Chen, Lei; Weng, Shao-En; Peng, Chu-Jun; Li, Yin-Chi; Shuai, Hong-Han; Cheng, Wen-Huang
2022 IEEE International Symposium on Circuits and Systems (ISCAS),
2022-May-28
Conference Proceeding
Network 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.
