Stochastic Game in Remote Estimation under DoS Attacks
For researchers in cyber-physical systems security, this provides a game-theoretic framework for optimal power control under jamming, though the results are theoretical with no empirical validation.
This paper models the interaction between a sensor and a DoS attacker in remote state estimation as a zero-sum stochastic game, proving existence of stationary Nash equilibrium and monotone optimal strategies that reduce computational complexity.
This paper studies remote state estimation under denial-of-service (DoS) attacks. A sensor transmits its local estimate of an underlying physical process to a remote estimator via a wireless communication channel. A DoS attacker is capable to interfere the channel and degrades the remote estimation accuracy. Considering the tactical jamming strategies played by the attacker, the sensor adjusts its transmission power. This interactive process between the sensor and the attacker is studied in the framework of a zero-sum stochastic game. To derive their optimal power schemes, we first discuss the existence of stationary Nash equilibrium (SNE) for this game. We then present the monotone structure of the optimal strategies, which helps reduce the computational complexity of the stochastic game algorithm. Numerical examples are provided to illustrate the obtained results.