吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

基于ReliefF的入侵特征选择方法

杨志伟1, 努尔布力1, 贾雪1, 胡亮2   

  1. 1. 新疆大学 信息科学与工程学院, 乌鲁木齐 830046; 2. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2014-08-04 出版日期:2015-05-26 发布日期:2015-05-21
  • 通讯作者: 努尔布力 E-mail:nurbol_mail@163.com

Intrusion Feature Selection Methods Based on ReliefF

YANG Zhiwei1, Nurbol1, JIA Xue1, HU Liang2   

  1. 1. College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China;2. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2014-08-04 Online:2015-05-26 Published:2015-05-21
  • Contact: Nurbol E-mail:nurbol_mail@163.com

摘要:

基于ReliefF的入侵特征选择方法, 结合入侵检测数据集类内紧密和类外差距大的特点, 通过对入侵特征权重计算的优化, 提出一种改进算法: Re-ReliefF算法, 解决了网络安全领域数据维度导致处理效率较低的问题. 实验结果表明, 在安全测试数据集下, 改进算法相对传统算法在性能上有一定提高.

关键词: 入侵检测, 特征选择, ReliefF算法

Abstract:

The authors analyzed the intrusion feature selection methods and algorithms based on ReliefF. Combining with the characteristics, in which data points have high similarity in the same class and nonsimilarity in different classes, and optimizing the compute method of intrusion feature weight, we proposed an improved algorithm ReReliefF. It resolved the problems about processing efficiency with the data dimensions in network security. Experiments on the network security test datasets showed the effectiveness of the proposed algorithms, and the improved algorithm has advantages on performance compared to the traditional one.

Key words:  intrusion detection, feature selection, ReliefF algorithm

中图分类号: 

  • TP309