| 摘要: |
| 利用动态自反馈理论改造模糊聚类过程,分析入侵数据类型及其在入侵中所起的作用,提出一种面向混合数据的自反馈模糊聚类分析算法,并用算法对KDD99数据集进行对比测试。测试结果显示,本方法能够有效提高入侵检测引擎的检测率,降低其误报率,增强计算机系统抵御入侵及自身免疫能力。 |
| 关键词: 入侵检测 模糊聚类 自反馈 FCMBP |
| DOI： |
| 投稿时间：2007-06-30 |
| 基金项目:广西科技攻关项目(桂科攻关0385001);广西留学回国人员科学基金项目(桂科回0342001)资助 |
|
| A Feedback Fuzzy Clustering Method Oriented Mixed Data |
|
LINGHU Da-zhi1, LI Tao-shen2
|
| (1.Department of Computer and Information Management, Guangxi Finance and Economics College, Nanning, Guangxi, 530003, China;2.School of Computer, Electronics and Information, Guangxi University, Nanning, Guangxi, 530004, China) |
| Abstract: |
| This paper uses dynamic feedback theory to reconstruct fuzzy clustering process and analyze intrusion data types and it's roles in intrusion activity.A feedback fuzzy clustering algorithm oriented mixed data is proposed,and the algorithm's performance is tested by using KDD99 date set.The experimental results show that the method can effectively increase the detection rates of intrusion detection engine and reduce their error rate,and enhance computer systems against intrusion and self-immunity. |
| Key words: intrusion detection fuzzy cluster self-feedback FCMBP |
