Publications

• Notable Conference Papers (C)
• [C22] M. Nazzal, I. Khalil, A. Khreishah, and N.H. Phan, “PromSec: Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models (LLMs),” 31st ACM Conference on Computer and Communications Security (CCS 2024), Salt Lake City, UT, USA, Oct. 2024. Covered by a US Provisional Patent.
• [C21] M. Nazzal, I. Khalil, A. Khreishah, N.H. Phan, and Y. Ma, “Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection,” in 45th IEEE Symposium on Security and Privacy (IEEE S&P 2024), San Francisco, CA, USA, May 2024. Presentation Video
• [C20] A. Al-Barqawi, M. Nazzal, I. Khalil, A. Khreishah, and N.H. Phan, “ViGText: Deepfake Image Detection with Vision-Language Model Explanations and Graph Neural Networks,” Accepted to appear in the 33rd Network and Distributed System Security (NDSS 2026), San Diego, CA, USA, Feb 2026.
• [C19] M. Nazzal*, K. Nguyen*, D. Vungarala*, R. Zand, H. Phan, A. Khreishah, and S. Angizi, “FedChip: Federated LLM for Artificial Intelligence Accelerator Chip Design,” Accepted to appear in IEEE International Conference on LLM-Aided Design, 2025 (ICLAD), Stanford University, Stanford, CA, Jun. 2025. [Accepted] (*Equal contribution)
• [C18] D. Vungarala*, M. Nazzal*, M. Morsali, C. Zhang, A. Ghosh, A. Khreishah, and S. Angizi, “SA-DS: A Dataset for Large Language Model-Driven AI Accelerator Design Generation,” 58th IEEE International Symposium on Circuits and Systems (ISCAS 2025). [Accepted] (*Equal contribution)
• [C17] T.K. Ton, N. Nguyen, M. Nazzal, A. Khreishah, C. Borcea, N.H. Phan, R. Jin, I. Khalil, and Y. Shen, “Demo: SGCode: A Flexible Prompt-Optimizing System for Secure Generation of Code,” 31st ACM Conference on Computer and Communications Security (CCS 2024), Salt Lake City, UT, USA, Oct. 2024.
• [C16] M. Morsali, M. Nazzal, A. Khreishah, and S. Angizi, “IMA-GNN: In-Memory Acceleration of Centralized and Decentralized Graph Neural Networks at the Edge,” 33rd edition of Great Lakes Symposium on VLSI (GLSVLSI), Knoxville, TN, USA, Jun. 2023. [Best Paper Award]
• Notable Journal Papers (J)
• [J12] M. Nazzal, A. Khreishah, J. Lee, S. Angizi, A. Al-Fuqaha, and M. Guizani, “Semi-decentralized Inference in Heterogeneous Graph Neural Networks for Traffic Demand Forecasting: An Edge-Computing Approach,” IEEE Transactions on Vehicular Technology, Jan. 2024.
• Notable Patents (P)
• [P7] M. Nazzal, I. Khalil, A. Khreishah, and N.H. Phan, “Method and System for Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models,” US Patent, Patent Application No.: US63/561,573, Washington, D.C., USA, Filing date: Mar. 5, 2024.
• Notable Book Chapters (BC)
• [BC1] M. Nazzal, M. A. Aygul, and H. Arslan, Channel Modeling for 5G and Beyond, In: H. Arslan, E. Basar, Flexible and Cognitive Radio Access Technologies for 5G and Beyond, Telecommunications Series, Institution of Engineering and Technology, ISBN-13: 978-1-83953-079-1, p. 342, 2020.

