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基于熵的入侵检测特征参数选择 被引量：8

Selection intrusion detection parameters using entropy
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摘要 传统入侵检测的特征选择方法不但与评估数据的统计特性有关,还与检测算法有关。提出了一种独立于检测算法的入侵检测特征参数选择方法。该方法以入侵检测模型为基础,信息熵为准则。仿真结果显示出用所选特征参数进行检测,不但保证了检测的正确率,而且提高了检测速度,减小了内存资源的占用。 Feature selection methods for intrusion detection now available are influenced by the statistical characteristics of evaluation data and the detection methods. A feature selection method independent of detection method is presented. The method is based on the intrusion detection model and the entropy is used as the criterion. The simulation results show that it is effective to increase the detection speed and reduce of the memory, without sacrificing the detection correctness by using the selected features based on entropy.
作者 饶鲜 杨绍全 魏青 董春曦
机构地区 西安电子科技大学电子对抗研究所
出处 《系统工程与电子技术》 EI CSCD 北大核心 2006年第4期599-601,610,共4页 Systems Engineering and Electronics
基金 "十五"军事通讯预研资助课题(4100104030)
关键词 网络安全 入侵检测 熵 特征选择 network security intrusion detection entropy feature selection
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献7

  • 1Denning D E.An intrusion detection model[J].IEEE Trans.On Software Engineering,1987,13(2):222-232.
  • 2Forres S,Perelson A S,Allen L,et al.Self-nonself discrimination in a computer[J].In Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy,Los Alamitos,CA:IEEE Computer Society Press 1994:120-128.
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  • 7饶鲜,董春曦,杨绍全.基于支持向量机的入侵检测系统[J].软件学报,2003,14(4):798-803. 被引量：134

二级参考文献6

  • 1[1]Forrest S, Perrelason AS, Allen L, Cherukur R. Self_Nonself discrimination in a computer. In: Rushby J, Meadows C, eds. Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy. Oakland, CA: IEEE Computer Society Press, 1994. 202～212.
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  • 6[6]Warrender C, Forresr S, Pearlmutter B. Detecting intrusions using system calls: Alternative data models. In: Gong L, Reiter MK, eds. Proceedings of the 1999 IEEE Symposium on Security and Privacy. Oakland, CA: IEEE Computer Society Press, 1999. 133～145.

共引文献133

同被引文献55

引证文献8

二级引证文献21

系统工程与电子技术
2006年 第4期

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