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

Sze Yong, Minghui Zhu, Emilio Frazzoli

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

37 Citations (Scopus)

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
Externally publishedYes
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: Dec 15 2015Dec 18 2015

Other

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

Fingerprint

State Estimation
State estimation
Signal noise measurement
Attack
Asymptotic analysis
Random processes
Linear systems
Actuators
Sensors
Switched Linear Systems
Switching Systems
Unknown Inputs
Multiple Models
Asymptotic Analysis
Power System
Cyber Physical System
Efficacy
Stochastic Processes
Actuator
Benchmark

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

Cite this

Yong, S., 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] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2015.7403027

Resilient state estimation against switching attacks on stochastic cyber-physical systems. / Yong, Sze; Zhu, Minghui; Frazzoli, Emilio.

54rd IEEE Conference on Decision and Control,CDC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 5162-5169 7403027.

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

Yong, S, 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., 7403027, Institute of Electrical and Electronics Engineers Inc., pp. 5162-5169, 54th IEEE Conference on Decision and Control, CDC 2015, Osaka, Japan, 12/15/15. https://doi.org/10.1109/CDC.2015.7403027
Yong S, Zhu M, Frazzoli E. Resilient state estimation against switching attacks on stochastic cyber-physical systems. In 54rd IEEE Conference on Decision and Control,CDC 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 5162-5169. 7403027 https://doi.org/10.1109/CDC.2015.7403027
Yong, Sze ; Zhu, Minghui ; Frazzoli, Emilio. / Resilient state estimation against switching attacks on stochastic cyber-physical systems. 54rd IEEE Conference on Decision and Control,CDC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 5162-5169
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