| 基于BP神经网络的入侵检测系统的特征选择 |
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| 引用本文： | 李凯,田双亮,耿丽君.基于BP神经网络的入侵检测系统的特征选择[J].长春大学学报,2009,19(6):37-40. |
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| 作者姓名： | 李凯 田双亮 耿丽君 |
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| 作者单位： | 西北民族大学计算机与信息工程学院;山西财经大学会计学院; |
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| 摘 要： | 随着各种入侵和攻击网络工具的出现,入侵检测成为网络管理的关键组成部分。特征选择能够有效地提高机器学习与规则提取算法性能。本文设计了一种基于遗传神经网络的入侵检测系统,采用基于多种改进的遗传算法特征选择方法,实验结果表明不同改进的遗传算法特征选择对BP神经网络的分类正确率有一定的影响。
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| 关 键 词： | 入侵检测 改进的遗传算法 特征选择 BP神经网络 |
Feature selection of intrusion detection system based on BP neural network |
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| LI Kai,TIAN Shuang-liang,GENG Li-jun.Feature selection of intrusion detection system based on BP neural network[J].Journal of Changchun University,2009,19(6):37-40. |
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| Authors: | LI Kai TIAN Shuang-liang GENG Li-jun |
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| Institution: | 1.Institute of Computer and Information Engineering;Northwest University for Nationalities;Lanzhou 730030;China;2.School of Accounting;Shanxi University of Finance and Economics;Taiyuan 030006;China |
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| Abstract: | With the advent of a variety of the invasions and attack network tools,intrusion detection has become a key component of network management.Feature selection can effectively improve machine learning and rule extraction algorithm performance.This article designs a intrusion detection system based on genetic neural network,which adopts selection method based on a variety of improved genetic algorithm features.The experimental results show that the genetic algorithm selection with different characteristics has... |
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| Keywords: | intrusion detection improved genetic algorithm feature selection BP neural network |
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