Faculty of Science

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The Faculty of Science (FSCI) provides students with the tools needed to adapt to future developments in the scientific path of their choice. Areas of study include applied & industrial mathematics, chemistry, integrative neuroscience, forensic science, computer science and physics.

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Browsing Faculty of Science by Author "Alharbi, Khalid"

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    A framework for privacy-preserving data sharing in smart grid
    (2016-01-01) Alharbi, Khalid; Lin, Xiaodong
    While smart grid introduces a lot of enhancements to the traditional power grid and improves managing and controlling consumers demands, it also introduces security and privacy issues. Therefore, failure to address them will hinder the flourish of smart grid. In this thesis, we propose a novel framework for privacy-preserving data sharing in smart grid using a combination of homomorphic encryption and proxy re-encryption. The proposed framework allows distributed energy resources to be able to analyze the consumers data while preserving the consumers privacy. To the best of our knowledge, the proposed framework is first attempt to consider an important problem concerning data sharing in smart grid. Furthermore, in order to effectively collect consumer (or household) electricity consumption data, we also propose an efficient lightweight privacy- preserving data aggregation scheme, called ELPDA, for smart grid. The proposed scheme aims at resolving the power consumption data security and residential consumer privacy by employing one-time masking technique to protect consumers privacy while achieving lightweight data aggregation. Moreover, we study the situation in which gateways aggregating consumers’ data become malicious. Then, we propose a security-enhanced data aggregation scheme for smart grid communications from a homomorphic cryptosystem, trapdoor hash functions and homomorphic authenticators. The distinctive feature of our scheme achieves data confidentiality and integrity against the malicious aggregator (e.g. gateway), meaning that the aggregator is not able to learn the privacy of users or corrupt the power consumption reports during the aggregation process. In addition to the above schemes for smart grid upnlink communications, we propose an efficient and privacy-preserving scheme in order to protect smart grid in downlink communications. Specifically, we propose an efficient identity based signcryption, called EIBSC, providing privacy preservation in downlink communication for smart grids. The proposed scheme is characterized by employing the concealing destination technique on the tree-based network to protect consumer privacy in downlink communication. Furthermore, the proposed scheme employs identity based signcryption to efficiently achieve downlink message source authentication, data integrity and confidentiality. Additionally, compared to other identity-based signcryption schemes, the proposed scheme is more efficient in regards to computational overhead and ciphertext size. Furthermore, security analysis demonstrates that the proposed scheme is resilient against various security threats to smart grids.