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基于FCM和RBF网络的入侵检测研究
引用本文:邓广慧,唐贤瑛,夏卓群.基于FCM和RBF网络的入侵检测研究[J].电脑与信息技术,2006,14(1):6-8,62.
作者姓名:邓广慧  唐贤瑛  夏卓群
作者单位:长沙理工大学计算机与通信工程学院,湖南,长沙,410076
摘    要:入侵检测过程广义上属于分类和模式识别的范畴。文章提出了用模糊C-均值聚类法将网络连接信息聚类,再通过训练RBF网络存储数据并进行识别的入侵检测方法,分析了网络连接信息中的正常网络信息和各种不同的攻击信息。通过仿真实验,该方法取得了较好的实验结果。

关 键 词:入侵检测  模糊C-聚值聚类法  RBF网络
文章编号:1005-1228(2006)01-0006-03
收稿时间:2005-11-24
修稿时间:2005-11-24

Research on FCM and RBF network-based intrusion detection
DENG Guang-hui,TANG Xian-ying,XIA Zhuo-qun.Research on FCM and RBF network-based intrusion detection[J].Computer and Information Technology,2006,14(1):6-8,62.
Authors:DENG Guang-hui  TANG Xian-ying  XIA Zhuo-qun
Affiliation:Computer and Communication Engineering Department , Changsha University of Science and Technology, Changsha,Hunan 410076,China
Abstract:Intrusion detection belongs to the category of classification and pattern recognization in a broad sense. FCM is addressed to classify the network connection records and RBF network is applied to train these records so as to store and to recognize the information . This paper analyzes the normal network information and various intrusion information in the network connection records . Experiments show its fine detecting performance.
Keywords:intrusion detection  Fuzzy C-mean clustering(FCM)  RBF network
本文献已被 CNKI 维普 万方数据 等数据库收录!
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