The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMMUNICATIONS
Transactions ID Number: 28-340
Full Name: Haitao He
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: Information and Network Center, Sun Yat-sen University, Xingang Xi Road 135
Country: CHINA
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E-mail address: hthe@mail.sysu.edu.cn
Other E-mails: billowhe@gmail.com
Title of the Paper: traffic classification using en-semble learning and co-training
Authors as they appear in the Paper: Haitao He, Chuhui Che, Feiteng Ma, Jun Zhang, Xiaonan Luo
Email addresses of all the authors:
Number of paper pages: 10
Abstract: Classification of network traffic is the essential step for many network researches. However, with the rapid evolution of Internet applications the effectiveness of the port-based or payload-based identification approaches has been greatly diminished in recent years. And many researchers begin to turn their attentions to an alternative machine learning based method. This paper presents a novel machine learning-based classification model, which combines ensemble learning paradigm with co-training techniques. Compared to previous approaches, most of which only employed single classifier, multiple classifiers and semi-supervised learning are applied in our method and it mainly helps to overcome three shortcomings: limited flow accuracy rate, weak adaptability and huge demand of labelled training set. In this paper, statistical characteristics of IP flows are extracted from the packet level traces to establish the feature set, then the classification model is created a!
nd tested and the empirical results prove its feasibility and effectiveness.
Keywords: traffic classification, ensemble learning, co-training, network measurement
EXTENSION of the file: .pdf
Special (Invited) Session: traffic classification using en-semble learning and co-training
Organizer of the Session: 594-575
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