Publications
Journal Publications [Total IF: 106.4]
[J24] Asad, Muhammad, Safa Otoum, and Saima Shaukat "Clients Eligibility-Based Lightweight Protocol in Federated Learning: An IDS Use-Case," in IEEE Transactions on Network and Service Management, doi: 10.1109/TNSM.2024.3398213. [IF: 5.1] (Q1)
[J23] Asad, Muhammad, and Safa Otoum, "Federated learning for efficient spectrum allocation in open RAN". Cluster Computing (2024). https://doi.org/10.1007/s10586-024-04500-9 [IF: 4.4] (Q1)
[J22] Muhammad Asad and Safa Otoum, "Integrative Federated Learning and Zero-Trust Approach for Secure Wireless Communications," in IEEE Wireless Communications, vol. 31, no. 2, pp. 14-20, April 2024, doi: 10.1109/MWC.001.2300355 [IF: 12.9] (Q1)
[J21] Muhammad Hamza Rafique Bhatti, Nadeem Javaid, Nabil Alrajeh, Muhammad Aslam, Muhammad Asad, "New hybrid deep learning models to predict cost from healthcare providers in smart hospitals," in IEEE Access. (IF= 3.9) [Q1]
[J20] Asad, Muhammad, Saima Shaukat, Ehsan Javanmardi, Jin Nakazato, Naren Bao, and Manabu Tsukada, "Secure and Efficient Blockchain-Based Federated Learning Approach for VANETs," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2023.3322221. (IF= 10.6) [Q1]
[19] Asad, Muhammad, Saima Shaukat, Dou Hu, Zekun Wang, Ehsan Javanmardi, Jin Nakazato, and Manabu Tsukada. 2023. "Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey" Sensors 23, no. 17: 7358. https://doi.org/10.3390/s23177358 (IF= 3.9) [Q2]
[18] Asad, Muhammad, Saima Shaukat, Ehsan Javanmardi, Jin Nakazato, and Manabu Tsukada. 2023. "A Comprehensive Survey on Privacy-Preserving Techniques in Federated Recommendation Systems" Applied Sciences 13, no. 10: 6201. https://doi.org/10.3390/app13106201 (IF = 2.7) [Q2]
[17] Shaukat, Saima, Asad, Muhammad, and Asmara Akram. 2023. "Developing an Urdu Lemmatizer Using a Dictionary-Based Lookup Approach" Applied Sciences 13, no. 8: 5103. https://doi.org/10.3390/app13085103 (IF = 2.7) [Q2]
[16] Asad, Muhammad, Muhammad Aslam, Syeda Fizzah Jilani, Saima Shaukat, and Manabu Tsukada. 2022. "SHFL: K-Anonymity-Based Secure Hierarchical Federated Learning Framework for Smart Healthcare Systems" Future Internet 14, no. 11: 338. https://doi.org/10.3390/fi14110338 (IF = 3.4) [Q2]
[J15] Ahmed, Gulnaz, Meng Joo Er, Mian Muhammad Sadiq Fareed, Shahid Zikria, Saqib Mahmood, Jiao He, Muhammad Asad, Syeda Fizzah Jilani, and Muhammad Aslam. "DAD-Net: Classification of Alzheimer’s Disease Using ADASYN Oversampling Technique and Optimized Neural Network." Molecules 27, no. 20 (2022): 7085. (IF = 4.6) [Q1]
[J14] Fareed, Mian Muhammad Sadiq, Shahid Zikria, Gulnaz Ahmed, Saqib Mahmood, Muhammad Aslam, Syeda Fizzah Jillani, Ahmad Moustafa, and Muhammad Asad. "ADD-Net: An Effective Deep Learning Model for Early Detection of Alzheimer Disease in MRI Scans." IEEE Access (2022). (IF = 3.9) [Q1]
[J13] Aslam, Muhammad, Dengpan Ye, Aqil Tariq, Muhammad Asad, Muhammad Hanif, David Ndzi, Samia A. Chelloug, Mohamed A. Elaziz, Mohammed A.A. Al-Qaness, and Syeda F. Jilani. 2022. "Adaptive Machine Learning Based Distributed Denial-of-Services Attacks Detection and Mitigation System for SDN-Enabled IoT" Sensors 22, no. 7: 2697. https://doi.org/10.3390/s22072697 (IF = 3.9) [Q2]
[J12] Ayesha Shafique, Muhammad Asad, Muhammad Aslam, Saima Shaukat, and Guo Cao “Multi-Hop Similarity-based Clustering Framework for IoT-oriented Software Defined Wireless Sensor Networks“ in IET Wireless Sensor Systems. (IF = 1.6) [Q3]
