Preventing Adversarial Attacks Against Deep Learning-Based Intrusion Detection System. - Xuan-Ha Nguyen; Xuan-Duong Nguyen; Kim-Hung Le (ISPEC, 2022)

Enhancing Explainability of Machine Learning-based Intrusion Detection Systems. - Thi-Ngoc-Phuc Ho; Thuy-Linh Nguyen; Xuan-Ha Nguyen; Kim-Hung Le (RIVF, 2022)

Realguard: A Lightweight Network Intrusion Detection System for IoT Gateways. - Xuan-Ha Nguyen; Xuan-Duong Nguyen; Hoang-Hai Huynh; Kim-Hung Le (Sensors, 2022)

The Impact of Rotational Invariance on Tree- and Deep Learning-Based Network Intrusion Detection System. - Dat-Thinh Nguyen; Xuan-Ha Nguyen; Kim-Hung Le (RIVF, 2023)

Benchmarking SVM Variants for Unsupervised Intrusion Detection System. - Xuan-Ha Nguyen; Dat-Thinh Nguyen; Kim-Hung Le (RIVF, 2023)

Robust detection of unknown DoS/DDoS attacks in IoT networks using a hybrid learning model. - Xuan-Ha Nguyen; Kim-Hung Le (Internet Things, 2023)

BERT-Enhanced DGA Botnet Detection: A Comparative Analysis of Machine Learning and Deep Learning Models. - Qui Cao; Phuc Dao-Hoang; Dat-Thinh Nguyen; Xuan-Ha Nguyen; Kim-Hung Le (ICCAIS, 2024)

An Automated Benchmarking Framework for Anomaly-based Intrusion Detection Systems. - Hoang-Cong-Thanh Nguyen; Xuan-Ha Nguyen; Kim-Hung Le (MAPR, 2024)

nNFST: A single-model approach for multiclass novelty detection in network intrusion detection systems. - Xuan-Ha Nguyen; Kim-Hung Le (J. Netw. Comput. Appl., 2025)

Bigsids: an efficient SDN-based network intrusion detection systems for big data environments. - Hoang-Hai Huynh; Xuan-Ha Nguyen; Xuan-Duong Nguyen; Kim-Hung Le (Clust. Comput., 2025)