|
|||||
|
|
| 基于SOM改进的K-Means聚类算法 | |
| 引用本文： | 侯丽敏,王文莉. 基于SOM改进的K-Means聚类算法[J]. 内蒙古大学学报(自然科学版), 2011, 42(5): 586-590 |
| 作者姓名： | 侯丽敏 王文莉 |
| 作者单位： | 郑州铁路职业技术学院信息工程系,郑州,450052 |
| 摘 要： | 随着网络技术和相关学科的发展,入侵检测技术日趋成熟.对SOM算法和K-Means算法进行了具体的分析,提出了一种基于SOM和K-Means的使两类算法优点相结合并克服各自不足的聚类算法,提高了聚类信息的精确度、对攻击的识别率和系统的整体性能. |
| 关 键 词： | K-Means算法 数据挖掘 入侵检测 网络安全 |
Improvement of K-Means Clustering Algorithm Based on SOM |
|
| HOU Li-min,WANG Wen-li. Improvement of K-Means Clustering Algorithm Based on SOM[J]. Acta Scientiarum Naturalium Universitatis Neimongol, 2011, 42(5): 586-590 | |
| Authors: | HOU Li-min WANG Wen-li |
| Affiliation: | HOU Li-min,WANG Wen-li(Department of Information Engineering,Zhengzhou Railway Vocational&Technical College,Zhengzhou 450052,China) |
| Abstract: | As a second line of defense for network security,intrusion detection technology is reaching maturity.SOM algorithm and the K-Means algorithm are analyzed.Combining their advantages and overcoming their shortcomings,a clustering algorithms is proposed.The new clustering algorithm can improve the accuracy of the information on the attacks,the recognition rate and the overall system performance. |
| Keywords: | K-Means algorithm data mining intrusion detection network security |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |