• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2011, Vol. 33 ›› Issue (10): 60-63.

• 论文 • 上一篇    下一篇

基于神经网络集成的入侵检测系统

徐〓敏,沈晓红,顾〓颀   

  1. (南通大学计算机科学与技术学院,江苏 南通 226019)
  • 收稿日期:2011-02-18 修回日期:2011-05-13 出版日期:2011-10-25 发布日期:2011-10-25

An Intrusion Detection System Based on Neural Network Ensembles

XU Min,SHEN Xiaohong,GU Qi   

  1. (School of Computer Science and Technology,Nantong University,Nantong 226019,China)
  • Received:2011-02-18 Revised:2011-05-13 Online:2011-10-25 Published:2011-10-25

摘要:

目前,较为成熟的入侵检测系统普遍存在检测率偏低、对新的入侵不够敏感等问题,影响了系统的整体性能。在深入研究的基础上,本文提出了一种基于神经网络集成的入侵检测方法。该方法采用神经网络集成分类技术,在去除冗余数据的基础上对成员网络进行训练,并通过动态的方法确定成员网络的个数,最终通过神经网络对成员网络结果进行融合,以提高系统的整体性能。理论和实验表明,该方法能在保证成员网络差异性的同时提高入侵的检测率,具有较好的应用前景。

关键词: 神经网络集成, 数据筛选, 入侵检测

Abstract:

With the problems of the low detection rate and the insufficient sensitivity to the new intrusion,the current intrusion detection systems affect the functions of the entre system. Based on the very deep research, this paper proposes a new neural network ensembles method for intrusion detection. The method is used to train the individual networks on the basis of data reduction. Neural network techniques are used to combine the different classification results. Theory and experiment show that the model is effective.

Key words: neural network ensembles;attribute selection;intrusion detection