Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/9735
Title: Big Data Analytics and Data Security in the Cloud via Fully Homomorphic Encryption
Authors: Victor, Onomza Waziri
John, K. Alhassan
Ismaila, Idris
Moses, Noel Dogonyaro
Keywords: Data Analytics, Security, Privacy, Bootstrapping, and Fully Homomorphic Encryption Scheme.
Issue Date: 2015
Publisher: World Academy of Science, Engineering and Technology International Journal of Computer and Information Engineering
Abstract: This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/9735
Appears in Collections:Cyber Security Science

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