An Optimization Framework for Cyber-Physical Vulnerability Analysis in Industrial Cyber-Physical Systems

Industrial Control Systems (ICSs) are widely used in critical infrastructures. These industrial facilities face various cyberattacks that may cause physical damage. With the increasing integration of the ICSs and information technology (IT) components, ensuring the security of ICSs is of paramount importance. Typically, a cyberattack in ICS aims to impose physical damage on the ICSs by exploiting a sequence of vulnerabilities that leads to compromising the system's sensors and/or controllers. Due to the physics of the ICSs operation, maliciously accessing different sensors or components may cause varying levels of risk. Therefore, identifying cyberattacks with the highest risks is essential for effectively designing detection schemes and mitigation strategies. In this paper, we develop an optimization-based holistic cybersecurity risk assessment framework by integrating the cyber and physical systems of ICSs to understand 1) the vulnerabilities of the ICS network with holistic consideration of cyber and physical components and their interactions, and 2) the attack strategies that can lead to significant physical damage to the critical assets in ICS. We formulate a novel optimization problem that accounts for the attacker's objective and limitation in both the physical and cyber systems of ICSs. This allows us to jointly model the interactions between the cyber and physical components and study the critical cyberattacks that cause the highest impact on the physical components under certain resource constraints. We verified the effectiveness of our proposed method in a numerical study, and the results show that a strategic attacker causes almost 19% further acceleration in the failure time of the physical system compared to a random attacker.