Research on New Network Security Early Warning Method Based on Improved Deep Neural Network
In order to further improve the performance of network intrusion detection,this paper proposes a network intrusion detection method based on improved deep neural network.First,the unsupervised sparse self-en-coder(SAE)was regularized by L1 to enhance the sparsity of the automatic data encoder;Then,the unsupervised SAE was introduced into the deep neural network to establish the intrusion detection network intrusion model.The deep neural network was used to complete the prediction and classification of network attack intrusion,and the feature extraction of intrusion attack was completed through classification.Finally,in order to verify the superiority of the model in terms of detection rate and low false positive rate,the paper used KDDCup99,NSL-KDD and other data sets for validation.The results show that compared with the traditional methods,the accuracy and detection rate of the pro-posed method are improved by about 10%.
Deep neural networkNetwork early warningIntrusion detection
NETL
NSTL
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