원문정보
보안공학연구지원센터(IJSIA)
International Journal of Security and Its Applications
Vol.9 No.4
2015.04
pp.307-316
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Traditional network intrusion detection algorithms are time consuming due to the existence of redundant attributes. In order to improve the efficiency of network intrusion detection, in this paper, we propose a wavelet transform based support vector machine ensemble algorithm. Firstly, we use wavelet transform to remove the redundant attributes from the original dataset. Then we train a support vector machine ensemble on the simplified dataset. As the wavelet transform in this algorithm can effectively remove the redundant attributes, the proposed algorithm is with high efficiency. Simulation experiments on KDD CUP 99 data set show that the proposed algorithm has good intrusion detection performance.
목차
Abstract
1. Introduction
2. Related Theories
2.1. Wavelet Transform
2.2. Support Vector Machines
2.3. Ensemble
3. The Wavelet Transform based Support Vector Machine Ensemble Algorithm
4. Experiments
4.1. Experimental Data
4.2. Data Preprocessing
4.3. Evaluation Indexes
4.4. Experimental Method and Result
4.5. Experimental Result Analysis
5. Conclusion
Acknowledgements
References
1. Introduction
2. Related Theories
2.1. Wavelet Transform
2.2. Support Vector Machines
2.3. Ensemble
3. The Wavelet Transform based Support Vector Machine Ensemble Algorithm
4. Experiments
4.1. Experimental Data
4.2. Data Preprocessing
4.3. Evaluation Indexes
4.4. Experimental Method and Result
4.5. Experimental Result Analysis
5. Conclusion
Acknowledgements
References
저자정보
참고문헌
자료제공 : 네이버학술정보