Research on Network Attack Detection Model Based on BiGRU-Attention
Weifa Zheng, Peiyu Cheng, Zitao Cai, Yanjun Xiao · 2022
The BiGRU model does not consider the weight of features when extracting features. In order to solve this problem, this paper adds the Attention mechanism to the BiGRU hidden layer, uses the feature vector obtained from the BiGRU as the input of the Attention layer, and uses the attention score as the weight of the feature vector, so that the most important features are retained to the greatest extent. In this paper, BiGRU-Attention model is applied to network attack traffic detection, and CIDDS data set is used for model training and testing. Experiments show that BiGRU-Attention model designed in this paper has high accuracy and F1 value.