Assessment of Cybersecurity in Industry 4.0 using Delphi-Based Factor Relationships and Comprehensive Distance-Based Ranking Methods under Uncertainty

Abstract

Industry 4.0 is a new revolution in which internet connection technologies are interfaced with various components of industrial systems to create the smart factories and manufacturing organizations of the future to achieve a sustainable manufacturing framework. A large number of networked devices presents a significant chance to gather important data for improving the technology of decision-making to enhance product life-cycle management. Industry 4.0 technologies will face significant challenges and obstacles due to the cybersecurity and data privacy problems suffered by current Internet technology. In actuality, cybersecurity poses an important challenge to the advancement of sustainable manufacturing. Cybersecurity architectures are widely employed to prevent intrusions and attacks on computers and networks. As a result, there is a major decrease in the adoption of Industry 4.0 technologies and the sustainable manufacturing framework within organizations. To achieve the implementation of this sustainable manufacturing in companies we suggested five cybersecurity measures and six criteria. The proposed decision-making method aims to rank the cybersecurity procedures. The ranking of these measures used a combination of Delphi-FARE (factor relationship) and COBRA (comprehensive distance-based ranking) methods based on a neutrosophic environment. The result showed that alternative one “Data Encryptions” is the best one, and alternative five “Cloud Servers” is the worst one. We conducted a sensitivity and comparison analysis to verify the stability of the model and its performance with other models and demonstrated impressive results.