Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems
The evaluation, importance and variation nature of multiple security and privacy properties are the main issues that make the benchmarking of blockchain-based IoT healthcare Industry 4.0 systems fall under the multi-criteria decision-making (MCDM) problem. In this article, one of the recent MCDM wei...
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| Format: | Article |
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Institute of Electrical and Electronics Engineers
2022
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| _version_ | 1796984206473035776 |
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| author | Qahtan, Sarah Sharif, Khaironi Yatim Zaidan, A. A. Alsattar, H. A. Albahri, O. S. Zaidan, B. B. Zulzalil, Hazura Osman, M. H. Alamoodi, A. H. Mohammed, R. T. |
| author_facet | Qahtan, Sarah Sharif, Khaironi Yatim Zaidan, A. A. Alsattar, H. A. Albahri, O. S. Zaidan, B. B. Zulzalil, Hazura Osman, M. H. Alamoodi, A. H. Mohammed, R. T. |
| author_sort | Qahtan, Sarah |
| collection | UPM |
| description | The evaluation, importance and variation nature of multiple security and privacy properties are the main issues that make the benchmarking of blockchain-based IoT healthcare Industry 4.0 systems fall under the multi-criteria decision-making (MCDM) problem. In this article, one of the recent MCDM weighting methods called fuzzy weighted with zero inconsistency (FWZIC) is effective for weighting the evaluation criteria subjectively without any inconsistency issues. However, considering the advantages of spherical fuzzy sets in providing a wide range of options to decision-makers and efficiently dealing with vagueness, hesitancy and uncertainty, this article formulated a new version of FWZIC for weighting the security and privacy properties, that is, spherical FWZIC (S-FWZIC). Moreover, an integrated MCDM framework was developed for benchmarking blockchain-based IoT healthcare Industry 4.0 systems on the basis of multi security and privacy properties. In the first phase of the methodology, a decision matrix is formulated based on the intersection of “blockchain-based Internet of Things healthcare Industry 4.0 systems” and “security and privacy properties” (i.e., user authentication, access control, privacy protection, integrity availability and anonymity). In the second phase, the weights of each security and privacy property are calculated through the S-FWZIC method. Then, these weights are employed to benchmark blockchain-based IoT healthcare Industry 4.0 systems through the combined grey relational analysis–technique for order of preference by similarity to ideal solution (GRA-TOPSIS) and the bald eagle search (BES) optimization method. Results indicate the following: First, the S-FWZIC method efficiently weighs the security and privacy properties, indicating that access control has the highest significance weight of 0.2070, while integrity has the lowest weight (0.0646); and second, the combination of the GRA-TOPSIS and the BES optimization method effectively ranks ... |
| first_indexed | 2024-03-06T11:17:11Z |
| format | Article |
| id | upm.eprints-102331 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-03-06T11:17:11Z |
| publishDate | 2022 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | upm.eprints-1023312023-07-10T00:45:43Z http://psasir.upm.edu.my/id/eprint/102331/ Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems Qahtan, Sarah Sharif, Khaironi Yatim Zaidan, A. A. Alsattar, H. A. Albahri, O. S. Zaidan, B. B. Zulzalil, Hazura Osman, M. H. Alamoodi, A. H. Mohammed, R. T. The evaluation, importance and variation nature of multiple security and privacy properties are the main issues that make the benchmarking of blockchain-based IoT healthcare Industry 4.0 systems fall under the multi-criteria decision-making (MCDM) problem. In this article, one of the recent MCDM weighting methods called fuzzy weighted with zero inconsistency (FWZIC) is effective for weighting the evaluation criteria subjectively without any inconsistency issues. However, considering the advantages of spherical fuzzy sets in providing a wide range of options to decision-makers and efficiently dealing with vagueness, hesitancy and uncertainty, this article formulated a new version of FWZIC for weighting the security and privacy properties, that is, spherical FWZIC (S-FWZIC). Moreover, an integrated MCDM framework was developed for benchmarking blockchain-based IoT healthcare Industry 4.0 systems on the basis of multi security and privacy properties. In the first phase of the methodology, a decision matrix is formulated based on the intersection of “blockchain-based Internet of Things healthcare Industry 4.0 systems” and “security and privacy properties” (i.e., user authentication, access control, privacy protection, integrity availability and anonymity). In the second phase, the weights of each security and privacy property are calculated through the S-FWZIC method. Then, these weights are employed to benchmark blockchain-based IoT healthcare Industry 4.0 systems through the combined grey relational analysis–technique for order of preference by similarity to ideal solution (GRA-TOPSIS) and the bald eagle search (BES) optimization method. Results indicate the following: First, the S-FWZIC method efficiently weighs the security and privacy properties, indicating that access control has the highest significance weight of 0.2070, while integrity has the lowest weight (0.0646); and second, the combination of the GRA-TOPSIS and the BES optimization method effectively ranks ... Institute of Electrical and Electronics Engineers 2022 Article PeerReviewed Qahtan, Sarah and Sharif, Khaironi Yatim and Zaidan, A. A. and Alsattar, H. A. and Albahri, O. S. and Zaidan, B. B. and Zulzalil, Hazura and Osman, M. H. and Alamoodi, A. H. and Mohammed, R. T. (2022) Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems. IEEE Transactions on Industrial Informatics, 18 (9). 6415 - 6423. ISSN 1551-3203; ESSN: 1941-0050 https://ieeexplore.ieee.org/document/9693264 10.1109/TII.2022.3143619 |
| spellingShingle | Qahtan, Sarah Sharif, Khaironi Yatim Zaidan, A. A. Alsattar, H. A. Albahri, O. S. Zaidan, B. B. Zulzalil, Hazura Osman, M. H. Alamoodi, A. H. Mohammed, R. T. Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems |
| title | Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems |
| title_full | Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems |
| title_fullStr | Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems |
| title_full_unstemmed | Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems |
| title_short | Novel multi security and privacy benchmarking framework for blockchain-based IoT healthcare industry 4.0 systems |
| title_sort | novel multi security and privacy benchmarking framework for blockchain based iot healthcare industry 4 0 systems |
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