parallel processing capability of the graphics processing unit. We examine a naive CPU-based solution for continuous range-monitoring queries, and we then extend this system using the GPU. Additionally, with mobile communication devices becoming commodity, location-based services will become ubiquitous. To cope with the very high intensity of location-based queries, we propose a view oriented approach of the location database, thereby reducing computation costs by exploiting computation sharing amongst queries requiring the same view. Our studies show that by exploiting the parallel processing power of the GPU, we are able to significantly scale the number of mobile objects, while maintaining an acceptable level of performance.Item Privacy preserving queries for LBS: Hash function secured (HFS)(IEEE, 2017) Albelaihy, Abdullah; Cazalas, JonathanLocation-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.Item A survey of the current trends of privacy techniques employed in protecting the Location privacy of users in LBSs(IEEE, 2017) Albelaihy, Abdullah; Cazalas, JonathanIn the age of the smartphone, Location Based Services (LBSs) have been immensely popular and changed the everyday routines of every individual user. However, an issue concerning the privacy and security of the user has been raised in the course of tracking the user as relevant and sensitive information about the user's location are revealed. This paper presents a survey of the current trends of privacy techniques employed in protecting the location privacy of users in LBSs. The paper further highlights the efficiency and deficiency of each technique discussed in this paper. The study, however, recommends that future researchers should endeavor to conduct a security analysis, simulation set-up and evaluate the proposed algorithm use of a modified Hilbert Curve to ensure the privacy efficiency of the proposed scheme.