PPCSA: Partial Participation-Based Compressed and Secure Aggregation in Federated Learning. - Ahmed Moustafa; Muhammad Asad 002; Saima Shaukat; Alexander Norta (AINA (2), 2021)

Resource and Heterogeneity-aware Clients Eligibility Protocol in Federated Learning. - Muhammad Asad 002; Safa Otoum; Saima Shaukat (GLOBECOM, 2022)

SHFL: K-Anonymity-Based Secure Hierarchical Federated Learning Framework for Smart Healthcare Systems. - Muhammad Asad 002; Muhammad Aslam 004; Syeda Fizzah Jilani; Saima Shaukat; Manabu Tsukada (Future Internet, 2022)

Multi-hop similarity-based-clustering framework for IoT-Oriented Software-Defined wireless sensor networks. - Ayesha Shafique; Muhammad Asad 002; Muhammad Aslam 004; Saima Shaukat; Guo Cao (IET Wirel. Sens. Syst., 2022)

Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey. - Muhammad Asad 002; Saima Shaukat; Dou Hu; Zekun Wang; Ehsan Javanmardi; Jin Nakazato; Manabu Tsukada (Sensors, 2023)

Secure and Efficient Blockchain-Based Federated Learning Approach for VANETs. - Muhammad Asad 002; Saima Shaukat; Ehsan Javanmardi; Jin Nakazato; Naren Bao; Manabu Tsukada (IEEE Internet Things J., 2024)

Clients Eligibility-Based Lightweight Protocol in Federated Learning: An IDS Use Case. - Muhammad Asad 002; Safa Otoum; Saima Shaukat (IEEE Trans. Netw. Serv. Manag., 2024)

Federated learning for secure and efficient vehicular communications in open RAN. - Muhammad Asad 002; Saima Shaukat; Jin Nakazato; Ehsan Javanmardi; Manabu Tsukada (Clust. Comput., 2025)