The emergence of P2P and fast-flux technology makes botnet more covert.The traditional recognition method of feature extraction is more and more difficult,and the recognition accuracy is low.In order to solve the above problems,this paper designs a new fusion network structure based on CNN and LSTM.In this method,convolutional neural network with improved activation function and network structure was used to detect spatial features,and LSTM network was used to detect temporal features.Experimental results show that the method can meet the needs of Botnet identification in terms of accuracy and recall.
关键词
僵尸网络/卷积神经网络/长短时记忆网络/特征并联融合/激活函数
Key words
Botnet/Convolutional Neural Network(CNN)/Long and short-term memory(LSTM)/Feature parallel fusion/Activation function
维普
万方数据