Network Traffic Classification Based on Message Statistics

Accurate and efficient network traffic classification is an important network management task. Two way messages in a session follow the underlying application protocol to exchange information. In this paper, we propose a novel application classification method based on message statistics, concisely...

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Bibliographic Details
Published in2008 4th International Conference on Wireless Communications, Networking and Mobile Computing pp. 1 - 4
Main Authors Gang Shen, Lian Fan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2008
Subjects
Application software
Classification tree analysis
Decision trees
Engineering management
Machine learning algorithms
Payloads
Protocols
Software engineering
Statistics
Telecommunication traffic
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ISBN9781424421077
1424421071
ISSN2161-9646
DOI10.1109/WiCom.2008.1046

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Summary:Accurate and efficient network traffic classification is an important network management task. Two way messages in a session follow the underlying application protocol to exchange information. In this paper, we propose a novel application classification method based on message statistics, concisely representing the protocols' unique characteristics. We present algorithms using SVD-based and information gain based algorithms to select the proper message feature set. As shown by the evaluation experiments, using the selected message features, a simple decision tree is able to reach the classification accuracy over 99%, which is comparable to other more sophisticated machine learning results.
ISBN:9781424421077
1424421071
ISSN:2161-9646
DOI:10.1109/WiCom.2008.1046