A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 Systems
E-health Industry 4.0 systems ranking based on Blockchain is a multi-criteria decision-making (MCDM) problem, considering the multiple evaluation properties, their significance, and data variety. The final closeness between the evaluation sample and ideal solutions also constitutes an optimisation...
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| Format: | Article |
| Language: | English |
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middle technical university
2023-12-01
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| Series: | Journal of Techniques |
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| Online Access: | https://journal.mtu.edu.iq/index.php/MTU/article/view/1464 |
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| author | Sarah Qahtan Khaironi Yatim Mohd Hafeez Osman Hazura Zulzalil Muhammad Luqman Mahamad Zakaria |
| author_facet | Sarah Qahtan Khaironi Yatim Mohd Hafeez Osman Hazura Zulzalil Muhammad Luqman Mahamad Zakaria |
| author_sort | Sarah Qahtan |
| collection | DOAJ |
| description |
E-health Industry 4.0 systems ranking based on Blockchain is a multi-criteria decision-making (MCDM) problem, considering the multiple evaluation properties, their significance, and data variety. The final closeness between the evaluation sample and ideal solutions also constitutes an optimisation problem. To the authors’ knowledge, no study has provided a multi-privacy and security ranking approach solution for E-health Industry 4.0 systems based on Blockchain. Consequently, this study proposes and discusses a multi-privacy and security ranking approach solution for E-health Industry 4.0 systems, utilising the SFS-FWZIC method to address the significance of properties issue and the Grey-TOPSIS method to tackle data variation, multiple evaluation properties, and the ideal solutions optimisation problem. The methodology of the proposed approach consists of three sections. First, three decision matrices are constructed based on the intersection of E-health systems with the mentioned properties, intersecting Electronic Health Records (EHRs), Electronic Medical Records (EMRs), and Personal Health Records (PHRs) with seven properties. Second, the weights of each privacy and security property are calculated using the SFS-FWZIC method. Finally, the weights determined by the SFS-FWZIC method and the three decision matrices are input into the Grey-TOPSIS method to rank E-health systems across the three categories. The findings reveal the following: (1) The SFS-FWZIC method effectively assigned weights to privacy and security properties, with access control achieving the highest significance weight (0.1934) and Secure-search receiving the lowest weight (0.0603). (2) The Grey-TOPSIS method efficiently ranked E-health systems across the three categories based on various parameters, including α=0.1,α=0.3,α=0.5,α=0.7, and α=0.9. Sensitivity and correlation analysis were conducted to evaluate the results, revealing high correlation results based on each α value across all discussed scenarios of changing property weights. The implications of this study can lead to better decision-making, improved security and privacy, increased competition, and widespread adoption, ultimately contributing to more efficient and effective healthcare delivery.
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| format | Article |
| id | doaj-art-558bcd596a2341b8a8a5edfc33f0dc62 |
| institution | Kabale University |
| issn | 1818-653X 2708-8383 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | middle technical university |
| record_format | Article |
| series | Journal of Techniques |
| spelling | doaj-art-558bcd596a2341b8a8a5edfc33f0dc622025-01-19T10:59:01Zengmiddle technical universityJournal of Techniques1818-653X2708-83832023-12-015410.51173/jt.v5i4.1464A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 SystemsSarah Qahtan0Khaironi Yatim1Mohd Hafeez Osman2Hazura Zulzalil3Muhammad Luqman Mahamad Zakaria4Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, MalaysiaFaculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang 43400, Malaysia E-health Industry 4.0 systems ranking based on Blockchain is a multi-criteria decision-making (MCDM) problem, considering the multiple evaluation properties, their significance, and data variety. The final closeness between the evaluation sample and ideal solutions also constitutes an optimisation problem. To the authors’ knowledge, no study has provided a multi-privacy and security ranking approach solution for E-health Industry 4.0 systems based on Blockchain. Consequently, this study proposes and discusses a multi-privacy and security ranking approach solution for E-health Industry 4.0 systems, utilising the SFS-FWZIC method to address the significance of properties issue and the Grey-TOPSIS method to tackle data variation, multiple evaluation properties, and the ideal solutions optimisation problem. The methodology of the proposed approach consists of three sections. First, three decision matrices are constructed based on the intersection of E-health systems with the mentioned properties, intersecting Electronic Health Records (EHRs), Electronic Medical Records (EMRs), and Personal Health Records (PHRs) with seven properties. Second, the weights of each privacy and security property are calculated using the SFS-FWZIC method. Finally, the weights determined by the SFS-FWZIC method and the three decision matrices are input into the Grey-TOPSIS method to rank E-health systems across the three categories. The findings reveal the following: (1) The SFS-FWZIC method effectively assigned weights to privacy and security properties, with access control achieving the highest significance weight (0.1934) and Secure-search receiving the lowest weight (0.0603). (2) The Grey-TOPSIS method efficiently ranked E-health systems across the three categories based on various parameters, including α=0.1,α=0.3,α=0.5,α=0.7, and α=0.9. Sensitivity and correlation analysis were conducted to evaluate the results, revealing high correlation results based on each α value across all discussed scenarios of changing property weights. The implications of this study can lead to better decision-making, improved security and privacy, increased competition, and widespread adoption, ultimately contributing to more efficient and effective healthcare delivery. https://journal.mtu.edu.iq/index.php/MTU/article/view/1464E-Health SystemsIndustry 4.0Multi-Criteria Decision-MakingSecurityPrivacy |
| spellingShingle | Sarah Qahtan Khaironi Yatim Mohd Hafeez Osman Hazura Zulzalil Muhammad Luqman Mahamad Zakaria A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 Systems Journal of Techniques E-Health Systems Industry 4.0 Multi-Criteria Decision-Making Security Privacy |
| title | A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 Systems |
| title_full | A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 Systems |
| title_fullStr | A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 Systems |
| title_full_unstemmed | A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 Systems |
| title_short | A Decision Cloud Ranking Approach Based on Privacy and Security in Blockchain E-Health Industry 4.0 Systems |
| title_sort | decision cloud ranking approach based on privacy and security in blockchain e health industry 4 0 systems |
| topic | E-Health Systems Industry 4.0 Multi-Criteria Decision-Making Security Privacy |
| url | https://journal.mtu.edu.iq/index.php/MTU/article/view/1464 |
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