Network Attack Detection Based on Neural Network LSTM

摘要：

　　With the development of the times,the network security problem is becoming more and more serious,and the form of network attack is more complex and diverse.It can effectively detect various network attacks becomes the basis for effective prevention of network attacks.In recent years,artificial intelligence has attracted more and more peoples attention,and its good learning ability has been favored by people.This paper uses the LSTM neural network with long and short memory function to train the KDD99 dataset,and identify the DOS according to the trained model.This is a research process of the planned adjustment for the hyperparameters to find the optimal solution after processing the data.

关键词： recurrent neural network network attacks hyperparameter training model

作者: Zichao Sun Peilin Lyu

作者单位: Information and Communication,Communication University of China,Beijing,China Jilin University,Jilin,China

会议类型: 国际会议

会议名称: 2019 2nd International Conference on Mechanical, Electronic and Engineering Technology (MEET 2019) 2019年第二届机电与工程技术国际会议

会议地点: 西安

会议语种:英文

页码: 1-6

在线出版日期: 2019-01-19（万方平台首次上网日期，不代表论文的发表时间）