Login | Register

Optimal Cybersecurity of Cyber-Physical Systems Using Game-Theory Strategies

Title:

Optimal Cybersecurity of Cyber-Physical Systems Using Game-Theory Strategies

Asgari, Shadi ORCID: https://orcid.org/0000-0002-8771-5011 (2025) Optimal Cybersecurity of Cyber-Physical Systems Using Game-Theory Strategies. Masters thesis, Concordia University.

[thumbnail of Asgari_MA_F2025.pdf]
Text (application/pdf)
Asgari_MA_F2025.pdf - Accepted Version
Restricted to Repository staff only until 1 September 2027.
Available under License Spectrum Terms of Access.
9MB

Abstract

In this thesis, the problem of optimal cybersecurity of Cyber-Physical Systems (CPS) will be addressed. In the first topic, optimal cybersecurity of CPS based on game theory method will be studied. In this problem, cybersecurity of CPS is investigated by defining a new game between attacker and defender in the case that
there is a passive detection mechanism on the Command-and-Control (C&C) side.
By considering the defender’s fixed strategy, a game theory-based optimal attack in the viewpoint of attacker will be designed. The proposed cyber-attack strategy can deteriorate the performance of the system and steer the system to the desired performance of the attacker and remains stealthy. Towards these ends, regarding
the general structure of a CPS, two cooperating attackers on input channels and measurement channels are considered to inject their signals according to the strategy of each other.
According to the defined objectives of each attacker, an appropriate cost function is defined for each attacker that depends on their strategies as well. Defining an optimization problem results in some coupled Hamilton Jacobi Belman (HJB) equations. To solve these coupled complex equations, some machine learning methods
will be applied to reach an optimal attack strategy. It will be shown that the passive detection mechanism cannot detect the proposed optimal attack strategy.
Furthermore, game theory-based robust optimal attack design in the viewpoint of attacker for defender’s fixed strategy detector in the presence of disturbances will be addressed to verify the detectability condition of the optimal cyber-attacks. To
address the effect of the disturbance in the system for the defined game, a hierarchical game that is the combination of zero-sum and Stackelberg game is proposed.
In the second problem, an optimal secure estimation and resilient control for linear CPS by taking advantages of the game theory method will be presented. To have the capability of the optimal secure estimation, we use an auxiliary system to provide the redundancy information on the measurement of the main plant. The
information of the auxiliary system with a specific dynamic will be added to the output of the system. As a result, we have a new set of information with redundancy to be transferred on the communication channels. To make it difficult for the attacker
to find the channels that are communicating information, a Moving Target Defense (MTD) block is utilized on the plant side before sending the information.
On the other hand, to have the same capability on the input channels to provide a resilient strategy, an auxiliary system will be used on the C&C side in parallel with the main controller to provide redundancies in the input signals. By adopting the same strategy on the measurement channels, i.e. using Moving Target Defense (MTD) approach, attacker cannot identify the channels that are communicating information.
Finally, in the third sub-problem of this chapter, we will consider the case that there is the possibility of the actuator fault as well as cyber-attacks. The problem will be solved based on game theory method by taking advantages of reinforcement learning
method.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Asgari, Shadi
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:23 June 2025
Thesis Supervisor(s):Khorasani, Khashayar
ID Code:995918
Deposited By: Shadi Asgari
Deposited On:04 Nov 2025 16:04
Last Modified:04 Nov 2025 16:04

References:

