DNFD-SRU: A Distributed Network Fault Detection Method Based on SRU

Traditional network fault detection methods need to collect data for training, which has data security problems. In recent years, as people pay more and more attention to data privacy, how to ensure data security has become more and more important. At the same time, because the network fault detection needs to meet certain real-time requirements, how to improve the detection speed is also an urgent problem to be solved. Based on the above two problems, this paper proposes a network fault detection algorithm DNFD-SRU based on federated learning and SRU. Federated learning can train the model on the premise of ensuring data security, and SRU has faster training speed.