现代电子技术2017，Vol.40Issue(1)：80-82,3.DOI:10.16652/j.issn.1004-373x.2017.01.022
基于人工鱼群算法优化神经网络在网络入侵检测中的应用研究
Application of neural network optimized by artificial fish swarm algorithm in network intrusion detection
朱小华1
作者信息
- 1. 浙江越秀外国语学院，浙江 绍兴 312000
- 折叠
摘要
Abstract
In order to solve the problems of low detection accuracy,high false alarm rate and low detection efficiency exis?ting in the traditional intrusion detection algorithm,a method of using artificial fish swarm algorithm to optimize the BP neural network algorithm is proposed in combination with the advantages of BP neural network algorithm in network intrusion detection. The simulation experiment results show that,in comparison with the traditional intrusion detection algorithm,the optimized neu?ral network has higher accuracy and efficiency while learning and detecting the intrusion data,can detect various network intru?sion types better,and improve the network safety performance greatly.关键词
BP神经网络/人工鱼群算法/入侵检测/优化模型Key words
BP neural network/artificial fish swarm algorithm/intrusion detection/optimization model分类
信息技术与安全科学引用本文复制引用
朱小华..基于人工鱼群算法优化神经网络在网络入侵检测中的应用研究[J].现代电子技术,2017,40(1):80-82,3.
