Interacting multiple model estimator for event-triggered cyber-physical systems against Denial-of-service attacks

Zengwang Jin, Shuting Zhang, Yanning Zhang, Changyin Sun

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceeding - 2021 China Automation Congress, CAC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3629-3634
Number of pages6
ISBN (Electronic)9781665426473
DOIs
StatePublished - 2021
Event2021 China Automation Congress, CAC 2021 - Beijing, China
Duration: 22 Oct 202124 Oct 2021

Publication series

NameProceeding - 2021 China Automation Congress, CAC 2021

Conference

Conference2021 China Automation Congress, CAC 2021
Country/TerritoryChina
CityBeijing
Period22/10/2124/10/21

Keywords

  • cyber-physical systems
  • DoS attack
  • event-triggered mechanism
  • state estimation

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