A Stackelberg Game based Physical Layer Authentication Strategy with Reinforcement Learning

Physical layer authentication as a promising complement for upper layer authentication is the first line of defense against malicious attacks in wireless communication. However, the smart spoofer can learn the rules from receiver’s authentication process and dynamically choose the proper time sending spoofing signal which poses a severe threat to wireless communications. According to this, the Stackelberg game-based physical layer authentication strategy is proposed in this paper to model the interactions between the receiver and the smart spoofer. We first consider the static game-based authentication under the worse condition that the smart spoofer acts as the leader with privilege over the receiver. Moreover the Stackelberg equilibrium of static authentication strategy is derived. Then, we propose a dynamic game-based strategy according to reinforcement learning technique named Policy Hill Climbing, in which the spoofer always choose equilibrium solution and the receiver is unaware of the system parameters, such as the channel timevarying coefficient. Simulation results are presented to validate the effectiveness of the proposed authentication strategy, and the Policy Hill Climbing algorithm improves the utility compared with Q-learning-based algorithm.