Application of deep learning model in computer data mining intrusion detection
Online veröffentlicht: 06. Juni 2023
Seitenbereich: 2131 - 2140
Eingereicht: 13. Aug. 2022
Akzeptiert: 01. Dez. 2022
DOI: https://doi.org/10.2478/amns.2023.1.00318
Schlüsselwörter
© 2023 Yan Chen et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
In order to improve the autonomous defense ability and correct detection rate of network intrusion detection system, in this essay, an intrusion detection model combining convolutional neural network and Inception network structure is proposed, and the attention mechanism is set in the model, and DropBlock layer is added. In this model, convolutional neural network layer is used to fully extract data features. The attention mechanism is used to calculate the weight of each feature to distinguish the importance of the feature. The DropBlock layer is used to improve the generalization ability of the model, improve the accuracy of intrusion detection and reduce the complexity of the model. Experiments on data sets show that this model has higher accuracy and stronger generalization ability.