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Semi-supervised and compound classification of network traffic

Zhang, Jun, Chen, Chao, Xiang, Yang and Zhou, Wanlei 2012, Semi-supervised and compound classification of network traffic, International journal of security and networks, vol. 7, no. 4, pp. 252-261, doi: 10.1504/IJSN.2012.053463.

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Title Semi-supervised and compound classification of network traffic
Author(s) Zhang, JunORCID iD for Zhang, Jun orcid.org/0000-0002-2189-7801
Chen, Chao
Xiang, YangORCID iD for Xiang, Yang orcid.org/0000-0001-5252-0831
Zhou, WanleiORCID iD for Zhou, Wanlei orcid.org/0000-0002-1680-2521
Journal name International journal of security and networks
Volume number 7
Issue number 4
Start page 252
End page 261
Total pages 11
Publisher Inderscience
Place of publication Geneva, Switzerland
Publication date 2012
ISSN 1747-8405
1747-8413
Keyword(s) Compound classifier
Network security
Semi-supervised
Traffic classification
Summary This paper presents a new semi-supervised method to effectively improve traffic classification performance when very few supervised training data are available. Existing semisupervised methods label a large proportion of testing flows as unknown flows due to limited supervised information, which severely affects the classification performance. To address this problem, we propose to incorporate flow correlation into both training and testing stages. At the training stage, we make use of flow correlation to extend the supervised data set by automatically labelling unlabelled flows according to their correlation to the pre-labelled flows. Consequently, a traffic classifier achieves excellent performance because of the enhanced training data set. At the testing stage, the correlated flows are identified and classified jointly by combining their individual predictions, so as to further boost the classification accuracy. The empirical study on the real-world network traffic shows that the proposed method significantly outperforms the state-of-the-art flow statistical feature based classification methods. Copyright © 2012 Inderscience Enterprises Ltd.
Language eng
DOI 10.1504/IJSN.2012.053463
Field of Research 080503 Networking and Communications
080109 Pattern Recognition and Data Mining
Socio Economic Objective 890199 Communication Networks and Services not elsewhere classified
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2012, Inderscience
Persistent URL http://hdl.handle.net/10536/DRO/DU:30070396

Document type: Journal Article
Collection: School of Information Technology
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