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Resilient strategy design for cyber-physical system under active eavesdropping attack
Authors:Huanhuan Yuan  Yuanqing Xia  Yuan Yuan  Hongjiu Yang
Institution:1. School of Astronautics, Northwestern Polytechnical University, Xi’an 710072, China;2. School of Automation, Beijing Institute of Technology, Beijing 100081, China;3. Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, PR China;1. School of Artificial Intelligence, Shenyang University of Technology, Shenyang, China;2. College of Engineering, Qufu Normal University, Rizhao, Shandong, China
Abstract:We consider a remote state estimation process under an active eavesdropper for cyber-physical system. A smart sensor transmits its local state estimates to a remote estimator over an unreliable network, which is eavesdropped by an adversary. The intelligent adversary can work in passive eavesdropping mode and active jamming mode. An active jamming mode enables the adversary to interfere the data transmission from sensor to estimator, and meanwhile improve the data reception of itself. To protect the transmission data from being wiretapped, the sensor with two antennas injects noise to the eavesdropping link with different power levels. Aiming at minimizing the estimation error covariance and power cost of themselves while maximizing the estimation error covariance of their opponents, a two-player nonzero-sum game is constructed for sensor and active eavesdropper. For an open-loop case, the mixed Nash equilibrium is obtained by solving an one-stage nonzero-sum game. For a long term consideration, a Markov stochastic game is introduced and a Nash Q-learning method is given to find the Nash equilibrium strategies for two players. Numerical results are provided to show the effectiveness of our theoretical conclusions.
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