南京理工大学学报（自然科学版）2017，Vol.41Issue(1)：59-64,6.DOI:10.14177/j.cnki.32-1397n.2017.41.01.008
特征和分类器参数组合优化的网络入侵检测
Network intrusion detection by using combination optimizingfeatures and classifier parameters
摘要
Abstract
In order to obtain better intrusion detection results,this paper designs a network intrusion detection algorithm by using combination optimizing features and classifier parameters.A mathematical model of combinatorial optimization is set up based on the features and parameters of classifier influence on intrusion detection results respectively.A biogeography-based optimization algorithm is adopted to simulate migration process of species inhabitancy to find the optimal solution of mathematical model and obtain the optimal features and classifier parameters.Standard intrusion detection-KDD Cup 99 data sets are used to test feasibility and superiority.The results show that the proposed algorithm can make mine relation between features and classifier parameters to improve intrusion detection rate and that the execution speed can meet the real-time requirements of intrusion detection.关键词
网络入侵/特征选择/分类器设计/生物地理学优化算法Key words
network intrusion/feature selection/classifier design/biogeography-based optimization algorithm分类
信息技术与安全科学引用本文复制引用
王战红..特征和分类器参数组合优化的网络入侵检测[J].南京理工大学学报（自然科学版）,2017,41(1):59-64,6.基金项目
河南省高等学校重点科研项目(15A120014) （15A120014）
公安部重点研究计划项目(201202ZDYJ017) （201202ZDYJ017）
