Network Security Situation Prediction Based on Adaptive Clustering RBF Network

DOI

10.2991/isrme-15.2015.164How to use a DOI?

Keywords

Network Security Situation Prediction(NSSP); Radical Basis Function (RBF) Neural Network; Adaptive Clustering

Abstract

Proposed is an algorithm for network security situation prediction (NSSP) based on adaptive clustering radical basis function (RBF) neural network. Experiment results show that, the proposed method not only reflects the general trend of network security situation, but also improves the prediction accuracy.

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  - Fangwei Li
AU  - Bo Zheng
AU  - Jiang Zhu
AU  - Zhuxun Peng
PY  - 2015/04
DA  - 2015/04
TI  - Network Security Situation Prediction Based on Adaptive Clustering RBF Network
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 806
EP  - 810
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.164
DO  - 10.2991/isrme-15.2015.164
ID  - Li2015/04
ER  -