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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Main Authors: Mohammed Z.K., Zaidan A.A., Aris H.B., Alsattar H.A., Qahtan S., Deveci M., Delen D.
Other Authors: 58314479500
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Published: Springer 2024
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spelling my.uniten.dspace-345522024-10-14T11:20:36Z 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 35070838500 58314229900 57196317038 57223984929 55734383000 55887961100 anonymity privacy Bitcoin networks Diophantine linear fuzzy sets Industry 5.0 Metaverse Multiple attribute decision-making 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. � 2023, The Author(s). Article in press 2024-10-14T03:20:36Z 2024-10-14T03:20:36Z 2023 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/123456789/34552 All Open Access Hybrid Gold Open Access Springer Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic anonymity privacy
Bitcoin networks
Diophantine linear fuzzy sets
Industry 5.0
Metaverse
Multiple attribute decision-making
spellingShingle anonymity privacy
Bitcoin networks
Diophantine linear fuzzy sets
Industry 5.0
Metaverse
Multiple attribute decision-making
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
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. � 2023, The Author(s).
author2 58314479500
author_facet 58314479500
Mohammed Z.K.
Zaidan A.A.
Aris H.B.
Alsattar H.A.
Qahtan S.
Deveci M.
Delen D.
format Article
author Mohammed Z.K.
Zaidan A.A.
Aris H.B.
Alsattar H.A.
Qahtan S.
Deveci M.
Delen D.
author_sort Mohammed Z.K.
title 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_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_sort bitcoin network-based anonymity and privacy model for metaverse implementation in industry 5.0 using linear diophantine fuzzy sets
publisher Springer
publishDate 2024
_version_ 1814060103659159552
score 13.209306