Multi-Cloud Data Management Using Shamir's Secret Sharing and Quantum Byzantine Agreement Schemes

Multi-Cloud Data Management Using Shamir's Secret Sharing and Quantum Byzantine Agreement Schemes

Mohammed A. AlZain (Taif University, Saudi Arabia), Alice S. Li (La Trobe University, Australia), Ben Soh (La Trobe University, Australia) and Eric Pardede (La Trobe University, Australia)
DOI: 10.4018/978-1-4666-9466-8.ch053
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Cloud computing is a phenomenal distributed computing paradigm that provides flexible, low-cost on-demand data management to businesses. However, this so-called outsourcing of computing resources causes business data security and privacy concerns. Although various methods have been proposed to deal with these concerns, none of these relates to multi-clouds. This paper presents a practical data management model in a public and private multi-cloud environment. The proposed model BFT-MCDB incorporates Shamir's Secret Sharing approach and Quantum Byzantine Agreement protocol to improve trustworthiness and security of business data storage, without compromising performance. The performance evaluation is carried out using a cloud computing simulator called CloudSim. The experimental results show significantly better performance in terms of data storage and data retrieval compared to other common cloud cryptographic based models. The performance evaluation based on CloudSim experiments demonstrates the feasibility of the proposed multi-cloud data management model.
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2. Background

Our proposed multi-cloud data management model uses Shamir’s Secret Sharing approach and a Quantum Byzantine Agreement protocol. We briefly describe below the background of these two crucial schemes to ensure data Confidentiality, Integrity and Availability (CIA).

2.1. Shamir’s Secret Sharing Approach

Agrawal et al. (2009) introduces Shamir’s secret sharing algorithm (1979) as a solution to the privacy issue. The algorithm proposes dividing the data D into (n) pieces (D1….Dn) in such a way that knowledge of any k or more of Di pieces makes the value of D known. Therefore, a complete knowledge of (k – 1) pieces reveals no information about D. k should be less than n to keep the value of shares un-constructible and ensure that the adversary cannot access k data pieces. Shamir’s method theoretically secures information.

In addition, by using a (k,n) threshold scheme with n = 2k – 1, In Agrawal et al. (2009), it is shown that a strong key management scheme can be achieved. The goal is to take a distributed approach to secure DaaS (Data as a Service), having the best of both worlds in the use of a secret-sharing approach and also multiple service platforms. With this approach, we can address both privacy-preserving querying and the data security of outsourced data.

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