Motivation: Industrial control systems (ICS) are used to automate and monitor processes and equipment in various industries, such as energy, transportation, and manufacturing. These systems provide many benefits, but they can also be vulnerable to se- curity threats if not properly protected. Most ICS networks use protocols designed for controlled environments and do not have built-in security mechanisms. However, the increas- ing connectivity of ICS devices to networks and the internet creates opportunities for malicious actors to cause disruptions and malfunctions. In this study, we employed an empirical methodology to assess the potential vulnerabilities in existing ICS networks. Using network scanning techniques, we identi- fied vulnerable ICS devices according to the Purdue model, which considers the hierarchical structure of ICS networks and the different services that devices run on. Our evaluation showed that this method could effectively identify high-risk devices and prioritize them for security measures.
Acknowledgement: This work was done under the guidance of Prof. Saman Zonouz, and Prof. Paul Pearce at Georgia Tech.