Abstract: Network has penetrated into all fields of people’s production and life. However, due to the existence of a large number of illegal intrusions, the network is facing more and more serious security problems. Therefore, detecting intrusion to ensure network security is an urgent problem to be solved. In order to solve this problem, an intrusion detection method based on heterogeneous convolution neural network is proposed. The convolution neural network model of deep learning is used to extract the intrusion data features. Then the optimal model is obtained according to the training data of convolution neural network with two different structures, which can be used to judge the network intrusion. Finally, experiment on KDD 99 verifies the accuracy and accuracy of the method proposed in this paper.

Key words: deep learning, convolutional neural network, heterogeneous convolutional neural network, intrusion detection, network security