(196f) Handling Cyberattacks in Advanced Control of Cubesats

Satellites are critical to day-to-day life, with their applications ranging from communication to observations helping scientists to learn about Earth and space. Cyberattacks on satellites are typically well managed in larger programs like the Joint Polar Satellite System and Orion [6], but smaller low-cost missions like CubeSats, a class of nanosatellites, could be vulnerable to attack such as spoofing attacks [7]. CubeSats are a 4-inch cube that are characterized by their light weight. They have been employed in, for example, interplanetary missions [8]. Cyberattacks such as spoofing can be problematic on satellites that incorporate control strategies which manipulate actuators leading to modification of their orientation and degrading their performance. Cyberattacks on satellite have been discussed in the literature. [1] for example, discusses a potential outcome of a cyberattacks involving satellites as their ability to harm one another. As a step toward cyberattack-resilient control of autonomous cyber-physical systems, [2] proposed a resilient estimator where Kalman filtering technique combined with watermarking approach was elaborated in order to detect cyberattacks on a CubeSat’s sensors such as spoofing. A number of strategies for handling cyberattacks on control systems were also developed by our group in order to detect and mitigate cyberattacks for systems described by nonlinear differential equations (e.g., [3][4][5]). However, the needs of space systems (e.g., reduced computation time) were not directly addressed in our group’s prior work.

In this work, we analyze how our prior methods extend to the case of the CubeSat control. We begin by discussing the dynamic model used to represent the CubeSat behavior. We then discuss the theoretical and application principles of applying our prior cyberattack detection policies that integrate with an advanced control algorithm known as Lyapunov-based economic model predictive control (LEMPC) [9], which were developed in [10] to the case of the CubeSat. We then discuss how the strategies in [10] could be extended to allow other advanced controllers that are not LEMPC to be considered with respect to their cybersecurity guarantees. For example, we consider a case of an EMPC with a terminal constraint instead of an LEMPC, and how it might be integrated with detection strategies. We compare the different strategies developed with respect to their effectiveness and ease of use to provide a more comprehensive view of different integrated cyberattack detection and control policies than have been developed in our prior work.

References:

[1] Falco, G. (2020). When Satellites Attack: Satellite-to-Satellite Cyber Attack, Defense and Resilience. In ASCEND 2020 (p. 4014).

[2] Marquis, V., Ho, R., Rainey, W., Kimpel, M., Ghiorzi, J., Cricchi, W. and Bezzo, N., 2018, April. Toward attack-resilient state estimation and control of autonomous cyber-physical systems. In 2018 Systems and Information Engineering Design Symposium (SIEDS) (pp. 70-75). IEEE.

[3] Helen Durand. “A nonlinear systems framework for cyberattack prevention for chemical process control systems”. In: Mathematics 6.9 (2018), p. 169.

[4] Helen Durand and Matthew Wegener. “Mitigating cyberattack impacts using Lyapunov-based economic model predictive control”. In: 2020 American Control Conference (ACC). IEEE. 2020, pp. 1894–1899.

[5] Keshav Kasturi Rangan, Henrique Oyama, and Helen Durand. “Integrated cyberattack detection and handling for nonlinear systems with evolving process dynamics under Lyapunov-based economic model predictive control”. In: Chemical Engineering Research and Design 170 (2021), pp. 147–179.

[6] NASA Office of Inspector General, Office of Audits, NASA’s Cybersecurity Readiness, Report No. IG-21-019, May 18, 2021

[7] Marquis, V., Ho, R., Rainey, W., Kimpel, M., Ghiorzi, J., Cricchi, W., & Bezzo, N. (2018, April). Toward attack-resilient state estimation and control of autonomous cyber-physical systems. In 2018 Systems and Information Engineering Design Symposium (SIEDS) (pp. 70-75). IEEE.

[8] Howell, Elizabeth. "Cubesats: Tiny payloads, huge benefits for space research." Space. com (2018).

[9] Heidarinejad, M., Liu, J., & Christofides, P. D. (2012). Economic model predictive control of nonlinear process systems using Lyapunov techniques. AIChE Journal, 58(3), 855-870.

[10] Oyama, H., & Durand, H. (2020). Integrated cyberattack detection and resilient control strategies using Lyapunov‐based economic model predictive control. AIChE Journal, 66(12), e17084.