A novel secure privacy-preserving data sharing model with deep-based key generation on the blockchain network in the cloud

• Published in: Computer standards and interfaces Vol. 92; p. 103932
• Main Authors: B, Samuel, K, Kasturi
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-03-2025
• Subjects: Authentication; Cloud computing; Cloud service providers; Key Generation; SpinalNet; SpinalNet; Cloud computing; Key Generation; Authentication; Cloud service providers
• ISSN: 0920-5489
• DOI: 10.1016/j.csi.2024.103932

•Here, revenue distribution model depend on Multiple Services (MS).•Key generation is performed depend on the SpinalNet.•Data protection phase, includes encryption, hashing functions, passwords.•Authentication scheme done by cloud security on blockchain and smart contracts.
Cloud computing is currently emerging as a developing technology in which a Cloud Service Provider (CSP) is a third-party organization that provides effective storage of data and facilities to a large client base. Saving information in a cloud offers users the satisfaction of accessing it without the need for direct knowledge of the distribution and management of an infrastructure. The primary objective is to develop a novel, secure, and privacy-preserving data-sharing model that utilizes deep-based key generation on blockchain in the cloud. Data communication is done using multiple entities. The research aims to develop a collaborative data-sharing method in the cloud for the authentication scheme for cloud security on blockchain and smart contracts. Initialization, registration, key generation, authentication of data sharing, and validation are carried out here. The proposed data-sharing model involves a revenue distribution model that depends on Multiple Services (MS) models to improve multiple cloud services. The security parameters namely passwords, hashing functions, key interpolation, and encryption are used for preserving the Data privacy and here the SpinalNet is used for generating keys. Furthermore, the devised SpinalNet_Genkey obtained a value of 45.001 MB, 0.002, and 0.003 sec for memory usage, revenue, and computation cost.