Configuration Security for Sustainable Digital Twins of Industrial Automation and Control Systems in Emerging Countries

Abstract

AbstractDigital twins (DTs) under industry 4.0 provide the manufacturing industry with the mapping relationship between products in physical space and virtual space, as well as the process of recording, simulating, and predicting the operation trajectory of the all life cycle of objects in the physical world and digital virtual space. This paper is to analyze and study the configuration security of industrial automation and control systems to contribute to the security of the world’s industrial control networks. Also, it is hoped to the world’s industries as soon as possible to get rid of the risk of invasion of industrial control systems. This paper uses an improved artificial bee colony (ABC) algorithm combined with support vector machine technology for research, and expects to achieve good attack detection results. In the case of small-scale data, the performance of this method is more general. However, in the case of large-scale data, the detection accuracy, false alarm rate, and detection time of this method are all excellent. Compared with other attack detection methods, the method proposed has certain advantages in various aspects. Security situation awareness can be used to detect, analyze, and visualize the security situation of industrial control network platform and data flow process, and analyze the security threat intelligence from the time and space dimensions through DTs technology. The attack detection method of industrial control system based on ABC algorithm can effectively detect the attack state, and provides an important theoretical basis for the research of attack detection methods.KeywordsIndustrial automationControl systemAttack detectionArtificial bee colony algorithm