[J11] Shafique, Ayesha, Guo Cao, Zia Khan, Muhammad Asad, and Muhammad Aslam. 2022. "Deep Learning-Based Change Detection in Remote Sensing Images: A Review" Remote Sensing 14, no. 4: 871. (IF = 5.0) [Q1]
[J10] Asad, Muhammad, Ahmed Moustafa, Fethi A. Rabhi, and Muhammad Aslam. "THF: 3-way hierarchical framework for efficient client selection and resource management in federated learning." IEEE Internet of Things Journal 9, no. 13 (2021): 11085-11097. (IF = 10.6) [Q1]
[J9] Asad Muhammad, Ahmed Moustafa, and Muhammad Aslam. "CEEP-FL: A comprehensive approach for communication efficiency and enhanced privacy in federated learning." Applied Soft Computing (2021): 107235. (IF = 8.7) [Q1]
[J8] Asad Muhammad; Moustafa, Ahmed; Yu, Chao. 2020. "A Critical Evaluation of Privacy and Security Threats in Federated Learning." Sensors 20, no. 24: 7182. (IF = 3.9) [Q2]
[J7] Ayesha Shafique, Guo Cao, Muhammad Aslam, Muhammad Asad, and Dengpan Ye; Application-Aware SDN-Based Iterative Reconfigurable Routing Protocol for Internet of Things (IoT). Sensors 2020, 20, 3521. (IF = 3.9) [Q2]
[J6] Asad Muhammad; Moustafa, Ahmed; Ito, Takayuki. 2020. "FedOpt: Towards Communication Efficiency and Privacy Preservation in Federated Learning." Appl. Sci. 10, no. 8: 2864. (IF = 2.7) [Q2]
[J5] Muhammad Aslam, Fan Wang, Xiaopeng Hu, Muhammad Asad, and Ehsan Ullah Munir, “Multihopping Multilevel Clustering Heterogeneity-Sensitive Optimized Routing Protocol for Wireless Sensor Networks,” Journal of Sensors, vol. 2017, Article ID 5378403, 14 pages, 2017. (IF = 1.9) [Q2]
[J4] Asad Muhammad, et al. "IoT enabled adaptive clustering based energy efficient routing protocol for wireless sensor networks." International Journal of Ad Hoc and Ubiquitous Computing 32.2 (2019): 133-145. (IF = 0.7) [Q3]
[J3] Muhammad Asad, Yao Nianmin, and Muhammad Aslam. "Spiral Mobility Based on Optimized Clustering for Optimal Data Extraction in WSNs." Technologies 6.1 (2018): 35. (IF = 3.6) [Q2]
[J2] Muhammad Asad, Arsalan Ali Shaikh, Soomro Pir Dino, Muhammad Aslam, and Yao Nianmin, "Lifetime Maximization on Scalable Stable Election Protocol for Large Scale Traffic Engineering" International Journal of Advanced Computer Science and Applications(IJACSA), 9(1), 2018. (IF = 0.9) [Q3]
[J1] Christopher Mumpe, Da Tang, Muhammad Asad, Jing Chen, Jinsi Zhu, and Luyuan jin, "Neighbour-Cooperation Heterogeneity-Aware Traffic Engineering For Wireless Sensor Networks" International Journal of Advanced Computer Science and Applications(IJACSA), 9(12), 2018. (IF = 0.9) [Q3]
International Conferences
[C15] Muhammad Asad and Yading Yuan "FeSEC: a secure and efficient federated learning framework for medical imaging", Proc. SPIE 12931, Medical Imaging 2024: Imaging Informatics for Healthcare, Research, and Applications, 129310F (2 April 2024); https://doi.org/10.1117/12.3005993
[C14] Asad, Muhammad, Safa Otoum, and Omar Al Fandi. "Edge Computing for the Metaverse: Balancing Security and Privacy Concerns." 2023 International Conference on Intelligent Metaverse Technologies & Applications (iMETA). IEEE, 2023.
[C13] Asad, Muhammad, and Safa Otoum. "Towards Privacy-Aware Federated Learning for User-Sensitive Data." 2023 Fifth International Conference on Blockchain Computing and Applications (BCCA). IEEE, 2023.
[C12] Bao, Naren, Jin Nakazato, Asad Muhammad, Ehsan Javanmardi, and Manabu Tsukada. "Towards a Trusted Inter-Reality: Exploring System Architectures for Digital Identification." In Proceedings of the 13th International Conference on the Internet of Things, pp. 270-275. 2023.
