%0 Journal Article
%T Intrusion detection model based on weighted multi-random decision tree<br>基于加权多随机决策树的入侵检测模型
%A ZHAO Xiao-feng
%A YE Zhen
%A <br>赵晓峰
%A 叶震
%J 计算机应用
%D 2007
%I 
%X The traditional decision tree category methods(such as:ID3,C4.5) are effective on small data sets.However,when these methods are applied to massive data of IDS,its effectivity will get influenced.In this paper,a random model based decision tree algorithm was applied,and an intrusion detection model based on it was provided.It is verified by experiment that this model is evidently powerful for IDS.
%K decision tree
%K intrusion detection
%K discernibility matrix
%K random decision tree<br>决策树
%K 入侵检测
%K 分辨矩阵
%K 随机决策树
%K 加权
%K 随机模型
%K 决策树
%K 计算机入侵
%K 检测模型
%K decision
%K tree
%K weighted
%K based
%K model
%K detection
%K 表现
%K 分类准确率
%K 对比试验
%K 分布式
%K 设计
%K 系统资源
%K 有效性
%K 数据集
%K 入侵检测
%K 算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=FB13A00A278E49ECF259EFD0EC2795C7&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=94C357A881DFC066&sid=8F39F7FDA07C2566&eid=42AB3C691163F5B1&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=13