Evidence map›Paper›PMID 39384960›Full record

ArticleScientific reports2024

Empowering decentralized identity systems for Web 3.0 in complex spherical fuzzy knowledge.

Masfa Nasrullah Ansari, Abdul Razaq, Hanan Alolaiyan, Umer Shuaib, Mohammed Abdullah Salman, Qin Xin

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Masfa Nasrullah AnsariDepartment of Mathematics, Government College University, Faisalabad, 38000, Pakistan.
Abdul RazaqDepartment of Mathematics, Division of Science and Technology, University of Education, Lahore, 54770, Pakistan.
Hanan AlolaiyanDepartment of Mathematics, College of Science, King Saud University, Riyadh, Saudi Arabia.
Umer ShuaibDepartment of Mathematics, Government College University, Faisalabad, 38000, Pakistan.
Mohammed Abdullah SalmanDepartment of Mathematics and Statistics, Amran University, Amran, Yemen. dr.msalman@amu.edu.ye.
Qin XinFaculty of Science and Technology, University of the Faroe Islands, Vestarabryggja 15, FO 100, Torshavn, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Web 3.0 network system, the next generation of the world wide web, incorporates new technologies and algorithms to enhance accessibility, decentralization, and security, mimicking human comprehension and enabling more personalized user interactions. The key component of this environment is decentralized identity management (DIM), embracing an identity and access management strategy that empowers computing devices and individuals to manage their digital personas. Aggregation operators (AOs) are valuable techniques that facilitate combining and summarizing a finite set of imprecise data. It is imperative to employ such operators to effectively address multicriteria decision-making (MCDM) issues. Yager operators have a significant extent of adaptability in managing operational environments and exhibit excellent effectiveness in addressing decision-making (DM) uncertainties. The complex spherical fuzzy (CSF) model is more effective in capturing and reflecting the known unpredictability in a DM application. This research endeavors to enhance the DM scenario of the Web 3.0 environment using Yager aggregation operators within the CSF environment. We present two innovative aggregation operators, namely complex spherical fuzzy Yager-ordered weighted averaging (CSFYOWA) and complex spherical fuzzy Yager-ordered weighted geometric (CSFYOWG) operators. We elucidate some structural characteristics of these operators and come up with an updated score function to rectify the drawbacks of the existing score function in the CSF framework. By utilizing newly proposed operators under CSF knowledge, we develop an algorithm for MCDM problems. In addition, we adeptly employ these strategies to handle the MCDM scenario, aiming to identify the optimal approach for ensuring the privacy of digital identity or data in the evolving landscape of the Web 3.0 era. Moreover, we undertake a comparative study to highlight the veracity and proficiency of the proposed techniques compared to the previously designed approaches.

Indexed as

Complex spherical fuzzy setsMulti-criteria decision-making problemsYager ordered weighted averaging operatorYager ordered weighted geometric operator

Identifiers

PMID39384960
PMCPMC11479633

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.