(702f) Extending Lyapunov-Based Active Cyberattack Detection to Terminal Equality-Constrained Control and Directed Randomization to Quantum Control

Cybersecurity considerations are becoming more critical due to the high exposure of control systems to a range of threats and security vulnerabilities. To enhance safety and attack resiliency of control systems, passive cyberattack detection strategies (e.g., [1]) as well as active detection methodologies (e.g., [2]) can be developed. In our prior group’s work (i.e., [3]), an active detection strategy for chemical processes under Lyapunov-based economic model predictive control (LEMPC) [4] was elaborated. This strategy specific to LEMPC probed for cyberattacks by using random modifications of the LEMPC generated at random times to check whether the modified Lyapunov functions decreased over the subsequent sampling period (which should be the case in the absence of an attack). However, though LEMPC was used for cyberattack detection policies in our prior works, LEMPC is not the only EMPC framework. Thus, it is important to understand to what extent the insights revealed by studying the cyberattack detection policies within an LEMPC-based framework translate to other EMPC formulations (e.g., a terminal equality constraint formulation [5]). In addition to LEMPC-focused cyberattack detection strategies, our prior work has considered another strategy intended for the case that all sensors are under attack. We termed this strategy “directed randomization” because randomly selects between two control actions at every sampling time of process operation [6]. This is done to attempt to make it hard for an attacker that is targeting the sensors to consistently predict which control action should have been applied to match their false state measurements to it. Randomness plays an important role in this strategy; this therefore raises another question regarding whether such detection strategies can be extended to the control of systems with inherent randomness, in particular quantum systems.

Motivated by these considerations, this talk will be divided into two parts. In the first part, we first show how the key components of the active detection policy developed in [3] can be extended to a terminal equality constraint EMPC formulation. We discuss the role of the prediction horizon length in our ability to extend the detection concepts from [3], and provide the conditions under which safety and feasibility of this strategy are maintained in the absence as well as in the presence of an attack on the sensors for one sampling period. In the second part of this talk, we investigate the challenges with applying “directed randomization” to the mitigation of cyberattacks on quantum systems. We first provide a background on quantum mechanics and quantum control where we focus specifically on the use of a laser to control the bond length of a hydrogen fluoride molecule [7]. We then discuss how the measurement principles of quantum mechanics can cause projective measurement of a quantum system to be challenging to integrate with directed randomization, but instead discuss how principles from [8] (in particular, attempts to design quantum algorithms which significantly reduce the probability of measuring certain outcomes) might be used to attempt to re-gain properties like those of directed randomization in probing for cyberattacks on quantum systems.

References:

[1] Oyama, Henrique, Dominic Messina, Keshav Kasturi Rangan, and Helen Durand. "Lyapunov-based economic model predictive control for detecting and handling actuator and simultaneous sensor/actuator cyberattacks on process control systems." Frontiers in Chemical Engineering 4 (2022): 810129.

[2] Narasimhan, Shilpa, Nael H. El-Farra, and Matthew J. Ellis. "Active multiplicative cyberattack detection utilizing controller switching for process systems." Journal of Process Control 116 (2022): 64-79.

[3] Oyama, Henrique, and Helen Durand. "Integrated cyberattack detection and resilient control strategies using Lyapunov‐based economic model predictive control." AIChE Journal 66, no. 12 (2020): e17084.

[4] Heidarinejad, Mohsen, Jinfeng Liu, and Panagiotis D. Christofides. "Economic model predictive control of nonlinear process systems using Lyapunov techniques." AIChE Journal 58, no. 3 (2012): 855-870.

[5] Amrit, Rishi, James B. Rawlings, and David Angeli. "Economic optimization using model predictive control with a terminal cost." Annual Reviews in Control 35, no. 2 (2011): 178-186.

[6] Oyama, Henrique, Dominic Messina, Keshav Kasturi Rangan, Akkarakaran Francis Leonard, Kip Nieman, Helen Durand, Katie Tyrrell, Katrina Hinzman, and Michael Williamson. "Development of directed randomization for discussing a minimal security architecture." Digital Chemical Engineering 6 (2023): 100065.

[7] Magann, Alicia B., Matthew D. Grace, Herschel A. Rabitz, and Mohan Sarovar. "Digital quantum simulation of molecular dynamics and control." Physical Review Research 3, no. 2 (2021): 023165.

[8] Nieman, Kip and Helen Durand. “Safety with Non-Deterministic Control Action Selection Using Quantum Devices.” ADCHEM 2024 (2024), accepted.