[1] A. Teixeira, I. Shames, H. Sandberg, and K. H. Johansson, “A secure control framework
for resource-limited adversaries,” Automatica, vol. 51, pp. 135–148, 2015.
[2] J. Shi, J.Wan, H. Yan, and H. Suo, “A survey of cyber-physical systems,” in 2011 International
Conference on Wireless Communications and Signal Processing (WCSP). IEEE,
2011, pp. 1–6.
[3] S. K. Khaitan and J. D. McCalley, “Design techniques and applications of cyberphysical
systems: A survey,” IEEE Systems Journal, vol. 9, no. 2, pp. 350–365, 2014.
[4] G. B. K. L. R. R. Rajkumar, “An end-to-end integration framework for automotive cyberphysical
systems using sysweaver,” AVICPS 2010, p. 23, 2010.
[5] H. Chen, “Applications of cyber-physical system: a literature review,” Journal of Industrial
Integration and Management, vol. 2, no. 03, p. 1750012, 2017.
[6] S. Sridhar, A. Hahn, and M. Govindarasu, “Cyber–physical system security for the electric
power grid,” Proceedings of the IEEE, vol. 100, no. 1, pp. 210–224, 2011.
[7] S. H. Ahmed, G. Kim, and D. Kim, “Cyber physical system: Architecture, applications
and research challenges,” in 2013 IFIP Wireless Days (WD). IEEE, 2013, pp. 1–5.
[8] S. A. Haque, S. M. Aziz, and M. Rahman, “Review of cyber-physical system in healthcare,”
International Journal of Distributed Sensor Networks, vol. 10, no. 4, p. 217415,
2014.
[9] F. Pasqualetti, F. Dörfler, and F. Bullo, “Attack detection and identification in cyberphysical
systems,” IEEE Transactions on Automatic Control, vol. 58, no. 11, pp. 2715–
2729, 2013.
[10] Y. Li, P. Zhang, L. Zhang, and B. Wang, “Active synchronous detection of deception
attacks in microgrid control systems,” IEEE Transactions on Smart Grid, vol. 8, no. 1, pp.
373–375, 2016.
[11] Y. Mo and B. Sinopoli, “Secure control against replay attacks,” in 2009 47th Annual
Conference on Communication, Control, and Computing (Allerton). IEEE, 2009, pp.
911–918.
[12] F. Miao, M. Pajic, and G. J. Pappas, “Stochastic game approach for replay attack detection,”
in 52nd IEEE Conference on Decision and Control. IEEE, 2013, pp. 1854–1859.
[13] H. S. Sánchez, D. Rotondo, T. Escobet, V. Puig, and J. Quevedo, “Bibliographical review
on cyber attacks from a control oriented perspective,” Annual Reviews in Control, vol. 48,
pp. 103–128, 2019.
[14] H. Habibzadeh, B. H. Nussbaum, F. Anjomshoa, B. Kantarci, and T. Soyata, “A survey
on cybersecurity, data privacy, and policy issues in cyber-physical system deployments in
smart cities,” Sustainable Cities and Society, vol. 50, p. 101660, 2019.
[15] V. R. Palleti, Y. C. Tan, and L. Samavedham, “A mechanistic fault detection and isolation
approach using Kalman filter to improve the security of cyber physical systems,” Journal
of Process Control, vol. 68, pp. 160–170, 2018.
[16] D. Xu, F. Zhu, Z. Zhou, and X. Yan, “Distributed fault detection and estimation in cyber–
physical systems subject to actuator faults,” ISA Transactions, vol. 104, pp. 162–174,
2020.
[17] V. Reppa, M. M. Polycarpou, and C. G. Panayiotou, “Distributed sensor fault diagnosis
for a network of interconnected cyberphysical systems,” IEEE Transactions on Control of
Network Systems, vol. 2, no. 1, pp. 11–23, 2015.
[18] J. CHEN, R. J. PATTON, and H.-Y. ZHANG, “Design of unknown input observers and
robust fault detection filters,” International Journal of Control, vol. 63, no. 1, pp. 85–105,
1996.
[19] N. Tudoroiu and K. Khorasani, “Fault detection and diagnosis for satellite’s attitude control
system (acs) using an interactive multiple model (IMM) approach,” in Proceedings
of 2005 IEEE Conference on Control Applications, 2005. CCA 2005. IEEE, 2005, pp.
1287–1292.
[20] N. Meskin, E. Naderi, and K. Khorasani, “A multiple model-based approach for fault
diagnosis of jet engines,” IEEE Transactions on Control Systems Technology, vol. 21,
no. 1, pp. 254–262, 2011.
[21] B. Pourbabaee, N. Meskin, and K. Khorasani, “Sensor fault detection, isolation, and identification
