An Integrated Cloud and Blockchain Enabled Platforms for Biomedical Research

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Date

2023

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Springer Science and Business Media Deutschland GmbH

Abstract

In the current pandemic scenario, healthcare data tends to be an important asset among organizations. The major challenge is to handle the data effectively while maintaining the privacy and security of the data. In a real-world, context healthcare data proves to be heterogeneous. Hence, managing such significance to big data has ardently laid numerous challenges among researchers and scientists around the globe. Cloud environment and blockchain technology can be discussed as usable platforms which can deliver a comprehensive centralized data privacy system. In the current approach study, we have integrated both technologies to provide usability in medical systems. Further, we have also proposed and implemented a blockchain application with an integrated cloud-based environment regarding heterogeneous medical databases. The study is proposed in 2 phases to maintain the privacy and the accessibility of the data. The double-spending problem is also presented, as mentioned above, using Blockchain’s consensus process. Each network node independently verifies the validity of individual transactions and entire blocks. As a result, there is no need to put faith in a single entity or other nodes. As a result, third parties are no longer required for network actions or blockchain management. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Keywords

Blockchain technology, Cloud environment, Healthcare databases, Medical system

Citation

Ghazal, T. M., Hasan, M. K., Abdullah, S. N. H. S., Bakar, K. A. A., Taleb, N., Al-Dmour, N. A., Yafi, E., Chauhan, R., Alzoubi, H. M. & Alshurideh, M. (2023). An Integrated Cloud and Blockchain Enabled Platforms for Biomedical Research. In M. Alshurideh, B.H. Al Kurdi, R. Masa’deh, H.M. Alzoubi, & S. Salloum (Eds.) The Effect of Information Technology on Business and Marketing Intelligence Systems. Studies in Computational Intelligence, 1056 (pp. 2037 - 2053). Cham: Springer. https://doi.org/10.1007/978-3-031-12382-5_111

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https://doi.org/10.1007/978-3-031-12382-5_111
 https://hdl.handle.net/20.500.12519/883

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