计算机应用研究2017，Vol.34Issue(8)：2429-2433,5.DOI:10.3969/j.issn.1001-3695.2017.08.043
基于特征选择的网络入侵检测方法
Feature selection based approach to network intrusion detection
摘要
Abstract
The intrusion detection system deals with huge amount of data which contains redundant and noisy features causing poor detection rate and slow training process.This paper introduced feature selection algorithm into the field of intrusion detection,and put forward a intrusion detection method based on feature selection.It used different discretization and feature selection algorithm to extract difference of multiple optimal feature subset,followed by normalizing the extracted feature subsets to perform a normalizing process.At last it applied the classification algorithm to create a model.Compared with the traditional algorithm (decision tree,naive Bayes,support vector machine),the experimental results demonstrate that the approach can effectively improve the precision of attack-detection and training cycle.关键词
入侵检测/特征选择/机器学习Key words
intrusion detection/feature selection/machine learning分类
信息技术与安全科学引用本文复制引用
戴远飞,陈星,陈宏,叶靓,林俊鑫,郭文忠..基于特征选择的网络入侵检测方法[J].计算机应用研究,2017,34(8):2429-2433,5.基金项目
国家自然科学基金资助项目(61402111) （61402111）
福建科技重大项目(2015H6013) （2015H6013）
厦门市重大科技计划项目(3502Z20151010) （3502Z20151010）
