计算机应用与软件2024，Vol.41Issue(11)：379-385,7.DOI:10.3969/j.issn.1000-386x.2024.11.052
软件定义网络中基于改进随机森林算法的入侵检测研究
INTRUSION DETECTION BASED ON IMPROVED RANDOM FOREST ALGORITHM IN SOFTWARE DEFINED NETWORK
马群 1胡佳卉 2于雅静1
作者信息
- 1. 中国移动通信集团设计院有限公司河北分公司 河北 石家庄 050000
- 2. 中国联通智网创新中心 北京 100000
- 折叠
摘要
Abstract
In view of the large differences in the characteristics of intrusion data streams in software-defined networks and the applicability of the random forest algorithm in intrusion detection,this paper proposes an intrusion detection model based on an improved random forest algorithm.We analyzed the differences in the characteristics of intrusion data based on the Fisher ratio,and conducted feature partitioning according to their corresponding values.A weighted voting method was introduced to increase the weight of the decision tree with better classification performance.The node was split based on the maximum information gain rate.The grid search algorithm was improved to further improve the effect of random forest parameter optimization.Through experimental analysis,the accuracy,F1 value,AUC value and other evaluation indicators of this model is significantly improved,which verifies the effectiveness of the improved algorithm.关键词
软件定义网络/随机森林算法/入侵检测/Fisher准则/网格搜索算法Key words
Software-defined network(SDN)/Random forest algorithm/Intrusion detection/Fisher criterion/Grid search algorithm分类
信息技术与安全科学引用本文复制引用
马群,胡佳卉,于雅静..软件定义网络中基于改进随机森林算法的入侵检测研究[J].计算机应用与软件,2024,41(11):379-385,7.
