现代电子技术2024，Vol.47Issue(18)：47-51,5.DOI:10.16652/j.issn.1004-373x.2024.18.008
基于联邦学习的无线通信网络DoS攻击检测方法
Method of wireless communication network DoS attack detection based on federation learning
马玉梅 1张东阳1
作者信息
- 1. 华北电力大学(保定)计算机系,河北 保定 071003
- 折叠
摘要
Abstract
A DoS attack on wireless communication network can increase network load,resulting in more delay.In wireless communication network,data is usually scattered across multiple nodes,which can lead to data leakage and attack.Therefore,a method of wireless communication network DoS attack detection based on federation learning is proposed.The initial wireless communication network data is preprocessed and normalized,and the random forest algorithm is used for the dimensionality reduction to remove redundant feature and obtain the optimal network data feature set.The feature set is input into the federation learning training model with deep convolutional neural network as the general model,to independently train the local model and perform the model modification.It is transmitted to the central server for aggregation,and the training is completed after convergence.The trained federation learning model is used to detect the DoS attack rate in wireless communication network,and compared with the maximum capacity received by the receiver to determine whether there is a DoS attack.The experimental results show that the proposed method has high stability and reliability when processing large amounts of data,and can accurately detect DoS attack in a short time.关键词
联邦学习/无线通信网络/DoS攻击检测/深度卷积神经网络/随机森林算法/通用模型Key words
federation learning/wireless communication network/DoS attack detection/deep convolutional neural network/random forest algorithm/universal model分类
电子信息工程引用本文复制引用
马玉梅,张东阳..基于联邦学习的无线通信网络DoS攻击检测方法[J].现代电子技术,2024,47(18):47-51,5.
