Intrusion detection in internet of things using supervised machine learning based on application and transport layer features using UNSW-NB15 data-set. - Muhammad Ahmad 001; Qaiser Riaz; Muhammad Zeeshan Ul Hasnain Hashmi; Hasan Tahir; Syed Ali Haider; Muhammad Safeer Khan (EURASIP J. Wirel. Commun. Netw., 2021)

Protocol-Based Deep Intrusion Detection for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets. - Muhammad Zeeshan 001; Qaiser Riaz; Muhammad Ahmad Bilal 001; Muhammad Khuram Shahzad; Hajira Jabeen; Syed Ali Haider; Azizur Rahim (IEEE Access, 2022)

Federated Learning With Explainable AI for Malicious Traffic Detection in IoT Networks. - Muhammad Ahmad Bilal 001; Ihtesham Ul Islam; Naima Iltaf; Muhammad Junaid Khan; Muhammad Jaleed Khan (IEEE Access, 2025)

Transformer and Graph Neural Network-Based Federated Learning for Cellular Traffic Prediction With Sustainability Analysis. - Muhammad Qasim; Muhammad Imran 003; Faisal Akram; Muhammad Ahmad Bilal 001; Muhammad Jaleed Khan (IEEE Access, 2025)

Secure and Explainable Federated Learning for IoT Intrusion Detection: A Comprehensive Survey. - Muhammad Ahmad Bilal 001; Ihtesham Ul Islam; Muhammad Junaid Khan; Shibli Nisar; Maemoona Farooq; Hassan Khan 001 (IEEE Open J. Commun. Soc., 2026)