Incremental Clustering Algorithm for Intrusion Detection Based aiNet

摘要：

In order to improve the intrusion detection systems self-learning,self-organizing capability and ability to handle huge amounts of data,to enhance detection capabilities,an aiNet incremental clustering algorithm is raised in this paper. This method combines the principles of artificial immune cloning selection,affinity maturation and network suppression,effectively increase the capacity of self-learning and intelligent;the incremental clustering and sub-cluster merger thinking applied to the algorithm,effectively improve the efficiency of clustering;design testing laboratories,experimental results showing that the detection effect is good.

关键词： artificial immune network incremental clustering intrusion detection system

作者: Jiankang Liu Liu Cheng

作者单位: Sichuan Agricultural University,Dujiangyan 611830,China

会议类型: 国际会议

会议名称: 2010 International Forum on Computer Science-Technology and Applications(2010 国际计算机科学技术应用论坛 IFCSTA 2010)

会议地点: 南宁

会议语种:英文

页码: 36-38

在线出版日期: 2010-12-10（万方平台首次上网日期，不代表论文的发表时间）