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Network Attack Detection Based on Neural Network LSTM

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DOI: 10.23977/meet.2019.93701


Zichao Sun, Peilin Lyu

Corresponding Author

Zichao Sun


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 people's 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.


Recurrent Neural Network, Network Attacks, Hyperparameter, Training Model

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