Private blockchain-based encryption framework using computational intelligence approach

Ghazal, T M, Hasan, Mohammad Kamrul, Sheikh Abdullah, Siti Norul Huda, Abu Bakar, Khairul Azmi and Al Hamadi, Hussam Private blockchain-based encryption framework using computational intelligence approach. Egyptian Informatics Journal, 23 (4). pp. 69-75. ISSN 1110-8665

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Abstract

Electronic Health monitoring system has performed an essential role in managing healthcare monitoring. E-health can provide effective and valuable facilities for the patients to monitor. Though, there are protection disputes in the current E-Health system. The current e-health system, on the other hand, has security issues. Malevolent doctors may work together with cloud Storage Service Providers (CSPs) to interfere with patients' electronic health records (EHRs) or promptly leak EHR matter to other enemies for income. (EHRs). The malevolent doctors may conspire with the Patient Healthcare Monitoring Service Provider (PHMSP) to manipulate with the patients'. For profit, EHRs or directly divulge the EHR content of EHRs to other opponents. Block-chain has recently appeared as one of the most powerful methods in the protection and secrecy fields. It is assumed to be the promised security approach that will eventually replace the security challenges in existing e-health monitoring systems. Encryption in blockchain refers to technical methods that make accessing encrypted data difficult for unauthorized resources. This research proposed a blockchain-based encryption framework to provide security-based solutions using a computational intelligence methodology. The proposed approach provides better results in terms of 0.93 in the training phase and 0.91 in the validation accuracy.

Affiliation: Skyline University College
SUC Author(s): Ghazal, T M ORCID: https://orcid.org/0000-0003-0672-7924
All Author(s): Ghazal, T M, Hasan, Mohammad Kamrul, Sheikh Abdullah, Siti Norul Huda, Abu Bakar, Khairul Azmi and Al Hamadi, Hussam
Item Type: Article
Uncontrolled Keywords: Private blockchain, Computational Intelligence, Machine Learning
Subjects: B Information Technology > BL Machine Learning
B Information Technology > BM Artificial Intelligence
B Information Technology > BS Blockchain
Divisions: Skyline University College > School of IT
Depositing User: Mr Mosys Team
Date Deposited: 25 Dec 2023 13:49
Last Modified: 25 Dec 2023 13:49
URI: https://research.skylineuniversity.ac.ae/id/eprint/650
Publisher URL: https://doi.org/10.1016/j.eij.2022.06.007
Publisher OA policy: https://v2.sherpa.ac.uk/id/publication/17760
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