ML-LGBM: A Machine Learning Model Based on Light Gradient Boosting Machine for the Detection of Version Number Attacks in RPL-Based Networks. - Musa Osman; Jingsha He; Fawaz Mahiuob Mohammed Mokbal; Nafei Zhu; Sirajuddin Qureshi (IEEE Access, 2021)

An efficient intrusion detection framework based on embedding feature selection and ensemble learning technique. - Fawaz Mahiuob Mohammed Mokbal; Dan Wang 019; Musa Osman; Ping Yang; Saeed H. Alsamhi (Int. Arab J. Inf. Technol., 2022)

An effective deep learning scheme for android malware detection leveraging performance metrics and computational resources. - Ahsan Wajahat; Jingsha He; Nafei Zhu; Tariq Mahmood 001; Ahsan Nazir; Faheem Ullah; Sirajuddin Qureshi; Musa Osman (Intell. Decis. Technol., 2024)

An ensemble learning framework for the detection of RPL attacks in IoT networks based on the genetic feature selection approach. - Musa Osman; Jingsha He; Nafei Zhu; Fawaz Mahiuob Mohammed Mokbal (Ad Hoc Networks, 2024)

HADTF: a hybrid autoencoder-decision tree framework for improved RPL-based attack detection in IoT networks based on enhanced feature selection approach. - Musa Osman; Jingsha He; Nafei Zhu; Fawaz Mahiuob Mohammed Mokbal; Asaad Ahmed (J. Supercomput., 2024)