计算机与数字工程2023，Vol.51Issue(10)：2384-2389,6.DOI:10.3969/j.issn.1672-9722.2023.10.032
AdaBoost改进的规划识别方法在入侵检测中的研究
Research on AdaBoost Improved Planning Identification Method in Intrusion Detection
陈磊 1胡广朋1
作者信息
- 1. 江苏科技大学计算机学院 镇江 212000
- 折叠
摘要
Abstract
The idea of ensemble learning is introduced into planning recognition,and an improved planning recognition meth-od based on AdaBoost is proposed and applied to intrusion detection.This method combines the serial integration algorithm Ada-Boost with the traditional planning recognition algorithm,regards each planning recognition prediction model as a weak classifier,and combines each weak predictor with AdaBoost algorithm to form a strong predictor.Finally,the recognition result of the strong predictor is output.Nsl-kdd data set is used for experimental verification.The experimental results show that the proposed method has better recognition effect than the traditional method.关键词
入侵检测/规划识别/集成学习/AdaBoostKey words
intrusion detection/planning identification/integrated learning/AdaBoost分类
数理科学引用本文复制引用
陈磊,胡广朋..AdaBoost改进的规划识别方法在入侵检测中的研究[J].计算机与数字工程,2023,51(10):2384-2389,6.
