Incremental Wavelet Neural Network based Prediction of Network Security Situation

DOI

10.2991/icmmct-16.2016.236How to use a DOI?

Keywords

Network Security Situation; WNN; Incremental Learning; Generalization Performance

Abstract

Network security situation prediction can help network administrators to make security decisions, and the current network security technology cannot predict the future network security situation. Hereby, a network security situation prediction based on incremental wavelet neural network (IWNN) was proposed, which establishes the nonlinear mapping according to the time relationship of network security situation value. Meanwhile, in this method, the complexity of the future network security situation is considered by incremental learning. Therefore, IWNN has better generalization performance in network security situation prediction when considering the changes in the pattern of the future network attack, the network scale and the network security technology, etc. Finally, the performance of the proposed method is verified by the experimental data processing results.

Copyright

© 2016, 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  - Xiaojian Liu
PY  - 2016/03
DA  - 2016/03
TI  - Incremental Wavelet Neural Network based Prediction of Network Security Situation
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 1198
EP  - 1202
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.236
DO  - 10.2991/icmmct-16.2016.236
ID  - Liu2016/03
ER  -