TCP/IP Feature Reduction in Intrusion Detection

被引：0
|
作者：
LIU Yuling
机构：
来源：
Wuhan University Journal of Natural Sciences | 2007年 / 01期
关键词：
intrusion detection; feature reduction; decision tree; data mining;
D O I：
暂无
中图分类号：
TP393.08 [];
学科分类号：
0839 ; 1402 ;
摘要：
Due to the amount of data that an IDS needs to exam- ine is very large, it is necessary to reduce the audit features and neglect the redundant features. Therefore, we investigated the performance to reduce TCP/IP features based on the decision tree rule-based statistical method(DTRS). Its main idea is to create n decision trees in n data subsets, extract the rules, work out the relatively important features in accordance with the frequency of use of different features and demonstrate the performance of re- duced features better than primary features by experimental re- sults.
引用
收藏
页码：151 / 154
页数：4
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