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Empowering decentralized identity systems for Web 3.0 in complex spherical fuzzy knowledge.
Masfa Nasrullah Ansari1, Abdul Razaq2, Hanan Alolaiyan3
1Department of Mathematics, Government College University, Faisalabad, 38000, Pakistan.
Scientific Reports
|October 9, 2024
Summary
This study introduces new Yager aggregation operators within the complex spherical fuzzy environment to improve decision-making for Web 3.0 decentralized identity management, enhancing digital privacy and security.
Area of Science:
- Computer Science
- Information Security
- Artificial Intelligence
Background:
- Web 3.0 emphasizes decentralization, security, and personalized user experiences.
- Decentralized Identity Management (DIM) is crucial for managing digital personas in Web 3.0.
- Multicriteria Decision-Making (MCDM) challenges require robust aggregation techniques for imprecise data.
Purpose of the Study:
- To enhance Web 3.0 decision-making scenarios using Yager aggregation operators within the Complex Spherical Fuzzy (CSF) environment.
- To introduce novel aggregation operators, Complex Spherical Fuzzy Yager-Ordered Weighted Averaging (CSFYOWA) and Complex Spherical Fuzzy Yager-Ordered Weighted Geometric (CSFYOWG).
- To develop an algorithm for MCDM problems and apply it to optimize digital identity and data privacy in Web 3.0.
Main Methods:
- Development of two new aggregation operators: CSFYOWA and CSFYOWG.
- Elucidation of structural characteristics and an updated score function for the CSF framework.
- Application of proposed operators and algorithm to solve MCDM problems in Web 3.0 privacy preservation.
Main Results:
- Introduction of novel CSFYOWA and CSFYOWG operators with improved score function for CSF.
- Development of an effective MCDM algorithm tailored for Web 3.0 privacy challenges.
- Demonstration of the proposed techniques' efficacy through comparative analysis.
Conclusions:
- The proposed Yager aggregation operators and MCDM algorithm offer a significant advancement for decision-making in Web 3.0 environments.
- These methods effectively address uncertainties and enhance privacy solutions for digital identity and data.
- The research validates the superiority of the novel techniques over existing approaches for Web 3.0 applications.
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