Adaptive event-triggered state estimation for complex networks with nonlinearities against hybrid attacks

Yahan Deng; Zhenhai Meng; Hongqian Lu; Yahan Deng; Zhenhai Meng; Hongqian Lu

doi:10.3934/math.2022158

AIMS Mathematics

2022, Volume 7, Issue 2: 2858-2877. doi: 10.3934/math.2022158

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Research article

Adaptive event-triggered state estimation for complex networks with nonlinearities against hybrid attacks

School of Information Engineering, Guangxi City Vocational University, Chongzuo 532100, China

Received: 17 September 2021 Accepted: 09 November 2021 Published: 22 November 2021
MSC : 93C57, 93C65

This paper investigates the event-triggered state estimation problem for a class of complex networks (CNs) suffered by hybrid cyber-attacks. It is assumed that a wireless network exists between sensors and remote estimators, and that data packets may be modified or blocked by malicious attackers. Adaptive event-triggered scheme (AETS) is introduced to alleviate the network congestion problem. With the help of two sets of Bernoulli distribution variables (BDVs) and an arbitrary function related to the system state, a mathematical model of the hybrid cyber-attacks is developed to portray randomly occurring denial-of-service (DoS) attacks and deception attacks. CNs, AETS, hybrid cyber-attacks, and state estimators are then incorporated into a unified architecture. The system state is cascaded with state errors as an augmented system. Furthermore, based on Lyapunov stability theory and linear matrix inequalities (LMIs), sufficient conditions to ensure the asymptotic stability of the augmented system are derived, and the corresponding state estimator is designed. Finally, the effectiveness of the theoretical method is demonstrated by numerical examples and simulations.
- complex networks,
- adaptive event-triggered scheme,
- state estimation,
- deception attacks,
- denial-of-service attacks
Citation: Yahan Deng, Zhenhai Meng, Hongqian Lu. Adaptive event-triggered state estimation for complex networks with nonlinearities against hybrid attacks[J]. AIMS Mathematics, 2022, 7(2): 2858-2877. doi: 10.3934/math.2022158

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Abstract

This paper investigates the event-triggered state estimation problem for a class of complex networks (CNs) suffered by hybrid cyber-attacks. It is assumed that a wireless network exists between sensors and remote estimators, and that data packets may be modified or blocked by malicious attackers. Adaptive event-triggered scheme (AETS) is introduced to alleviate the network congestion problem. With the help of two sets of Bernoulli distribution variables (BDVs) and an arbitrary function related to the system state, a mathematical model of the hybrid cyber-attacks is developed to portray randomly occurring denial-of-service (DoS) attacks and deception attacks. CNs, AETS, hybrid cyber-attacks, and state estimators are then incorporated into a unified architecture. The system state is cascaded with state errors as an augmented system. Furthermore, based on Lyapunov stability theory and linear matrix inequalities (LMIs), sufficient conditions to ensure the asymptotic stability of the augmented system are derived, and the corresponding state estimator is designed. Finally, the effectiveness of the theoretical method is demonstrated by numerical examples and simulations.

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