Secure State Estimation Against Sensor Attacks in the Presence of Noise

We consider the problem of estimating the state of a noisy linear dynamical system when an unknown subset of sensors is arbitrarily corrupted by an adversary. We propose a secure state estimation algorithm, and derive (optimal) bounds on the achievable state estimation error given an upper bound on...

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Bibliographic Details
Published in:IEEE transactions on control of network systems Vol. 4; no. 1; pp. 49 - 59
Main Authors: Mishra, Shaunak, Shoukry, Yasser, Karamchandani, Nikhil, Diggavi, Suhas N., Tabuada, Paulo
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.03.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Combinatorial analysis
Control systems
Covariance matrices
Dynamical systems
Economic models
Encoding
Error detection
Kalman filters
Noise measurement
Secure cyber-physical systems
secure state reconstruction
sensor attacks
Sensors
State estimation
Symmetric matrices
ISSN:2325-5870, 2372-2533
Online Access:Get full text
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Summary:We consider the problem of estimating the state of a noisy linear dynamical system when an unknown subset of sensors is arbitrarily corrupted by an adversary. We propose a secure state estimation algorithm, and derive (optimal) bounds on the achievable state estimation error given an upper bound on the number of attacked sensors. The proposed state estimator involves Kalman filters operating over subsets of sensors to search for a sensor subset which is reliable for state estimation. To further improve the subset search time, we propose Satisfiability Modulo Theory-based techniques to exploit the combinatorial nature of searching over sensor subsets. Finally, as a result of independent interest, we give a coding theoretic view of attack detection and state estimation against sensor attacks in a noiseless dynamical system.
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ISSN:2325-5870
2372-2533
DOI:10.1109/TCNS.2016.2606880