TY - GEN
T1 - Interacting multiple model estimator for event-triggered cyber-physical systems against Denial-of-service attacks
AU - Jin, Zengwang
AU - Zhang, Shuting
AU - Zhang, Yanning
AU - Sun, Changyin
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - This paper investigates the problem of security state estimation of event-triggered cyber-physical systems (CPSs) under constrained bandwidth and random DoS attacks. Two independent Markov chains are introduced to separately describe the transition of system models and the occurrence of DoS attacks. By presenting an event-triggered scheduling mechanism based on the measurement innovation, the impact of bandwidth and power limitations in CPSs is mitigated. For the purpose of reducing the complexity of model sequences, the interacting multiple model (IMM) framework is extended event-triggered CPSs to cut down the the branch of exponential growth assumptions. In addition, the statistical information of event-triggered conditions are utilized to estimate the continuous state, identify the system mode and detect DoS attacks. Finally, the performance of the proposed method is validated by Monte Carlo simulation in a two-dimensional maneuvering target tracking.
AB - This paper investigates the problem of security state estimation of event-triggered cyber-physical systems (CPSs) under constrained bandwidth and random DoS attacks. Two independent Markov chains are introduced to separately describe the transition of system models and the occurrence of DoS attacks. By presenting an event-triggered scheduling mechanism based on the measurement innovation, the impact of bandwidth and power limitations in CPSs is mitigated. For the purpose of reducing the complexity of model sequences, the interacting multiple model (IMM) framework is extended event-triggered CPSs to cut down the the branch of exponential growth assumptions. In addition, the statistical information of event-triggered conditions are utilized to estimate the continuous state, identify the system mode and detect DoS attacks. Finally, the performance of the proposed method is validated by Monte Carlo simulation in a two-dimensional maneuvering target tracking.
KW - cyber-physical systems
KW - DoS attack
KW - event-triggered mechanism
KW - state estimation
UR - http://www.scopus.com/inward/record.url?scp=85128008113&partnerID=8YFLogxK
U2 - 10.1109/CAC53003.2021.9728267
DO - 10.1109/CAC53003.2021.9728267
M3 - 会议稿件
AN - SCOPUS:85128008113
T3 - Proceeding - 2021 China Automation Congress, CAC 2021
SP - 3629
EP - 3634
BT - Proceeding - 2021 China Automation Congress, CAC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 China Automation Congress, CAC 2021
Y2 - 22 October 2021 through 24 October 2021
ER -