Publication:
Bitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy sets

dc.citedby20
dc.contributor.authorMohammed Z.K.en_US
dc.contributor.authorZaidan A.A.en_US
dc.contributor.authorAris H.B.en_US
dc.contributor.authorAlsattar H.A.en_US
dc.contributor.authorQahtan S.en_US
dc.contributor.authorDeveci M.en_US
dc.contributor.authorDelen D.en_US
dc.contributor.authorid58314479500en_US
dc.contributor.authorid35070838500en_US
dc.contributor.authorid58314229900en_US
dc.contributor.authorid57196317038en_US
dc.contributor.authorid57223984929en_US
dc.contributor.authorid55734383000en_US
dc.contributor.authorid55887961100en_US
dc.date.accessioned2024-10-14T03:20:36Z
dc.date.available2024-10-14T03:20:36Z
dc.date.issued2023
dc.description.abstractMetaverse 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).en_US
dc.description.natureArticle in pressen_US
dc.identifier.doi10.1007/s10479-023-05421-3
dc.identifier.scopus2-s2.0-85162036004
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85162036004&doi=10.1007%2fs10479-023-05421-3&partnerID=40&md5=1e9cabbf999eb4f4e45cc1b653531a87
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34552
dc.publisherSpringeren_US
dc.relation.ispartofAll Open Access
dc.relation.ispartofHybrid Gold Open Access
dc.sourceScopus
dc.sourcetitleAnnals of Operations Research
dc.subjectanonymity privacy
dc.subjectBitcoin networks
dc.subjectDiophantine linear fuzzy sets
dc.subjectIndustry 5.0
dc.subjectMetaverse
dc.subjectMultiple attribute decision-making
dc.titleBitcoin network-based anonymity and privacy model for metaverse implementation in Industry 5.0 using linear Diophantine fuzzy setsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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