通信学报

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未知网络应用流量的自动提取方法

王变琴,余顺争   

  1. 1. 中山大学 东校区教学实验中心,广东 广州 510006;2. 中山大学 信息科学与技术学院,广东 广州 510006
  • 出版日期:2014-07-25 发布日期:2014-07-15
  • 基金资助:
    国家自然科学基金资助项目(61202271);广东省自然科学基金资助项目(S2012040007184);国家自然科学基金-广东联合基金资助项目(U0735002)

Automatic extraction for the traffic of unknown network applications

  • Online:2014-07-25 Published:2014-07-15

摘要: 提取未知网络应用特征时需要获得其流量数据,但在网络工程中,采集的未知应用流量往往是几种应用流量的混合,如何将未知混合流量进行分离,按照应用进行归类是现有方法没有解决的问题。基于此提出一种基于载荷信息的流量聚类方法,该方法通过对报文载荷的部分字节编码,采用扩展的ROCK算法对未知混合流量进行分离,按照不同应用进行归类。实验结果表明,与基于会话行为特征(一种流量统计特征)的流量聚类方法相比,这种方法具有较高的精确度。

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.

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