A NOVEL FUZZY-INTEGRATED MCDM FRAMEWORK FOR SECURITY RISK WEIGHTAGE ESTIMATION, ASSESSMENT, AND COMPARISON OF VARIOUS BLOCKCHAIN WEB APPLICATIONS

Abstract Blockchain technology has transformed decentralized systems, yet it continues to be at risk to multiple security, centralization, and scalability challenges. This paper identifies and maps significant security considerations and sub-criteria for four prominent blockchain platforms— Ethereum, Solana, Hyperledger Fabric, and Algorand—through literature review and data consolidation. To mitigate these challenges, the paper proposes a novel Fuzzy-Integrated Multi Criteria Decision Making (MCDM) framework, called Fuzzy-Integrated Risk Mitigation Model (FIRMM), which involves the combination of the Fuzzy Delphi Method (FDM) for risk prioritization, Fuzzy Analytic Hierarchy Process (FAHP) to estimate the weighting of risk factors, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for mitigation selection. In addition to systematically validating the data through consistency ratio, sensitivity analysis, and expert validated using simulated and real-world datasets, FIRMM was applied using the blockchain platforms (Ethereum, Solana, Hyperledger Fabric, and Algorand) to compare risks and demonstrate risk-reduction with mitigation ranking correlations with expert judgment scoring as high as 85%. Overall, FIRMM provides a rigorous, empirically validated process to assist developers and blockchain platform stakeholders in decision-making and improving blockchain platform's resilience for a sustainable future.