Journal
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
Volume 4, Issue 3, Pages 632-642Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCNS.2016.2549640
Keywords
Cyberphysical systems; game theory; remote state estimation; security; wireless sensors
Funding
- HK RGC [T23-701/14N]
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We consider remote state estimation of cyberphysical systems under signal-to-interference-plus-noise ratio-based denial-of-service attacks. A sensor sends its local estimate to a remote estimator through a wireless network that may suffer interference from an attacker. Both the sensor and the attacker have energy constraints. We first study an associated two-player game when multiple power levels are available. Then, we build a Markov game framework to model the interactive decision-making process based on the current state and information collected from previous time steps. To solve the associated optimality (Bellman) equations, a modified Nash Q-learning algorithm is applied to obtain the optimal solutions. Numerical examples and simulations are provided to demonstrate our results.
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