Cubic Polynomial Smooth Support Vector Machine Used in Intrusion Detection

DOI

10.2991/icmemtc-16.2016.244How to use a DOI?

Keywords

Intrusion Detection; Polynomial support vector machine; accuracy; Data mining

Abstract

In the research of intrusion detection, we mainly focus on how to improve the accuracy of detection. Based on the introduction of support vector machine, this paper proposes a cubic polynomial smooth support vector machine model and uses it into intrusion detection. Subsequently we analyze each part of the model. Finally we conducted experiments to show that the proposed algorithm has higher accuracy than similar algorithms in Intrusion Detection.

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  - Zhixin Cai
PY  - 2016/04
DA  - 2016/04
TI  - Cubic Polynomial Smooth Support Vector Machine Used in Intrusion Detection
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 1236
EP  - 1239
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.244
DO  - 10.2991/icmemtc-16.2016.244
ID  - Cai2016/04
ER  -