Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (17): 110-112.DOI: 10.3778/j.issn.1002-8331.2010.17.031

• 网络、通信、安全 • Previous Articles     Next Articles

Feature selection based on multi-objective evolutionary algorithm for intrusion detection

JIANG Jia-fu,WU Peng   

  1. Institute of Computer and Communication Engineering,Changsha University of Science and Technology,Changsha 410076,China
  • Received:2008-12-03 Revised:2009-02-16 Online:2010-06-11 Published:2010-06-11
  • Contact: JIANG Jia-fu


蒋加伏,吴 鹏   

  1. 长沙理工大学 计算机与通信工程学院,长沙 410076
  • 通讯作者: 蒋加伏

Abstract: According to that an intrusion detection system needs to achieve the best trade-off between detection rate and false positive rate,an improved multi-objective evolutionary algorithm is proposed to reduce the feature space and then select the best feature subset.The experiment results show that the best trade-off between detection rate and false positive rate can be achieved by the improved multi-objective evolutionary algorithm.The algorithm can improve the performance of the intrusion detection system.

Key words: intrusion detection, feature selection, multi-objective evolutionary algorithm, sequential search

摘要: 针对入侵检测系统要求检测率和误报率均衡优化,提出一种由顺序搜索策略改进的多目标进化算法,对特征空间进行压缩,以选择最优特征子集。实验结果表明,改进的多目标进化算法实现了检测率与误报率的均衡优化,较好地提高了入侵检测系统的性能。

关键词: 入侵检测, 特征选择, 多目标进化算法, 顺序搜索

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