Application of a fuzzy analytic hierarchy process to select the level of a cyber resilient capability maturity model in digital supply chain systems

Abstract

Cyber resilience has emerged over the past few years because traditional cybersecurity measures are no longer enough to protect organizations from persistent attacks. The cyber-resilient capability maturity model is a crucial element within an effective digital supply chain with six components: identify, protect, detect, respond, recover, and continuity, which affect the cybersecurity of the organization. To measure the maturity level requires a holistic approach, the analytic hierarchy process (AHP) method, which allows both for using multiple criteria and also for simultaneous evaluation. Generally, the factors affecting cyber resilience in digital supply chains have non-physical structures. Therefore, the real problem is represented in a better way by using fuzzy numbers instead of constant numbers to evaluate these factors. In this study, a fuzzy AHP approach is proposed to determine the cyber resilient capability maturity level in the digital supply chain. The proposed method is applied in 9 SME companies to test the assessments. In the application, factors are weighted with fuzzy triangular numbers in pairwise comparisons. The result indicates that the weight factors from comparing the relationship of all factors put the importance of the identify factors first, followed by protect, detect, respond, recover, and continuity, respectively.