Proceedings of the 2014 International Conference on Computer Science and Electronic Technology

Research and Simulation of Network Intrusion Detection Algorithm Based on Fuzzy Classification

Authors
Chun Liu
Corresponding Author
Chun Liu
Available Online January 2015.
DOI
10.2991/iccset-14.2015.3How to use a DOI?
Keywords
fuzzy classification; abnormal data; intrusion detection
Abstract

The network intrusion accurate detection problem is researched. In the network intrusion detection process, the classification features of network operation data has poor uniformity, and the error of features classification is large, a network intrusion detection method based on fuzzy classification algorithm is proposed, principal component analysis method is used, the dimensions of network operation data are reduced. The redundant data are reduced, and fuzzy classification method is used, network intrusion featuresare classified, the network intrusion detection is realized. The simulation results show that the algorithm can effectively improve the accuracy of detection, it has perfect results.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2014 International Conference on Computer Science and Electronic Technology
Series
Advances in Computer Science Research
Publication Date
January 2015
ISBN
10.2991/iccset-14.2015.3
ISSN
2352-538X
DOI
10.2991/iccset-14.2015.3How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Chun Liu
PY  - 2015/01
DA  - 2015/01
TI  - Research and Simulation of Network Intrusion Detection Algorithm Based on Fuzzy Classification
BT  - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 14
EP  - 17
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccset-14.2015.3
DO  - 10.2991/iccset-14.2015.3
ID  - Liu2015/01
ER  -