using multiple-model-based hybrid Kalman filter for gas turbine engines,” IEEE
Transactions on Control Systems Technology, vol. 24, no. 4, pp. 1184–1200, 2015.
[22] M. Davoodi, N. Meskin, and K. Khorasani, “A single dynamic observer-based module for
design of simultaneous fault detection, isolation and tracking control scheme,” International
Journal of Control, vol. 91, no. 3, pp. 508–523, 2018.
[23] H.Wang and G.-H. Yang, “A finite frequency domain approach to fault detection observer
design for linear continuous-time systems,” Asian Journal of Control, vol. 10, no. 5, pp.
559–568, 2008.
[24] J. Chen and Y.-Y. Cao, “A stable fault detection observer design in finite frequency domain,”
International Journal of Control, vol. 86, no. 2, pp. 290–298, 2013.
[25] J. Wei, Y. Wu, and J. Dong, “Actuator and sensor faults estimation for discrete-time descriptor
linear parameter-varying systems in finite frequency domain,” International Journal
of Systems Science, vol. 49, no. 7, pp. 1572–1585, 2018.
[26] Y. Long and G.-H. Yang, “Fault detection in finite frequency domain for networked control
systems with missing measurements,” Journal of the Franklin Institute, vol. 350, no. 9, pp. 2605–2626, 2013.
[27] X. Li and G. Yang, “Fault detection in finite frequency domain for linear systems under
feedback control,” in 2009 IEEE Control Applications,(CCA) & Intelligent Control,(
ISIC). IEEE, 2009, pp. 1332–1337.
[28] M. Zhou, Z. Wang, Y. Shen, and M. Shen, “H_/H∞ fault detection observer design in
finite-frequency domain for lipschitz non-linear systems,” IET Control Theory & Applications,
vol. 11, no. 14, pp. 2361–2369, 2017.
[29] A. Chibani, M. Chadli, and N. B. Braiek, “A finite frequency approach to H∞ filtering
for t–s fuzzy systems with unknown inputs,” Asian Journal of Control, vol. 18, no. 5, pp.
1608–1618, 2016.
[30] S. Tan, J. M. Guerrero, P. Xie, R. Han, and J. C. Vasquez, “Brief survey on attack detection
methods for cyber-physical systems,” IEEE Systems Journal, vol. 14, no. 4, pp. 5329–
5339, 2020.
[31] F. Pasqualetti, F. Dörfler, and F. Bullo, “Attack detection and identification in cyberphysical
systems,” IEEE Transactions on Automatic Control, vol. 58, no. 11, pp. 2715–
2729, 2013.
[32] A. Sargolzaei, C. D. Crane, A. Abbaspour, and S. Noei, “A machine learning approach
for fault detection in vehicular cyber-physical systems,” in 2016 15th IEEE International
Conference on Machine Learning and Applications (ICMLA), 2016, pp. 636–640.
[33] K. Paridari, N. O’Mahony, A. E.-D. Mady, R. Chabukswar, M. Boubekeur, and H. Sandberg,
“A framework for attack-resilient industrial control systems: Attack detection and
controller reconfiguration,” Proceedings of the IEEE, vol. 106, no. 1, pp. 113–128, 2017.
[34] C. De Persis and P. Tesi, “Input-to-state stabilizing control under denial-of-service,” IEEE
Transactions on Automatic Control, vol. 60, no. 11, pp. 2930–2944, 2015.
[35] D. Ding, Q.-L. Han, Y. Xiang, X. Ge, and X.-M. Zhang, “A survey on security control
and attack detection for industrial cyber-physical systems,” Neurocomputing, vol. 275, pp.
1674–1683, 2018.
[36] C.-Y. Gu, J.-W. Zhu,W.-A. Zhang, and L. Yu, “Sensor attack detection for cyber-physical
systems based on frequency domain partition,” IET Control Theory & Applications,
vol. 14, no. 11, pp. 1452–1466, 2020.
[37] Y. Z. Lun, A. D’Innocenzo, F. Smarra, I. Malavolta, and M. D. Di Benedetto, “State of
the art of cyber-physical systems security: An automatic control perspective,” Journal of
Systems and Software, vol. 149, pp. 174–216, 2019.
[38] M. Taheri, K. Khorasani, I. Shames, and N. Meskin, “Cyber attack and machine induced
fault detection and isolation methodologies for cyber-physical systems,” arXiv preprint
arXiv:2009.06196, 2020.
[39] Y. Wu and J. Dong, “Cyber-physical attacks against state estimators based on a finite
frequency approach,” IEEE Transactions on Systems, Man, and Cybernetics: Systems,
2018.
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top