Application of Swarm Intelligent Algorithm Optimization Neural Network in Network Security

DOI

10.2991/icmmita-16.2016.235How to use a DOI?

Keywords

traffic detection;swarm intelligence algorithm;neural network;network security

Abstract

A network traffic detection model based on swarm intelligent optimization neural network algorithm is proposed in this paper. QAPSO algorithm is used to optimize the basis function center and base function width of RBF neural network,and the connection weights of the output layer and the hidden layer as well. This paper analyzes the detection model studied in this paper by an example,and use the collected data to train the network traffic identification system and test its performance. The comparison between the proposed method and the conventional PSO algorithm based on the HPSO algorithm shows that the proposed method has faster recognition speed and better recognition accuracy, and avoids the problem of falling into the local optimal solution. Situation.

Copyright

© 2017, 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  - Hui Xia
PY  - 2017/01
DA  - 2017/01
TI  - Application of Swarm Intelligent Algorithm Optimization Neural Network in Network Security
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.235
DO  - 10.2991/icmmita-16.2016.235
ID  - Xia2017/01
ER  -