Cyberattacks on control systems in the chemical process industries cause concern regarding how they can impact finances, safety, and production levels of companies. A key practical challenge for cyberattack detection and handling using process information is that process behavior evolves over time. Conceivably, changes in process dynamics might cause some detection strategies to flag a change in the dynamics as an attack due to the new data appearing abnormal compared to data from before the dynamics changed. In this work, we utilize several case studies to probe the question of what might be the impacts, benefits, and limitations of cyberattack detection and handling policies when the process dynamics change over time. The goal of this work is to characterize, through simulation studies, characteristics, which might be desirable and undesirable in cyberattack detection and handling procedures when

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The controllers for a cyber-physical system may be impacted by sensor measurement cyberattacks, actuator signal cyberattacks, or both types of attacks. Prior work in our group has developed a theory for handling cyberattacks on process sensors. However, sensor and actuator cyberattacks have a different character from one another. Specifically, sensor measurement attacks prevent proper inputs from being applied to the process by manipulating the measurements that the controller receives, so that the control law plays a role in the impact of a given sensor measurement cyberattack on a process. In contrast, actuator signal attacks prevent proper inputs from being applied to a process by bypassing the control law to cause the actuators to apply undesirable control actions. Despite these differences, this manuscript shows that we can extend and combine strategies for handling sensor cyberattacks from our prior work to handle attacks on actuators and to handle cases where sensor and actuator attacks occur at the same time. These strategies for cyberattack-handling and detection are based on the Lyapunov-based economic model predictive control (LEMPC) and nonlinear systems theory. We first review our prior work on sensor measurement cyberattacks, providing several new insights regarding the methods. We then discuss how those methods can be extended to handle attacks on actuator signals and then how the strategies for handling sensor and actuator attacks individually can be combined to produce a strategy that is able to guarantee safety when attacks are not detected, even if both types of attacks are occurring at once. We also demonstrate that the other combinations of the sensor and actuator attack-handling strategies cannot achieve this same effect. Subsequently, we provide a mathematical characterization of the “discoverability” of cyberattacks that enables us to consider the various strategies for cyberattack detection presented in a more general context. We conclude by presenting a reactor example that showcases the aspects of designing LEMPC.