Bayesian Network Structure Learning and Its Applications in Intrusion Detection
- https://doi.org/10.2991/csic-15.2015.25How to use a DOI?
- Rough set, Mutual information, Bayesian network, Structure learning, Intrusion detection
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.
- © 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 -