...
首页> 外文期刊>Journal of Computers >Modified Mutual Information-based Feature Selection for Intrusion Detection Systems in Decision Tree Learning
【24h】

Modified Mutual Information-based Feature Selection for Intrusion Detection Systems in Decision Tree Learning

机译:决策树学习中的入侵检测系统进行修改的基于信息的特征选择

获取原文
           

摘要

—As network-based technologies become omnipresent, intrusion detection and prevention for these systems become increasingly important. This paper proposed a modified mutual information-based feature selection algorithm (MMIFS) for intrusion detection on the KDD Cup 99 dataset. The C4.5 classification method was used with this feature selection method. In comparison with dynamic mutual information feature selection algorithm (DMIFS), we can see that most performance aspects are improved. Furthermore, this paper shows the relationship between performance, efficiency and the number of features selected
机译:- 基于网络的技术成为全新的,入侵检测和预防这些系统变得越来越重要。本文提出了一种修改的基于互信息的特征选择算法(MMIF),用于KDD杯99数据集上的入侵检测。 C4.5分类方法用于该特征选择方法。与动态互信息特征选择算法(DMIF)相比,我们可以看到大多数性能方面得到改善。此外,本文显示了性能,效率和所选功能数之间的关系

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号