The Hierarchical Ensemble Model for Network Intrusion Detection in the Real-world Dataset

Chen, LeiLeiChenWeng, Shao EnShao EnWengPeng, Chu JunChu JunPengLi, Yin ChiYin ChiLiShuai, Hong HanHong HanShuaiWEN-HUANG CHENG2023-02-172023-02-172022-01-01978166548485502714310https://scholars.lib.ntu.edu.tw/handle/123456789/628368Network intrusion detection is an indispensable defense in the critical era fulling of cyberattacks. However, it faces a severe class imbalanced issue, and most of the researches are conducted on simulated data. Therefore, this work introduces a hierarchical ensemble architecture with machine learning approaches. It is trained on the latest and real-world dataset to solve the above problems. The experiments show that we outperform state-of-the-art methods on real network traffic data.The Hierarchical Ensemble Model for Network Intrusion Detection in the Real-world Datasetconference paper10.1109/ISCAS48785.2022.99373222-s2.0-85142489486https://api.elsevier.com/content/abstract/scopus_id/85142489486