Earticle

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

키워드

저자

• Xuesen Cai [ College of Computer Science and Technology, Changchun Normal University, Changchun, China,130032 ] Corresponding author
• Fanhua Yu [ College of Computer Science and Technology, Changchun Normal University, Changchun, China,130032 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605