Browsing by Author "Albelaihy, Abdullah"
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Item BL0T: A novel phase privacy-preserving framework for location-based services(MDPI, 2018) Albelaihy, Abdullah; Cazalas, Jonathan; Thayananthan, VijeyThe inherent challenge within the domain of location-based services is finding a delicate balance between user privacy and the efficiency of answering queries. Inevitably, security issues can and will arise as the server must be informed about the query location in order to provide accurate responses. Despite the many security advancements in wireless communication, servers may become jeopardized or become infected with malicious software. That said, it is possible to ensure queries do not generate fake responses that appear real; in fact, if a fake response is used, mechanisms can be employed for the user to identify the query's authenticity. Towards this end, the paper propose BLoom Filter Oblivious Transfer (BLOT), a novel phase privacy preserving framework for LBS that combines a Bloom filter hash function and the oblivious transfer protocol. These methods are shown to be useful in securing a user's private information. An analysis of the results revealed that BLOT performed markedly better and enhanced entropy when compared to referenced approaches.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 Privacy-preserving queries for LBS: Independent secured hash function(Little Lion Scientific, 2018-06-15) Albelaihy, Abdullah; Cazalas, Jonathan; Thayananthan, VijeyWhile location-based services have become ubiquitous, seemingly permeating our personal and professional lives, their inherent nature poses security risks to users, who are forced to reveal their highly-sensitive location data in order to make effective use of the service. Towards this end, a litany of techniques have been proposed to provide efficient answers for privacy-preserving queries in LBS. Spatial bloom filters were initially proposed as an efficient data structure used to manage special and geographic information in an space-efficient manner. Unfortunately, bloom filters suffer from two deficiencies: they leak at most one bit of information per query, and the hash functions require careful design and security analysis in order to be orthogonal and independent. In fact, developing quality hash function is paramount. We propose a method to automatically generate good, independent hash functions, with the goal of reducing information leakage. This means that even if one of the hash function is broken, for any reason, nothing can be learned about any other hash function. The results show that our proposed Hash functions are less dependent and leaked than the compared approach, while still seeing a notable improvement in performance.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.Item A survey: The current trends of privacy techniques for protecting the location privacy of users in LBS(Little Lion Scientific, 2018-08-15) Albelaihy, Abdullah; Cazalas, Jonathan; Thayananthan, VijeyWith GPS-enabled devices and data connectivity now ubiquitous, Location Based Services (LBSs) have seemingly penetrated all aspects of our lives. While profoundly valuable, these services expose the user to a litany of privacy and security issues. LBS users must reveal their location, and at times other sensitive personal information, in order to effectively use the service and receive accurate results. 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 efficacy, or otherwise, of each technique discussed in this paper, with each technique having been evaluated based on accuracy, quality, efficiency, flexibility, location privacy, and query privacy. The outcome of this study is a taxonomy of current privacy and security techniques, which will assist researchers and developers as they look to further protect the sensitive information of their customer base.