现代电子技术2017，Vol.40Issue(21)：80-83,4.DOI:10.16652/j.issn.1004-373x.2017.21.022
蚁群算法选择神经网络参数的网络入侵检测
Network intrusion detection based on ant colony optimization algorithm selecting parameters of neural network
刘芳芳1
作者信息
- 1. 长春理工大学 光电信息学院 信息工程分院,吉林 长春 130000
- 折叠
摘要
Abstract
In order to improve the precision of network intrusion detection,a network intrusion detection model based on ant colony optimization selecting parameters of neural network is proposed. The data of network intrusion detection is collected, and the neural network is used to learn the intrusion detection data. The ant colony optimization algorithm is employed to select the parameters of neural network,which is verified with the standard intrusion detection data. The contrastive analysis is per-formed for the intrusion detection model and other models. The results show that the model can solve the difficulty of neural net-work parameter optimization,reduce the error rate of network intrusion detection,improve the precision of network intrusion de-tection,and is conducive to ensuring the network security.关键词
网络安全/非法用户/入侵检测/蚁群算法Key words
network security/illegal user/intrusion detection/ant colony optimization分类
信息技术与安全科学引用本文复制引用
刘芳芳..蚁群算法选择神经网络参数的网络入侵检测[J].现代电子技术,2017,40(21):80-83,4.
