Research on Information Fusion Method Based on sFlow and Netflow in Network Security Situation

被引：0

作者：

Wang, Yanbo ^{[1
]}

Wang, Huiqiang ^{[1
]}

Han, Chengqin ^{[1
]}

Ge, Baoyu ^{[1
]}

Yu, Ming ^{[2
]}

机构：

[1] Harbin Engn Univ, Coll Comp Sci & Technol, Harbin 150001, Peoples R China

[2] Northeast Forestry Univ, Informat & Comp engn coll, Harbin 150040, Peoples R China

来源：

EMERGING INTELLIGENT COMPUTING TECHNOLOGY AND APPLICATIONS | 2012年 / 304卷

基金：

高等学校博士学科点专项科研基金; 中国国家自然科学基金; 黑龙江省自然科学基金;

关键词：

sFlow; netflow; data fusion; bayes; fuzzy clustering;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper firstly analyses the characteristic of sFlow and Netflow data as situation awareness data source, then introduces the current common used information fusion methods, and researches the applicability of various methods in the network safety situation awareness system based on sFlow and Netflow. Finally, an improved fusion algorithm is proposed which is combined Bayes estimation and fuzzy clustering method. This method can effectively integrate the information from different data source, and fused data is more credible and comprehensive. It provides important data basis and theoretical guidance for analysis and realization of the network security situation.

引用

页码：139 / +

页数：2