An Adaptive Ensemble Machine Learning Model for Intrusion Detection. - Xianwei Gao; Chun Shan; Changzhen Hu; Zequn Niu; Zhen Liu (IEEE Access, 2019)

Detection of Malicious Domains in APT via Mining Massive DNS Logs. - Lu Huang 002; Jingfeng Xue; Weijie Han; Zixiao Kong; Zequn Niu (ML4CS (1), 2020)

Malware classification for the cloud via semi-supervised transfer learning. - Xianwei Gao; Changzhen Hu; Chun Shan; Baoxu Liu; Zequn Niu; Hui Xie (J. Inf. Secur. Appl., 2020)

A Survey on Adversarial Attack in the Age of Artificial Intelligence. - Zixiao Kong; Jingfeng Xue; Yong Wang 010; Lu Huang 002; Zequn Niu; Feng Li (Wirel. Commun. Mob. Comput., 2021)

A novel approach based on adaptive online analysis of encrypted traffic for identifying Malware in IIoT. - Zequn Niu; Jingfeng Xue; Dacheng Qu; Yong Wang 010; Jun Zheng 007; Hongfei Zhu (Inf. Sci., 2022)

A novel anomaly detection approach based on ensemble semi-supervised active learning (ADESSA). - Zequn Niu; Wenjie Guo; Jingfeng Xue; Yong Wang 010; Zixiao Kong; Lu Huang 002 (Comput. Secur., 2023)

An empirical study of problems and evaluation of IoT malware classification label sources. - Tianwei Lei; Jingfeng Xue; Yong Wang 010; Thar Baker; Zequn Niu (J. King Saud Univ. Comput. Inf. Sci., 2024)