%0 Journal Article
%T Research of K-means algorithm based on particle swarm optimization in network intrusion detection<br>基于粒子群优化的k均值算法在网络入侵检测中的应用
%A GU Bao-ping
%A XU Xiao-yuan
%A GUO Hong-yan
%A <br>谷保平
%A 许孝元
%A 郭红艳
%J 计算机应用
%D 2007
%I 
%X Based on the k-means algorithm, we proposed the PSO-k-means algorithm combining the k-means with PSO. Then KDD cup 99 dataset was applied to both algorithms. The experiment indicates that the PSO-k-means algorithm can avoid the inherent shortcomings of the k-means algorithm, and has higher detection performance with detection rate rising and false alarm rate falling.
%K k-means algorithm
%K PSO algorithm
%K PSO-k-means
%K intrusion detection<br>k均值算法
%K 粒子群算法
%K PSO-k均值
%K 入侵检测
%K 粒子群优化
%K 均值算法
%K 网络
%K 入侵检测
%K 应用
%K network
%K intrusion
%K detection
%K particle
%K swarm
%K optimization
%K based
%K algorithm
%K 误报率
%K 检测率
%K 结果
%K 试验
%K 检测性能
%K 评估
%K 数据集
%K 结合
%K 粒子群算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=14E16CBD27430512AAD7186AFDED435B&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=B31275AF3241DB2D&sid=5A64531D29896B77&eid=CDE3E49FCD9EE463&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=7