Network intrusion detection model of chaos immune genetic algorithm

Computer Engineering and Applications ›› 2014, Vol. 50 ›› Issue (21): 96-99.

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Network intrusion detection model of chaos immune genetic algorithm

JIA Huaping1, LI Yaolong1, SHI Xiaoying2

1.College of Mathematics and Information Science, Weinan Normal University, Weinan, Shaanxi 714099, China
2.College of Physics and Electrical Engineering, Weinan Normal University, Weinan, Shaanxi 714099, China

Online:2014-11-01 Published:2014-10-28

混沌免疫遗传算法的网络入侵检测模型

贾花萍1，李尧龙1，史晓影2

1.渭南师范学院数学与信息科学学院，陕西渭南 714099
2.渭南师范学院物理与电气工程学院，陕西渭南 714099

Abstract

Abstract: In order to effectively improve the detection rate of intrusion detection system and reduce the false alarm rate, the method of attribute reduction of high-dimensional data in intrusion detection feature selection is proposed. Attribute input irrelevant is weeded out to improve the detection effect. The chaos immune genetic algorithm is used in neural network learning process for intrusion detection. Compared with the traditional BP neural network detection results, the experimental results show that the method used in intrusion detection is feasible.

Key words: chaos, immune network, Genetic Algorithm（GA）, intrusion detection

摘要： 为了有效地提高入侵检测系统的检测率并降低误报率，提出采用属性约简方法对高维入侵检测数据进行特征选择，剔除无关的属性输入来提高检测效果，将混沌免疫遗传算法引入神经网络学习过程用以进行入侵检测，与传统BP神经网络检测结果进行比较，实验结果表明，将该方法用于入侵检测是切实可行的。

关键词: 混沌, 免疫网络, 遗传算法, 入侵检测

JIA Huaping1, LI Yaolong1, SHI Xiaoying2. Network intrusion detection model of chaos immune genetic algorithm[J]. Computer Engineering and Applications, 2014, 50(21): 96-99.

贾花萍1，李尧龙1，史晓影2. 混沌免疫遗传算法的网络入侵检测模型[J]. 计算机工程与应用, 2014, 50(21): 96-99.

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Network intrusion detection model of chaos immune genetic algorithm

混沌免疫遗传算法的网络入侵检测模型

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