%0 Journal Article
%T Kernel-based Adaptive K-medoid Clustering and its Application in Intrusion Detection<br>基于核的自适应聚类及其在入侵检测中的应用
%A SUN Sheng
%A WANG Yuan-zhen
%A <br>孙胜
%A 王元珍
%J 计算机科学
%D 2008
%I 
%X Aiming at the weakness of k-medoid algorithm that it is unable effectively to cluster large data set and high-dimension data,kernel-based learning method was introduced to the k-medoid clustering algorithm,kernel-based adaptive k-medoid algorithm was proposed,and it can cluster large data set and high-dimensional data.The results of experiment using the data sets of KDD cup 99 demonstrate that the algorithm has excellent capability and applying it in intrusion detection system can be an effective way.
%K Cluster
%K Kernel method
%K Kernel function
%K K-medoid
%K Anomaly detection<br>聚类
%K 核方法
%K 核函数
%K k-中心点
%K 异常检测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=FDD7DFEE1E380CDA8840A93ABF50C489&yid=67289AFF6305E306&vid=6209D9E8050195F5&iid=59906B3B2830C2C5&sid=6235172E4DDBA109&eid=AC1578C6BB9EBDEF&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=8