计算机工程2011，Vol.37Issue(17)：113-115,3.
基于快速属性约简的网络入侵特征选择
Network Intrusion Feature SelectionBased on Fast Attribute Reduction
摘要
Abstract
Aiming to problem that independent and redundant attributes of high dimensional network data cause classification algorithms' slow detection speed and low detection rate in network intrusion detection, this paper presents a feature selection method for network intrusion based on fast attribute reduction. It adopts Mutual Information(MI) between condition and label attributes of network data as measure to discard independent attributes, then a formula for measuring attribute importance based on positive region of rough set is applied as heuristic information to design a fast attribute reduction algorithm, which removes redundant attributes of network data to realize optimal selection of feature subset of network intrusion. Simulation experiment is done in KDDCUP1999. Result shows that the method is more effective in discarding independent and redundancy attributes and it has higher intrusion detection rate and lower false positive rate.关键词
互信息/粗糙集/属性约简/特征选择/网络入侵检测Key words
Mutual Information(MI)/ rough set/ attribute reduction/ feature selection/ network intrusion detection分类
信息技术与安全科学引用本文复制引用
牟琦,龚肖福,毕孝儒,犀向阳..基于快速属性约简的网络入侵特征选择[J].计算机工程,2011,37(17):113-115,3.基金项目
陕西省自然科学基金资助项目(2009JM7007) （2009JM7007）
