Bayesian Network Structure Learning and Its Applications in Intrusion Detection

DOI

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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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  - 10.2991/csic-15.2015.25
ID  - Feng2015/07
ER  -