摘要
采用主成分分析法和K-均值聚类算法,对当前的计算机入侵监测系统进行优化。主成分分析法将数据进行降维,K-均值聚类算法将数据重新分类,将两种算法结合对网络流量的数据进行预处理后,使得该系统具有更高的准确率和更低的误报率。
Principal Component Analysis and K-means clustering algorithm are used to optimize the current computer intrusion detection system.Principal component analysis is used to reduce the dimension of the data,K-means clustering algorithm is used to reclassify the data,after the two algorithms are combined to preprocess the network traffic data,the system has higher accuracy and lower false alarm rate.
作者
卢永祥
李巧兰
LU Yongxiang;LI Qiaolan(Center of Computer Technology and Experiment,Wuyi University,Wuyishan,Fujian 354300)
出处
《武夷学院学报》
2020年第9期42-47,共6页
Journal of Wuyi University
关键词
入侵检测系统
主成分分析
K-均值聚类算法
intrusion detection system
principal component analysis
K-means clustering algorithm
