The rampant increase in frequency and complexity of cyber-attacks against manufacturing firms, has motivated the development of identification and mitigation techniques for cyber-physical vulnerabilities in manufacturing. While the field of cybersecurity assessment approaches is expansive, there is no literature aimed at assessing cyber-physical vulnerabilities for manufacturing systems. In response, this paper provides a framework for systematically identifying cyber-physical vulnerabilities in manufacturing systems. The proposed approach employs intersection mapping to identify cyber-physical vulnerabilities in manufacturing. A cyber-physical vulnerability impact analysis using decision trees then provides the manufacturer with a stoplight scale between low, medium, and high levels of cyber-physical vulnerability for each analyzed production process. The stoplight scale allows manufacturers to interpret assessment results in an intuitive way. Finally, the paper provides a case study of the proposed approach at an applied manufacturing research facility and provides general recommendations to securing similar facilities from cyber-physical attacks.

Modern manufacturing systems utilise cyber-physical systems that are interconnected through an Internet of Things (IoT) network. An IoT infrastructure enables cyber-physical systems to communicate with each other and coordinate the manufacturing process autonomously with minimal human assistance. A significant challenge for cyber-physical systems is cybersecurity. Adversaries can exploit weaknesses in the IoT security infrastructure to gain remote access to the system and modify or damage manufacturing processes and/or products. Due to the autonomous nature of cyber-physical systems, cyberattacks can go unnoticed by the users for a long time, further compounding the problem. Attacks on cyber-physical systems are on the rise, and manufacturers need to address this problem. In this article, we discuss how game-theoretic thinking and modelling can help to identify a manufacturer’s cyber vulnerabilities and enhance its security. We consider various attack and defence scenarios and analyse each through the corresponding game-theoretic model. Our approach and findings can be used to improve the effectiveness and efficiency of security strategies for cyber-physical manufacturing systems.