摘要
将网络数据流聚类来实现负载平衡已经被广泛应用于集群入侵检测方法中。将相关性思想引入传统模糊C-均值聚类算法(FCM),给出数据流逻辑距离公式,提出了一种相关模糊C-均值聚类算法(CFCM)。最后,将此算法应用于集群入侵检测方法中,利用KDDCup1999数据集进行实验,验证其可行性及准确性。
Clustering Web flows to attain Load Balancing is widely used in Clustering Intrusion Detection approach. Correlated ideas were imported in the traditional fuzzy C-means clustering algorithm (FCM), defined logical distance formula,and presented a Correlated fuzzy C-means clustering algorithm(CFCM). At last we applied this approach in Clustering Intrusion Detection approach, and used KDD Cup 1999 data set to do experiment. The results demonstrated the viability and effectiveness of our approach.
出处
《计算机科学》
CSCD
北大核心
2010年第6期176-178,222,共4页
Computer Science
基金
重庆市自然科学基金重点项目"软件测试技术和方法研究"(CSTC
2006BA2003)资助
关键词
相关性思想
CFCM
集群入侵检测方法
Correlated ideas, CFCM, Clustering Intrusion Detection approach