TY - GEN
T1 - Resilient state estimation against switching attacks on stochastic cyber-physical systems
AU - Yong, Sze Zheng
AU - Zhu, Minghui
AU - Frazzoli, Emilio
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/2/8
Y1 - 2015/2/8
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84962016417&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962016417&partnerID=8YFLogxK
U2 - 10.1109/CDC.2015.7403027
DO - 10.1109/CDC.2015.7403027
M3 - Conference contribution
AN - SCOPUS:84962016417
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 5162
EP - 5169
BT - 54rd IEEE Conference on Decision and Control,CDC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 54th IEEE Conference on Decision and Control, CDC 2015
Y2 - 15 December 2015 through 18 December 2015
ER -