Data Stream Clustering Algorithm Based on Bucket Density for Intrusion Detection

被引：1
|
作者：
Yin, Chunyong [1 ]
Xia, Lian [1 ]
Wang, Jin [2 ]
机构：
[1] Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Jiangsu Engn Ctr Network Monitoring, Sch Comp & Software, Nanjing, Jiangsu, Peoples R China
[2] Yangzhou Univ, Coll Informat Engn, Yangzhou, Jiangsu, Peoples R China
来源：
ADVANCES IN COMPUTER SCIENCE AND UBIQUITOUS COMPUTING | 2018年 / 474卷
基金：
中国国家自然科学基金;
关键词：
Data streams; Density; Clustering algorithm; Intrusion detection;
D O I：
10.1007/978-981-10-7605-3_134
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The ability to process data streams has become one of the challenges of the current intrusion detection systems. A data stream clustering algorithm based on bucket density is proposed for this situation which is able to identify clusters in any shapes and the speed of online layer is fast. Feedback principle is used to solve the problem that some of the edge of the bucket is lost and users does not need to specify the number of clusters. An intrusion detection system is constructed with the improved algorithm. The experiment shows that the algorithm proposed has fast speed for clustering. The system based on the algorithm has a better capability of detection.
引用
收藏
页码：846 / 850
页数：5
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