摘要
The traffic model and application identification of Wechat has gained a great concern. First of all, Wechat traffic model was deep analyzed and concluded. It could be concluded that the traffic was a pulsed long-live connection. Furthermore, the applicability and economy of this pattern on Wechat were analyzed. Secondly, a method was proposed to accurately identify the Wechat traffic using deep packet inspection, and a payload-based signature was given. Finally, the sub-functions of Wechat in a fine-grained fashion was classified. Several algorithms were proposed to assist different sub-functions to improve their accuracy of identification. Experimental results showed that our proposed approaches could achieve the accuracy of 98% in identification and the accuracy of 52% in classification of sub-functions.
源语言 | 英语 |
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页(从-至) | 257-263 |
页数 | 7 |
期刊 | Dongbei Daxue Xuebao/Journal of Northeastern University |
卷 | 35 |
出版状态 | 已出版 - 1 10月 2014 |