SDAID: Towards a Hybrid Signature and Deep Analysis-based Intrusion Detection Method. - Hoang V. Vo; Hoa Ngoc Nguyen; Tu N. Nguyen 001; Hanh Phuong Du (GLOBECOM, 2022)

Towards a Webshell Detection Approach Using Rule-Based and Deep HTTP Traffic Analysis. - Ha Viet Le; Hoang V. Vo; Tu N. Nguyen 001; Hoa Ngoc Nguyen; Hung T. Du (ICCCI, 2022)

Leveraging AI-Driven Realtime Intrusion Detection by Using WGAN and XGBoost. - Hoang V. Vo; Duong H. Nguyen; Tuyen T. Nguyen; Hoa Ngoc Nguyen; Duan V. Nguyen (SoICT, 2022)

Enhancing AI - Powered Malware Detection by Parallel Ensemble Learning. - Hoang V. Vo; Phong H. Nguyen; Hau T. Nguyen; Duy B. Vu; Hoa Ngoc Nguyen (RIVF, 2023)

AI-powered intrusion detection in large-scale traffic networks based on flow sensing strategy and parallel deep analysis. - Hoang V. Vo; Hanh Phuong Du; Hoa Ngoc Nguyen (J. Netw. Comput. Appl., 2023)

APELID: Enhancing real-time intrusion detection with augmented WGAN and parallel ensemble learning. - Hoang V. Vo; Hanh Phuong Du; Hoa Ngoc Nguyen (Comput. Secur., 2024)

MDOB: Enhancing resilient and explainable AI-powered malware detection using feature set optimization and Mutual Deep＋Boosting Ensemble Inference. - Hoang V. Vo; Hanh Phuong Du; Hoa N. Nguyen (J. Inf. Secur. Appl., 2025)