Stochastic Game in Remote Estimation under DoS Attacks

TL;DR

This paper models the interaction between a sensor and a DoS attacker in remote estimation as a zero-sum stochastic game, deriving optimal power strategies and analyzing equilibrium properties to improve estimation robustness.

Contribution

It introduces a stochastic game framework for remote estimation under DoS attacks, deriving stationary Nash equilibria and revealing strategy structures to enhance security.

Findings

Existence of stationary Nash equilibrium confirmed.

Optimal strategies exhibit a monotone structure.

Numerical results demonstrate strategy effectiveness.

Abstract

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.