Application of Bayes learning algorithm to classify network traffic

doi:10.3778/j.issn.1002-8331.2010.25.023

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (25): 78-81.DOI: 10.3778/j.issn.1002-8331.2010.25.023

• 网络、通信、安全 • Previous Articles Next Articles

Application of Bayes learning algorithm to classify network traffic

QIU Mi¹，YANG Ai-min^1，2，LIU Yong-ding¹，HE Zhen-kai¹

1.School of Computer and Communication，Hunan University of Technology，Zhuzhou，Hunan 412008，China
2.Information Science and Technology College，Guangdong University of Foreign Studies，Guangzhou 510006，China

Received:2009-02-18 Revised:2009-04-13 Online:2010-09-01 Published:2010-09-01
Contact: QIU Mi

使用贝叶斯学习算法分类网络流量

邱密¹，阳爱民^1，2，刘永定¹，何震凯¹

1.湖南工业大学计算机与通信学院，湖南株洲 412008
2.广东外语外贸大学信息科学技术学院，广州 510006

通讯作者: 邱密

Abstract

Abstract: As network applications such as P2P rapidly increase，which makes the efficiency of traditional network traffic classification method that is based on the port and payload reduces.In this paper，it introduces a FCBF feature selection method，which can choose the best feature subsets.It uses Bayes learning algorithm to classify the network.The result of experiment shows a better classification accuracy.

摘要： 随着网络应用（如P2P）的快速增长，使得传统的基于端口与有效载荷的网络流量分类方法效率大大降低。基于FCBF特征选择方法选择最优特征子集，研究使用贝叶斯学习方法对网络流量进行分类；实验结果显示提出的方法取得了较好的分类准确率。

CLC Number:

TP309

QIU Mi¹，YANG Ai-min^1，2，LIU Yong-ding¹，HE Zhen-kai¹. Application of Bayes learning algorithm to classify network traffic[J]. Computer Engineering and Applications, 2010, 46(25): 78-81.

邱密¹，阳爱民^1，2，刘永定¹，何震凯¹. 使用贝叶斯学习算法分类网络流量[J]. 计算机工程与应用, 2010, 46(25): 78-81.

[1]	WANG Baowen，WU Xiaoliang，LI Ruiting，LIU Weilong. New verifiable multi-secret sharing scheme [J]. Computer Engineering and Applications, 2011, 47(4): 90-92.
[2]	HU Ming，PAN Xuezeng，LI Wen. Design and implementation of improved multiple-level security model [J]. Computer Engineering and Applications, 2011, 47(4): 77-80.
[3]	WANG Chuancai¹，PAN Feng^1，2，SHEN Junwei¹. Multi-level access control scheme of image ROI based on Hash chains [J]. Computer Engineering and Applications, 2011, 47(4): 81-83.
[4]	ZHONG Hong^1,2，SUN Yanfei²，YAN Feifei²，HUANG Hongsheng². Protocol for privacy-preserving space closest-pair of points [J]. Computer Engineering and Applications, 2011, 47(4): 87-89.
[5]	FENG Fan^1，2，WANG Jiazhen¹，LIU Huiying¹，WANG Huiping²，GUO Jingtao2，ZHANG Bin¹. Blind steganalysis algorithm based on PCA and Hilbert envelope analysis [J]. Computer Engineering and Applications, 2011, 47(4): 93-96.
[6]	SONG Wangan¹，CHEN Hu¹，ZHANG Futai². New certificateless proxy signature scheme [J]. Computer Engineering and Applications, 2011, 47(4): 97-101.
[7]	LIU Xiaoya，XIN Xiaolong. Improved blind signature electronic cash scheme [J]. Computer Engineering and Applications, 2011, 47(4): 114-116.
[8]	LUO Weimin¹，LIU Jing²，LIU Jingbo¹，CHEN Xiaofeng¹. Research of worms propagation in social networks based on game theory [J]. Computer Engineering and Applications, 2011, 47(3): 74-77.
[9]	NING Guoqiang，LI Xiehua，YIN Zhangfei. Solution to secure instant messaging [J]. Computer Engineering and Applications, 2011, 47(3): 82-83.
[10]	YUE Sheng，XIN Xiaolong. Threshold signature scheme without trusted party [J]. Computer Engineering and Applications, 2011, 47(3): 87-89.
[11]	LIU Yun，ZHENG Yongai. Novel encryption scheme for color image based on chaotic system [J]. Computer Engineering and Applications, 2011, 47(3): 90-93.
[12]	GUO Zhen，ZHANG Jianzhong，LAN Jianqing. Analysis and improvement of dynamic（t，n） threshold multi-secret sharing scheme [J]. Computer Engineering and Applications, 2011, 47(3): 110-112.
[13]	HU Guozheng¹，HAN Lansheng²，XIA Xiangsheng³. Security analysis of efficient certificateless signature scheme [J]. Computer Engineering and Applications, 2011, 47(2): 19-20.
[14]	CHEN Gang¹，CHEN Ning²，HU Anfeng². Image watermarking algorithm based on integer wavelet transform to resist geometric attacks [J]. Computer Engineering and Applications, 2011, 47(2): 185-189.
[15]	WU Rong. Composited authorization model for workflow applications [J]. Computer Engineering and Applications, 2011, 47(2): 91-94.

Application of Bayes learning algorithm to classify network traffic

使用贝叶斯学习算法分类网络流量

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics