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Empowering decentralized identity systems for Web 3.0 in complex spherical fuzzy knowledge.
Ansari, Masfa Nasrullah; Razaq, Abdul; Alolaiyan, Hanan; Shuaib, Umer; Salman, Mohammed Abdullah; Xin, Qin.
Affiliation
  • Ansari MN; Department of Mathematics, Government College University, Faisalabad, 38000, Pakistan.
  • Razaq A; Department of Mathematics, Division of Science and Technology, University of Education, Lahore, 54770, Pakistan.
  • Alolaiyan H; Department of Mathematics, College of Science, King Saud University, Riyadh, Saudi Arabia.
  • Shuaib U; Department of Mathematics, Government College University, Faisalabad, 38000, Pakistan.
  • Salman MA; Department of Mathematics and Statistics, Amran University, Amran, Yemen. dr.msalman@amu.edu.ye.
  • Xin Q; Faculty of Science and Technology, University of the Faroe Islands, Vestarabryggja 15, FO 100, Torshavn, Denmark.
Sci Rep ; 14(1): 23590, 2024 Oct 09.
Article in En | MEDLINE | ID: mdl-39384960
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep / Sci. rep. (Nat. Publ. Group) / Scientific reports (Nature Publishing Group) Year: 2024 Document type: Article Affiliation country: Pakistan Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep / Sci. rep. (Nat. Publ. Group) / Scientific reports (Nature Publishing Group) Year: 2024 Document type: Article Affiliation country: Pakistan Country of publication: United kingdom