改进深度神经网络的网络入侵检测算法  

Improved network intrusion detection algorithm for deep neural network

作　　者：李云 魏仕俊 LI Yun;WEI Shijun(Unit 75841 of PLA,Changsha 410000,China)

机构地区：[1]75841部队,长沙410000

出　　处：《计算机应用文摘》2024年第15期109-111,共3页Chinese Journal of Computer Application

摘　　要：为了解决传统入侵检测算法检测精度低的问题,文章提出了一种改进深度神经网络的网络入侵检测算法,首先对网络入侵数据进行了采集和预处理,然后利用预处理后的入侵数据进行线性入侵定位,最终基于离散定位结果实现了改进深度神经网络的网络入侵检测。实验结果表明,该方法能够高效实现对网络入侵的精准检测。In order to solve the problem of low detection accuracy of traditional intrusion detection algorithms,this article proposes an improved deep neural network network intrusion detection algorithm.Firstly,the network intrusion data is collected and preprocessed,and then the preprocessed intrusion data is used for linear intrusion localization.Finally,based on the discrete localization results,the improved deep neural network network intrusion detection is achieved.The experimental results show that this method can efficiently achieve accurate detection of network intrusion.

关 键 词：改进神经网络 网络入侵 数据采集 特征提取 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]