Proceedings of the 2016 International Conference on Education, Management and Computer Science

The Stability of the Internet Traffic Features

Authors
Bin Zhang, Yuandong Mao, Mei Zhang, Yun Yu, Guoquan Jiang, Bo Deng
Corresponding Author
Bin Zhang
Available Online May 2016.
DOI
https://doi.org/10.2991/icemc-16.2016.16How to use a DOI?
Keywords
Taffic feature; Entropy; Stability; Anomaly detection
Abstract
In this paper, we present a statistical analysis of traffic features at the packet level. We show that all traffic features demonstrate similar approximately power-law distribution for different time and interval at minute time scale except for the packet size. We observe that feature entropy and independent feature symbols number for fixed packets number are relatively stable in a short time interval, which is very useful for traffic anomaly detection.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Conference on Education, Management and Computer Science
Part of series
Advances in Intelligent Systems Research
Publication Date
May 2016
ISBN
978-94-6252-202-2
ISSN
1951-6851
DOI
https://doi.org/10.2991/icemc-16.2016.16How 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  - Bin Zhang
AU  - Yuandong Mao
AU  - Mei Zhang
AU  - Yun Yu
AU  - Guoquan Jiang
AU  - Bo Deng
PY  - 2016/05
DA  - 2016/05
TI  - The Stability of the Internet Traffic Features
BT  - 2016 International Conference on Education, Management and Computer Science
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/icemc-16.2016.16
DO  - https://doi.org/10.2991/icemc-16.2016.16
ID  - Zhang2016/05
ER  -