Why to Fail Fast and Often: A Strategy for OT Safety and Security Evaluation

Abstract

As the Operational Technology (OT) environment becomes increasingly interconnected and integrates diverse technologies, traditional models often struggle to accurately represent the complex interactions and dependencies of the underlying systems. Factors like changes in operational conditions, software updates, and the introduction of new devices can significantly impact the system’s risk profile. This paper presents a methodology to bridge the gap between manual and automated safety and security requirements in Industry 4.0 OT environments. First, a meta-model is developed to capture OT infrastructure components and relationships. This is then transformed into a C#-based GUI, enabling tasks like network scanning, application and interface identification, and AI-powered data extraction. Next, compliance checks and risk assessments are conducted using standards such as IEC 62443-3-3 and methods like LOPA, SEFR (HAZID), STRIDE, and DREAD. Finally, the data is converted into system models (e.g., OWL, AutomationML) for visualization. This approach reduces complexity and time by 83.72%, though it faces challenges like platform dependency and resource constraints.