Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets
Metaverse is a new technology expected to generate economic growth in Industry 5.0. Numerous studies have shown that current bitcoin networks offer remarkable prospects for future developments involving metaverse with anonymity and privacy. Hence, modelling effective Industry 5.0 platforms for the b...
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2025
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| author | Mohammed Z.K. Zaidan A.A. Aris H.B. Alsattar H.A. Qahtan S. Deveci M. Delen D. |
| author2 | 58314479500 |
| author_facet | 58314479500 Mohammed Z.K. Zaidan A.A. Aris H.B. Alsattar H.A. Qahtan S. Deveci M. Delen D. |
| author_sort | Mohammed Z.K. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Metaverse is a new technology expected to generate economic growth in Industry 5.0. Numerous studies have shown that current bitcoin networks offer remarkable prospects for future developments involving metaverse with anonymity and privacy. Hence, modelling effective Industry 5.0 platforms for the bitcoin network is crucial for the future metaverse environment. This modelling process can be classified as multiple-attribute decision-making given three issues: the existence of multiple anonymity and privacy attributes, the uncertainty related to the relative importance of these attributes and the variability of data. The present study endeavours to combine the fuzzy weighted with zero inconsistency method and Diophantine linear fuzzy sets with multiobjective optimisation based on ratio analysis plus the multiplicative form (MULTIMOORA) to determine the ideal approach for metaverse implementation in Industry 5.0. The decision matrix for the study is built by intersecting 22 bitcoin networks to support Industry 5.0's metaverse environment with 24 anonymity and privacy evaluation attributes. The proposed method is further developed to ascertain the importance level of the anonymity and privacy evaluation attributes. These data are used in MULTIMOORA. A sensitivity analysis, correlation coefficient test and comparative analysis are performed to assess the robustness of the proposed method. ? The Author(s) 2023. |
| format | Article |
| id | my.uniten.dspace-36193 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Springer |
| record_format | dspace |
| spelling | my.uniten.dspace-361932025-03-03T15:41:32Z Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets Mohammed Z.K. Zaidan A.A. Aris H.B. Alsattar H.A. Qahtan S. Deveci M. Delen D. 58314479500 58789685700 13608397500 57196317038 57223984929 55734383000 55887961100 Metaverse is a new technology expected to generate economic growth in Industry 5.0. Numerous studies have shown that current bitcoin networks offer remarkable prospects for future developments involving metaverse with anonymity and privacy. Hence, modelling effective Industry 5.0 platforms for the bitcoin network is crucial for the future metaverse environment. This modelling process can be classified as multiple-attribute decision-making given three issues: the existence of multiple anonymity and privacy attributes, the uncertainty related to the relative importance of these attributes and the variability of data. The present study endeavours to combine the fuzzy weighted with zero inconsistency method and Diophantine linear fuzzy sets with multiobjective optimisation based on ratio analysis plus the multiplicative form (MULTIMOORA) to determine the ideal approach for metaverse implementation in Industry 5.0. The decision matrix for the study is built by intersecting 22 bitcoin networks to support Industry 5.0's metaverse environment with 24 anonymity and privacy evaluation attributes. The proposed method is further developed to ascertain the importance level of the anonymity and privacy evaluation attributes. These data are used in MULTIMOORA. A sensitivity analysis, correlation coefficient test and comparative analysis are performed to assess the robustness of the proposed method. ? The Author(s) 2023. Final 2025-03-03T07:41:32Z 2025-03-03T07:41:32Z 2024 Article 10.1007/s10479-023-05421-3 2-s2.0-85162036004 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162036004&doi=10.1007%2fs10479-023-05421-3&partnerID=40&md5=1e9cabbf999eb4f4e45cc1b653531a87 https://irepository.uniten.edu.my/handle/123456789/36193 342 2 1193 1233 All Open Access; Hybrid Gold Open Access Springer Scopus |
| spellingShingle | Mohammed Z.K. Zaidan A.A. Aris H.B. Alsattar H.A. Qahtan S. Deveci M. Delen D. Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets |
| title | Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets |
| title_full | Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets |
| title_fullStr | Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets |
| title_full_unstemmed | Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets |
| title_short | Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets |
| title_sort | bitcoin network-based anonymity and privacy model for metaverse implementation in industry 5.0 using linear diophantine fuzzy sets |
| url_provider | http://dspace.uniten.edu.my/ |