Open AccessAdaptive event-triggered state estimation for complex networks with nonlinearities against hybrid attacks
Author(s) -
Yahan Deng,
Zhenhai Meng,
Hongqian Lu
Publication year - 2022
Publication title -
aims mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 15
ISSN - 2473-6988
DOI - 10.3934/math.2022158
Subject(s) - denial of service attack , estimator , lyapunov function , state (computer science) , control theory (sociology) , computer science , network packet , bernoulli's principle , stability (learning theory) , event (particle physics) , lyapunov stability , mathematics , algorithm , computer network , engineering , the internet , artificial intelligence , nonlinear system , statistics , physics , control (management) , quantum mechanics , machine learning , world wide web , aerospace engineering
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.