[C11] Yusuke Sugizaki, Hideya Ochiai, Muhammad Asad, Manabu Tsukada, Hiroshi Esaki, "Wireless Ad-Hoc Federated Learning for Cooperative Map Creation and Localization Models," In The 9th IEEE World Forum on Internet of Things (IEEE WFIoT2023), Aveiro, Portugal, 2023.
[C10] Wang, Zekun, Jin Nakazato, Muhammad Asad, Ehsan Javanmardi, and Manabu Tsukada. "Overcoming Environmental Challenges in CAVs through MEC-based Federated Learning." In 2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN), pp. 151-156. IEEE, 2023.
[C9] Asad, Muhammad, Safa Otoum, and Saima Shaukat. "Resource and Heterogeneity-aware Clients Eligibility Protocol in Federated Learning." In GLOBECOM 2022-2022 IEEE Global Communications Conference, pp. 1140-1145. IEEE, 2022.
[C8] Muhammad Asad, Ahmed Moustafa, and Takayuki Ito "Federated Learning Verses Classical Machine Learning: A Convergence Comparison" The 15th International Conference on Knowledge, Information and Creativity Support Systems (KICSS 2020), Tasmania, Australia (Online), 25-27 November 2020. (yet to publish)
[C7] Aslam, Muhammad, Dengpan Ye, Muhammad Hanif, and Muhammad Asad. "Adaptive Machine learning: A Framework for Active Malware Detection." In 2020 16th International Conference on Mobility, Sensing and Networking (MSN), pp. 57-64. IEEE, 2020.
[C6] Asad, Muhammad, Ahmed Moustafa, Takayuki Ito, and Muhammad Aslam. "Evaluating the communication efficiency in federated learning algorithms." In 2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 552-557. IEEE, 2021.
[C5] Mohamed, Tagy Aldeen, Ahmed Moustafa, Takayuki Ito, and Muhammad Asad. "Toward Agent-based Interactive Systems to Support Rehabilitation Process." In 2021 IEEE 24th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 558-562. IEEE, 2021.
[C4] Asad, Muhammad, and Muhammad Aslam. "Heuristic Path-Reconfiguration Algorithm Using Multi-hop Opportunistic Routing in WSNs." In 2018 International Conference on Frontiers of Information Technology (FIT), pp. 47-52. IEEE, 2018.
[C3] Ayoub, Naeem, Muhammad Asad, Muhammad Aslam, Zhenguo Gao, Ehsan Ullah Munir, and Rachida Tobji. "MAHEE: Multi-hop advance heterogeneity-aware energy efficient path planning algorithm for wireless sensor networks." In Communications, Computers and Signal Processing (PACRIM), 2017 IEEE Pacific Rim Conference on, pp. 1-6. IEEE, 2017.
[C2] Aslam, Muhammad, Fan Wang, Zefeng Lv, Muhammad Asad, Samra Zafar, Ehsan Ullah Munir, and Xiaopeng Hu. "Energy Efficient Cubical layered Path Planning Algorithm (EECPPA) for acoustic UWSNs." In Communications, Computers and Signal Processing (PACRIM), 2017 IEEE Pacific Rim Conference on, pp. 1-6. IEEE, 2017.
[C1] Aslam, Muhammad, Ehsan Ullah Munir, Muhammad Bilal, Muhammmad Asad, Asad Ali, Tauseef Shah, and Syed Bilal. "HADCC: hybrid advanced distributed and centralized clustering path planning algorithm for WSNs." In Advanced Information Networking and Applications (AINA), 2014 IEEE 28th International Conference on, pp. 657-664. IEEE, 2014.
Book Chapter
[B2] Moustafa A., Asad Muhammad., Shaukat S., Norta A. (2021) PPCSA: Partial Participation-Based Compressed and Secure Aggregation in Federated Learning. In: Barolli L., Woungang I., Enokido T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 226. Springer, Cham. https://doi.org/10.1007/978-3-030-75075-6_28
[B1] Aslam, Muhammad, Dengpan Ye, Muhammad Hanif, and Muhammad Asad. "Machine learning based SDN-enabled distributed denial-of-services attacks detection and mitigation system for Internet of Things." In International Conference on Machine Learning for Cyber Security, pp. 180-194. Springer, Cham, 2020.
Poster Presentation
[P1] Dou Hu, Jin Nakazato, Ehsan Javanmardi, Muhammad Asad, Manabu Tsukada "An Extended Kalman Filter Enabled Beam Tracking Framework in Intersection Management" in 2023 EuCNC & 6G Summit.