Mitigating Safety Concerns and Profit/Production Losses for Chemical Process Control Systems under Cyberattacks via Design/Control Methods

Abstract

One of the challenges for chemical processes today, from a safety and profit standpoint, is the potential that cyberattacks could be performed on components of process control systems. Safety issues could be catastrophic; however, because the nonlinear systems definition of a cyberattack has similarities to a nonlinear systems definition of faults, many processes have already been instrumented to handle various problematic input conditions. Also challenging is the question of how to design a system that is resilient to attacks attempting to impact the production volumes or profits of a company. In this work, we explore a process/equipment design framework for handling safety issues in the presence of cyberattacks (in the spirit of traditional HAZOP thinking), and present a method for bounding the profit/production loss which might be experienced by a plant under a cyberattack through the use of a sufficiently conservative operating strategy combined with the assumption that an attack detection method with characterizable time to detection is available.

Integrated cyberattack detection and resilient control strategies using Lyapunov‐based economic model predictive control

“…Detection Strategy 1 described in Section 3.1 may identify a cyberattack by taking advantage of LEMPC's properties, but it does not guarantee closed‐loop stability in the presence of an attack (and as shown in the example of the prior section, there can be many cases in which the method fails to detect attacks). A strategy suggested in References 20,17 could be used instead to give a detection strategy that provides short‐term guarantees that the closed‐loop state is maintained in a bounded region of operation after an attack on the sensor measurements (even, potentially, all of the measurements). Specifically, this second detection strategy uses state predictions from the process model from the last state measurement to identify an attack if the predictions deviate too significantly from the measurements.…”

“…The impacts of cyberattacks on MPC's were also related to process and equipment design. 17 However, further understanding of the interaction between cyberattack detection strategies and MPC/EMPC formulation and stability guarantees is still needed.…”

“…Durand 14 explored several MPC techniques with economics‐based objective functions (known as economic MPC's [EMPC's] 15,16 ) in the presence of false sensor measurements to explore cyberattacks in a nonlinear systems context. The impacts of cyberattacks on MPC's were also related to process and equipment design 17 . However, further understanding of the interaction between cyberattack detection strategies and MPC/EMPC formulation and stability guarantees is still needed.…”

Handling of stealthy sensor and actuator cyberattacks on evolving nonlinear process systems

“…In addition, process disturbances were added to the right-hand side of the differential equations describing the rates of change of C A and T with zero mean and standard deviations of 100 kmol/m 3 h and 2200 K/h, and bounds of 50 kmol/m 3 h and 500 K/h, respectively (Case 1). The false state trajectory provided as a measurement sequence from the sensors to the controller is developed via a secondary simulation of C A and T using Equations ( 10) and (11). In this secondary simulation, which would be difficult to implement as it assumes the actual value of the state is known at the first time that the attack starts, which is not possible given the limitations of measuring devices, disturbances are added to the right-hand side of Equations ( 10) and ( 11) taken from the same normal distribution as the disturbances impacting the process (and bounded with the same bounds), but different realizations of the random variable.…”

“…There has also been work on exploring cyberattack resilient control from a nonlinear systems perspective [10] and with equipment design considerations. [11] In addition to CPS, cyberattack detection methods have been studied in other contexts such as power/smart grids [12] and automotive platforms. [13] Integrated cyberattack detection and advanced control methods using model predictive control (MPC [14] ) also have been developed as an attempt to identify attacks while guaranteeing closed-loop stability even in the presence of cyberattacks.…”