Internet traffic classification method based on behavior feature learning - Zhen LIU; Ruoyu WANG (Dianxin kexue)
The connection graph based internet traffic classification method can reflect the connectivity behavior between hosts.Thus，it has high stability.But the heuristic rules summarized for traffic classification are generally incomplete，and they difficultly obtain high classification accuracy.Host communication behavior model and BOF method was researched，and a set of host connection related behavior features （HCBF）was extracted from the multiple flows with the same ｛destination IP，destination port and transport protocol｝.To evaluate the performance of HCBF，it was compared with the existing feature set on the respect of basic classification performance and classification stability.The experiments were carried out on the traffic collected in the traditional and mobile networks.Results show that HCBF out performs existing feature sets.