关键词: 长短期记忆网络, 动态域名生成算法, 卷积神经网络, 门控循环单元, 深度学习, 网络空间安全

Abstract: For solving the problem of detection diffculty of the DGA domain name,this paper proposed a new DGA domain detection model from the viewpoint of character level by deep learning model.The model consisted of character embedding layer,feature detection layer and classification prediction layer.The character embedding layer realizes the digital encoding of DGA domain.The feature detection layer adopts the deep learning model to extract features automati-cally,and the classification prediction layer adopts neural network for classification prediction.In order to select the optimal model of feature extraction,the LSTM and GRU models using Bidirectional mechanism,Stack mechanism,Attention mechanism,CNN models and CNN models integrated respectively with LSTM and GRU model were compared.The results show that the LSTM and GRU models using Stack mechanism and Attention mechanism integrated with Bidirectional mechanism,CNN models and CNN models integrated with LSTM and GRU model can improve the detection effect.The DGA domain detection model using CNN model integrated with Bi-GRU can obtain the optimum detection effect.

Key words: Convolutional neural network, Cyberspace security, Danamic domain generation algorithms, Deep learning, Gatedrecurrent unit, Long short-term memory