Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)

A Feature Analysis Approach to Network Traffic in Communication Networks

Authors
Honghao Zhao, Hongyu Dong, Xiaohui Zhang, Qing Ye, Fanbo Meng, Xinyu Sun, Ying Cao
Corresponding Author
Honghao Zhao
Available Online October 2016.
DOI
https://doi.org/10.2991/ceie-16.2017.83How to use a DOI?
Keywords
Network Traffic; Feature Analysis; Time-Frequency Analysis; Feature Extraction
Abstract
Network traffic holds the highlighting dynamic features. How to accurately characterize the hidden properties of network traffic has an important impact on network activities, such as anomaly detection and performance analysis. This paper proposes a feature analysis approach to describe network traffic. Firstly, the wavelet packet transformation is used to extract the multi-scale feature of network traffic. Then the principal component analysis method is exploited to refine the hidden features of network traffic in the time-frequency domain. Finally, to validate our feature analysis method, an anomaly detection test is conducted. Simulation results show that our approach is promising.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
978-94-6252-312-8
ISSN
2352-5401
DOI
https://doi.org/10.2991/ceie-16.2017.83How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Honghao Zhao
AU  - Hongyu Dong
AU  - Xiaohui Zhang
AU  - Qing Ye
AU  - Fanbo Meng
AU  - Xinyu Sun
AU  - Ying Cao
PY  - 2016/10
DA  - 2016/10
TI  - A Feature Analysis Approach to Network Traffic in Communication Networks
BT  - Proceedings of the International Conference on Communication and Electronic Information Engineering (CEIE 2016)
PB  - Atlantis Press
SP  - 648
EP  - 655
SN  - 2352-5401
UR  - https://doi.org/10.2991/ceie-16.2017.83
DO  - https://doi.org/10.2991/ceie-16.2017.83
ID  - Zhao2016/10
ER  -