Stability analysis on networked control systems under double attacks with predictive control

In this paper, stability of a networked control system under denial‐of‐service and false data injection attacks is analyzed with a predictive control method. To model denial‐of‐service attacks on the forward channel of networked control system, game theory is introduced for obtaining balanced results by denial‐of‐service frequency and duration. Then, measurement outputs of the networked control system are maliciously modified in the feedback channel. Under this double attack strategy, the stability of networked control system with predictive control is analyzed using a switched system method. By comparing three types of attack models, advantages of the double attacks are discussed to illustrate the necessity of this research. A numerical simulation is given to demonstrate effectiveness of the proposed methods on a networked control system under double attacks.

[1]  Xavier Litrico,et al.  Cyber Security of Water SCADA Systems—Part I: Analysis and Experimentation of Stealthy Deception Attacks , 2013, IEEE Transactions on Control Systems Technology.

[2]  Ling Shi,et al.  Optimal DoS Attack Scheduling in Wireless Networked Control System , 2016, IEEE Transactions on Control Systems Technology.

[3]  Derui Ding,et al.  Distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor networks , 2017, Autom..

[4]  Donghua Zhou,et al.  Two-Channel False Data Injection Attacks Against Output Tracking Control of Networked Systems , 2016, IEEE Transactions on Industrial Electronics.

[5]  Guo-Ping Liu,et al.  Design and Implementation of Secure Networked Predictive Control Systems Under Deception Attacks , 2012, IEEE Transactions on Control Systems Technology.

[6]  John Y. Hung,et al.  Denial of service attacks on network-based control systems: impact and mitigation , 2005, IEEE Transactions on Industrial Informatics.

[7]  Hongtao Sun,et al.  A Survey on Security Communication and Control for Smart Grids Under Malicious Cyber Attacks , 2019, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[8]  Panos J. Antsaklis,et al.  Risk-Sensitive Control Under Markov Modulated Denial-of-Service (DoS) Attack Strategies , 2015, IEEE Transactions on Automatic Control.

[9]  Yuanqing Xia,et al.  Stabilization of networked control systems with nonuniform random sampling periods , 2011 .

[10]  Chao Yang,et al.  False data injection attack on consensus‐based distributed estimation , 2017 .

[11]  Pietro Tesi,et al.  Input-to-State Stabilizing Control Under Denial-of-Service , 2015, IEEE Transactions on Automatic Control.

[12]  Fei Hu,et al.  Detection of Faults and Attacks Including False Data Injection Attack in Smart Grid Using Kalman Filter , 2014, IEEE Transactions on Control of Network Systems.

[13]  Ling Shi,et al.  SINR-Based DoS Attack on Remote State Estimation: A Game-Theoretic Approach , 2017, IEEE Transactions on Control of Network Systems.

[14]  Yuanqing Xia,et al.  A network-bound-dependent stabilization method of networked control systems , 2013, Autom..

[15]  Lei Guo,et al.  Event-Triggered Strategy Design for Discrete-Time Nonlinear Quadratic Games With Disturbance Compensations: The Noncooperative Case , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[16]  Dong Yue,et al.  Model‐based event‐triggered predictive control for networked systems with communication delays compensation , 2015 .

[17]  Ling Shi,et al.  Optimal Linear Cyber-Attack on Remote State Estimation , 2017, IEEE Transactions on Control of Network Systems.

[18]  Lei Guo,et al.  Optimal control for networked control systems with disturbances: a delta operator approach , 2017 .

[19]  Quanyan Zhu,et al.  Game-Theoretic Methods for Robustness, Security, and Resilience of Cyberphysical Control Systems: Games-in-Games Principle for Optimal Cross-Layer Resilient Control Systems , 2015, IEEE Control Systems.

[20]  Ling Shi,et al.  Optimal Denial-of-Service Attack Scheduling With Energy Constraint , 2015, IEEE Transactions on Automatic Control.

[21]  Jin Zhang,et al.  Adaptive Event-Triggering ${H}_{\infty }$ Load Frequency Control for Network-Based Power Systems , 2018, IEEE Transactions on Industrial Electronics.

[22]  Lei Guo,et al.  Resilient Control of Networked Control System Under DoS Attacks: A Unified Game Approach , 2016, IEEE Transactions on Industrial Informatics.

[23]  Lei Guo,et al.  Composite control of linear quadratic games in delta domain with disturbance observers , 2017, J. Frankl. Inst..

[24]  S. Shankar Sastry,et al.  Safe and Secure Networked Control Systems under Denial-of-Service Attacks , 2009, HSCC.

[25]  Guoqiang Hu,et al.  Distributed consensus tracking for multi‐agent systems under two types of attacks , 2016 .

[26]  Bruno Sinopoli,et al.  Detecting Integrity Attacks on SCADA Systems , 2011 .

[27]  Long Wang,et al.  Switched system approach to stabilization of networked control systems , 2011 .

[28]  Fuchun Sun,et al.  Data Fusion-based resilient control system under DoS attacks: A game theoretic approach , 2015 .

[29]  Hannu Salonen,et al.  On the existence of Nash equilibria in large games , 2010, Int. J. Game Theory.

[30]  Yurong Liu,et al.  Sampled‐data consensus of nonlinear multiagent systems subject to cyber attacks , 2018 .

[31]  Yuanqing Xia,et al.  Design and Stability Analysis of Networked Predictive Control Systems , 2013, IEEE Transactions on Control Systems Technology.