Journal on Communications ›› 2014, Vol. 35 ›› Issue (7): 164-171.doi: 10.3969/j.issn.1000-436x.2014.07.020

• paperⅡ • Previous Articles     Next Articles

Automatic extraction for the traffic of unknown network applications

Bian-qin WANG1,Shun-zheng YU2   

  1. 1 Education&Experiment Center,East Campus,Sun Yat-sen University,Guangzhou 510006,China
    2 School of Information Science and Technology,Sun Yat-sen University,Guangzhou 510006, China
  • Online:2014-07-25 Published:2017-06-24
  • Supported by:
    The National Natural Science Foundation of China;The Natural Science Foundation of Guangdong Province;The Key Program of NSFC-Guangdong Joint Funds

Abstract:

The features of unknown network applications can be extracted using its traffic data. However, the sample traffic in network engineering is usually a mixed traffic generated by several unknown applications. The separation of the mixed traffic by applications an unsolved problem presently. A clustering method for traffic classification was proposed based on payload information. The proposed method can firstly encode certain bytes of message payload, then separate and classify the unknown mixed traffic using an extended ROCK algorithm. The experiment results reveal that compared with the clustering method based on statistics character of traffic, the proposed method has higher accuracy.

Key words: traffic classification, behavioral features of session, payload, ROCK algorithm

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