LEA: A Leader Election Algorithm for Distributed Physical Layer Authentication

Physical layer authentication (PLA) as a promising solution has gained widespread attention due to its high security and lightweight deployment. A fixed authentication center is vulnerable to attacks, making both centralized PLA (CPLA) with a single authentication center and collaborative PLA with multiple collaboration nodes at risk of a single point of failure. In this paper, we propose a leader election algorithm for distributed physical layer authentication, where multiple receivers are col-laboratively trained under a leader and complete authentication independently. Specifically, the one with the strongest model generalization ability is elected as the leader by individual receivers voting based on data quality. The role of the leader is to filter out the underperforming receivers, assign reasonable weights to local models, and construct an authentication white list to achieve better authentication performance. Simulation results show that the proposed scheme outperforms the randomly selected leader and the traditional PLA schemes.