Pilot spoofing detection algorithm for edge nodes based on heterogeneous pilot energy estimation - Shiguo WANG; Shujuan TIAN; Qingyong DENG (Tongxin xuebao)
For the federated learning scenarios with edge-end cooperation, edge servers and device terminals update their models and exchange gradient parameters frequently, and hence eavesdroppers can manipulate channel estimation through pilot spoofing to intercept the transmitted information and reduce the update efficiency of federated learning model.Therefore, a pilot attack detection algorithm with heterogeneous pilot energy estimation was proposed.Firstly, a federated learning pilot attack system model was constructed after the security of pilot attacks on data transmission had been analyzed.Then, a pilot attack detection method based on random segmentation and encryption methods was proposed to detect the pilot spoofing accurately and the contaminated channel could be recovered as well.Experimental results show that the proposed algorithm is more suitable for detecting pilot attacks with low transmit power and strong concealment compared to other existing algorithms.Furthermore, the data transmission rate of edge servers is improved significantly through the precoding based on the recovered channel state information.