计算机工程与应用2012，Vol.48Issue(29)：105-108,4.DOI:10.3778/j.issn.1002-8331.2012.29.021
神经网络集成模型在入侵检测中的应用
Neural network ensembles model for intrusion detection
摘要
Abstract
Intrusion detection is a central issue of network security research. This paper proposes a new neural network ensembles model for intrusion detection system. The model trains the individual networks based on data reducing. Genetic algorithm is used to optimize neural network weight. Neural network techniques are used to combine the different classification results. Theory and experiment show that the model is effective.关键词
神经网络集成/属性选择/遗传算法/入侵检测Key words
neural network ensembles/ attribute selection/ genetic algorithm/ intrusion detection分类
信息技术与安全科学引用本文复制引用
徐敏,丁红,沈晓红..神经网络集成模型在入侵检测中的应用[J].计算机工程与应用,2012,48(29):105-108,4.基金项目
南通市应用研究项目(No.K2010053). （No.K2010053）
