Proceedings of the 2015 International Conference on Computer Science and Intelligent Communication

Bayesian Network Structure Learning and Its Applications in Intrusion Detection

Authors
Zuhong Feng, Chen Ye, Xiu-juan Gao
Corresponding Author
Zuhong Feng
Available Online July 2015.
DOI
https://doi.org/10.2991/csic-15.2015.25How to use a DOI?
Keywords
Rough set, Mutual information, Bayesian network, Structure learning, Intrusion detection
Abstract

In this paper, an algorithm with attribute reduction based on rough set is introduced. The algorithm can effectively reduce the dimension of attributes and accurately determine the network structure using DBNI with the method of distribution in Bayesian network structure learning with incomplete data. The simulation result shows the algorithm can effectively improve the learning efficiency and detection accuracy of the network.

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 2015 International Conference on Computer Science and Intelligent Communication
Series
Advances in Computer Science Research
Publication Date
July 2015
ISBN
978-94-62520-84-4
ISSN
2352-538X
DOI
https://doi.org/10.2991/csic-15.2015.25How 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  - Zuhong Feng
AU  - Chen Ye
AU  - Xiu-juan Gao
PY  - 2015/07
DA  - 2015/07
TI  - Bayesian Network Structure Learning and Its Applications in Intrusion Detection
BT  - Proceedings of the 2015 International Conference on Computer Science and Intelligent Communication
PB  - Atlantis Press
SP  - 107
EP  - 112
SN  - 2352-538X
UR  - https://doi.org/10.2991/csic-15.2015.25
DO  - https://doi.org/10.2991/csic-15.2015.25
ID  - Feng2015/07
ER  -