Evaluating Blockchain Cybersecurity Based on Tree Soft and Opinion Weight Criteria Method under Uncertainty Climate

Abstract

In the era of digital transformation (DT), many digital technologies have emerged and have had a positive impact on society. Nevertheless, because of certain issues with existing technologies, innovative technology has developed to eradicate them. Fog computing (FC) plays a vital role as an intermediate between edge layer and cloud computing (CC) to resolve limited resources and capabilities. In the same vein, blockchain technology (BCT) is responsible for resolving privacy and security issues that IoT suffers from. Due to using cryptography rules and hashing which is utilized in BCT to prevent any trickery. Hence, BC shows promise as a possible remedy for the cybersecurity issue, especially in financial services and transactions. In the context of cybersecurity, it's critical to comprehend how financial sector businesses might handle these issues by investigating the use of BCT for financial transactions. Thereby, we constructed Tree Soft Evaluator (TrSEV) framework to evaluate security for enterprises (ENs) that embrace BCT as a cyber security method. The initial and important step in the evaluation process is determining the influenced criteria. In our problem, we modeled the determined criteria of BCT in Tree soft (TrSo) model. After that these criteria are analyzed and obtaining weights for it. Hence, we harnessed Opinion Weight Criteria Method (OWCM) as a novel multi-criteria decision-making (MCDM) technique to obtain criteria weights, and weighted sum model (WSM) is utilized for ranking enterprises and recommending optimal and worst enterprise. Finally, the techniques harnessed in our constructed framework are employed under the authority of Neutrosophic theory, precisely Single value Neutrosophic sets (SVNSs).