计算机应用与软件2024，Vol.41Issue(7)：288-295,8.DOI:10.3969/j.issn.1000-386x.2024.07.041
基于ICA算法和三支决策的入侵检测方法
INTRUSION DETECTION METHOD BASED ON ICA ALGORITHM AND THREE-WAY DECISIONS
摘要
Abstract
With the diversification and intelligence of network intrusion behaviors,network data has the characteristics of high feature dimensionality and non-linear separability,which leads to insufficient feature extraction and low model classification accuracy in network data.Therefore,an intrusion detection model based on independent component analysis(ICA)and three-way decisions(TWD)is proposed.The characteristics of network connection data were reduced by using ICA algorithm based on maximal non-Gauss property.The data was mapped from high dimensional feature space to low dimensional space to eliminate redundant data.And a multi-granular feature space was constructed through multiple feature extraction.Decisions were made on network behaviors based on three decision-making theories.Experiments were performed on NSL-KDD and CIC-IDS2017 data set.The results show that the proposed model has better feature extraction capability and more accurate classification ability.关键词
ICA/三支决策/特征提取/入侵检测Key words
ICA/Three-way decisions/Feature extraction/Intrusion detection分类
信息技术与安全科学引用本文复制引用
王帅,黄树成..基于ICA算法和三支决策的入侵检测方法[J].计算机应用与软件,2024,41(7):288-295,8.基金项目
国家自然科学基金项目(61772244). （61772244）
