计算机与数字工程2012，Vol.40Issue(5)：82-83,148,3.
基于模糊C均值算法的入侵检测方法
An Approach for Intrusion Detection Based on Fuzzy C-means Algorithm
林荣亮 1张文波1
作者信息
- 1. 中国人民解放军92854部队 湛江524005
- 折叠
摘要
Abstract
Clustering analysis is an effective method of anomaly intrusion detection,which can find normal flow and abnormal flow in the network data set. Fuzzy C-means clustering algorithm is applied to classify the network traffic data into normal flow and abnormal flow. A new clustering center method which is designed for intrusion detecting problem specially is provided in this paper. Finally. KDD 99 data set is used for the illustrative example , and the result proves that this algorithm could discover the abnormal flows effectively.关键词
模糊聚类/入侵检测/距离测度/模糊C均值Key words
fuzzy clustering/ intrusion detection/ distance measurement/ fuzzy C-means algorithm分类
信息技术与安全科学引用本文复制引用
林荣亮,张文波..基于模糊C均值算法的入侵检测方法[J].计算机与数字工程,2012,40(5):82-83,148,3.
