Resilient state estimation against switching attacks on stochastic cyber-physical systems

Sze Zheng Yong, Minghui Zhu, Emilio Frazzoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

41 Scopus citations

Abstract

In this paper, we address the resilient state estimation problem for some relatively unexplored security issues for cyber-physical systems, namely switching attacks and the presence of stochastic process and measurement noise signals, in addition to attacks on actuator and sensor signals. We model the systems under attack as hidden mode stochastic switched linear systems with unknown inputs and propose the use of the multiple model inference algorithm developed in [1] to tackle these issues. We also furnish the algorithm with the lacking asymptotic analysis. Moreover, we characterize fundamental limitations to resilient estimation (e.g., upper bound on the number of tolerable attacks) and discuss the issue of attack detection under this framework. Simulation examples of switching attacks on benchmark and power systems show the efficacy of our approach to recover unbiased state estimates.

Original languageEnglish (US)
Title of host publication54rd IEEE Conference on Decision and Control,CDC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5162-5169
Number of pages8
ISBN (Electronic)9781479978861
DOIs
StatePublished - Feb 8 2015
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: Dec 15 2015Dec 18 2015

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume54rd IEEE Conference on Decision and Control,CDC 2015
ISSN (Print)0743-1546

Other

Other54th IEEE Conference on Decision and Control, CDC 2015
CountryJapan
CityOsaka
Period12/15/1512/18/15

Keywords

  • Actuators
  • Circuit breakers
  • Inference algorithms
  • Network topology
  • State estimation
  • Stochastic processes
  • Switches

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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  • Cite this

    Yong, S. Z., Zhu, M., & Frazzoli, E. (2015). Resilient state estimation against switching attacks on stochastic cyber-physical systems. In 54rd IEEE Conference on Decision and Control,CDC 2015 (pp. 5162-5169). [7403027] (Proceedings of the IEEE Conference on Decision and Control; Vol. 54rd IEEE Conference on Decision and Control,CDC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2015.7403027