Digital Twin of Food Supply Chain for Cyber Exercises

Abstract

The food supply chain is a critical part of modern societies. As with other facets of life, it is thoroughly digitalized, and uses network connections. Consequently, the cyber security of the supply chain becomes a major concern as new threats emerge. Cyber ranges can be used to prepare for such cyber security threats by creating realistic scenarios mimicking real-world systems and setups. Organizations can participate in cyber security training and exercises that present them with these scenarios. Cyber ranges can also be used efficiently for research and development activities, because cyber ranges are realistic environments and can be used for the generation of realistic data. The aim of this study is to describe a digital twin of the food supply chain built for cyber range-based cyber security exercises. The digital twin mirrors the real-world situation with sufficient detail, as required by the cyber exercise. This research uses the design science methodology, which describes the construction and evaluation of the proposed system. The study explains the general capabilities of the food supply chain digital twin and its use in the cyber range environment. Different parts of the supply chain are implemented as Node.js services that run on the Realistic Global Cyber Environment (RGCE) platform. The flow of ingredients and products is simulated using an apparatus model and message queues. The digital twin was demonstrated in a real live cyber exercise. The results indicate that the apparatus approach was a scalable and realistic enough way to implement the digital twin. The main limitations of the implemented system are the implementation on one specific platform, and the need for more feedback from multiple exercises. Creation of a digital twin enables the use of cyber ranges to train organizations related to the food supply chain.