Using Text Mining Techniques for Intrusion Detection Problem in Computer Network
Using Text Mining Techniques for Intrusion Detection Problem in Computer Network
复制标题
利用文本挖掘技术解决计算机网络入侵检测问题
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
Won Min
中科院分区：
文献类型：
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作者：
Oh Seung;Won Min
近年来，将数据挖掘技术应用于计算机网络入侵检测已经引起了人们的极大兴趣。一种新的方法，基于k-最近邻（kNN）分类器，被用来分类程序行为正常或侵入。每个系统调用都被视为一个单词，每个程序执行过程中的系统调用集合被视为一个文档。然后使用kNN分类器对这些文档进行分类，kNN分类器是文本挖掘中的一种流行方法。一个简单的例子说明了所提出的程序。
Recently there has been much interest in applying data mining to computer network intrusion detection. A new approach, based on the k-Nearest Neighbour(kNN) classifier, is used to classify Program behaviour as normal or intrusive. Each system call is treated as a word and the collection of system calls over each program execution as a document. These documents are then classified using kNN classifier, a Popular method in text mining. A simple example illustrates the proposed procedure.