Security is becoming increasingly relevant for the secure and resilient operation of industrial production facilities, as attacks with malware, for example, pose an existential threat to companies. An important key element in the area of security is security evaluations based on a risk assessment to identify, evaluate and assess all threats, vulnerabilities and resulting risks. Through subsequent risk mitigation, risks can be specifically reduced to an acceptable residual risk.
However, current analyses and certifications in the area of security are very time and resource consuming, as they have so far been carried out manually by experts. In the it's OWL project SUSI, a software and machine learning-based support of risk assessments for industrial production facilities is therefore to be developed in order to increase the degree of automation and relieve experts of routine tasks. The inIT and the project partners Weidmüller GmbH & Co KG, rt-solutions.de GmbH and Comma Soft AG see great potential here.