现代电子技术2024，Vol.47Issue(19)：33-39,7.DOI:10.16652/j.issn.1004-373x.2024.19.006
基于MobileViT的轻量型入侵检测模型研究
Research on lightweight intrusion detection model based on MobileViT
姚军 1孙方超1
作者信息
- 1. 西安科技大学 通信与信息工程学院,陕西 西安 710000
- 折叠
摘要
Abstract
In view of the data imbalance on the training of neural network model and the large number of model parameters in intrusion detection,an intrusion detection model based on improved MobileViT is proposed.The ANOVA(analysis of variance)is used to extract the features with great impact on the detection results,and the extracted features are converted into image-based data and input into the MobileViT network.For the attack traffic with a small proportion,the focus loss function is used to adjust the loss contribution of the attack traffic adaptively,so that the model can focus more on the unbalanced attack traffic.In order to solve the problem of neuronal death,the GeLU activation function is used to replace the ReLU6 activation function of MV2 in the MobileViT network to accelerate the convergence speed of the model.The results of experiments show that the improved MobileViT model has only 5.67 MB of parameters.It has the least parameters in comparison with Shufflenet and Mobilenet.The accuracy rate,recall rate and F1 score of the model reach 98.40%,96.49%and 95.17%,respectively.关键词
入侵检测/焦点损失函数/数据不平衡/MobileViT/GeLU/方差分析Key words
intrusion detection/focus loss function/data imbalance/MobileViT/GeLU/ANOVA分类
电子信息工程引用本文复制引用
姚军,孙方超..基于MobileViT的轻量型入侵检测模型研究[J].现代电子技术,2024,47(19):33-39,7.