• [J11] I. Alsmadi, K. Ahmad, M. Nazzal, F. Khurshid, and A. Al-Ali, “Adversarial NLP for Social Network Applications: Attacks, Defenses, and Research Directions,” IEEE Transactions on Computational Social Systems, vol. 10, no. 6, pp. 3089-3108, Nov. 2022.
• [J10] N. Aljaafari, M. Nazzal, S. Al-Safadi, A. Al-Qirim, and A. Salama, “Investigating the Factors Impacting Adversarial Attack and Defense Performances in Federated Learning,” IEEE Transactions on Engineering Management, May 2022.
• [J9] I. Alsmadi, N. Aljaafari, M. Nazzal, M. Abu-Tair, and T. Sakr, “Adversarial Machine Learning in Text Processing: A Literature Survey,” IEEE Access, vol. 10, pp. 17043-17077, Jan. 2022.
• [J8] H.M. Furqan, M.A. Aygül, M. Nazzal, S. Gul, and M. Khan, “Primary User Emulation and Jamming Attack Detection in Cognitive Radio via Sparse Coding,” EURASIP Journal on Wireless Communications and Networking, Apr. 2020.

• [J7] M.A. Aygül, M. Nazzal, et al., “Sparsifying Dictionary Learning for Beamspace Channel Representation,” IEEE Access, vol. 11, Sep. 2023.
• [J6] S. Shao, M. Nazzal, et al., “Self-optimizing Data Offloading in Mobile Heterogeneous Radio-Optical Networks,” IEEE Network Magazine, vol. 36, no. 2, May 2022.
• [J5] A. Alenezi, M. Nazzal, et al., “Machine Learning Regression-based RETRO-VLP for Real-time and Stabilized Indoor Positioning,” Cluster Computing, Dec. 2022.

• [C15] M. Nazzal, N. Aljaafari, A. Sawalmeh, A. Khreishah, M. Anan, A. Algosaibi, M. Alnaeem, A. Aldalbahi, A. Alhumam, C. P. Vizcarra, and S. Alhamed, “Genetic Algorithm-Based Dynamic Backdoor Attack on Federated Learning-Based Network Traffic Classification,” 8th International Conference on Fog and Mobile Edge Computing (FMEC 2023), Tartu, Estonia, Sep. 18-20, 2023.
• [C14] M.A. Aygül, M. Nazzal, and H. Arslan, “Estimating Multi-Dimensional Sparsity Level for Spectrum Sensing,” 2023 IEEE Wireless Communications and Networking Conference (WCNC 2023), Glasgow, Scotland, UK, Mar. 2023.
• [C13] M.A. Aygül, H.M. Furqan, M. Nazzal, and H. Arslan, “Deep Learning-Assisted Detection of PUEA and Jamming Attacks in Cognitive Radio Systems,” 2020 IEEE 92nd Vehicular Technology Conference: VTC2020-Fall, Victoria, BC, Canada, Oct. 2020.
• [C12] M. Nazzal, A. Sawalmeh, S. Shao, M. Anan, A. Khreishah, and A. Alanazi, “Retro-VLP: Towards Single Light Source-based Real-time Indoor Positioning,” International Conference on Information and Communication Systems (ICICS 2022), Irbid-Jordan, Jun. 2022.
• [C11] M. Nazzal, M.A. Aygül, and H. Arslan, “Estimation and Exploitation of Multidimensional Sparsity for MIMO-OFDM Channel Estimation,” 2022 IEEE Wireless Communications and Networking Conference (WCNC 2022), Austin, TX, USA, Apr. 2022.
• [C10] M.A. Aygül, M. Nazzal, and H. Arslan, “Deep RL-Based Spectrum Occupancy Prediction Exploiting Time and Frequency Correlations,” 2022 IEEE Wireless Communications and Networking Conference (WCNC 2022), Austin, TX, USA, Apr. 2022.
• [C9] M. Nazzal, M.A. Aygül, and H. Arslan, “Sparse Coding with Enhanced Atom Selection for FDD Massive MIMO Channel Estimation,” 2021 IEEE 94th Vehicular Technology Conference: VTC2021-Fall, Norman, OK, USA, Sep. 2021.
• [C8] M.A. Aygül, M. Nazzal, and H. Arslan, “Using OMP and SD Algorithms Together in Millimeter Wave Massive MIMO Channel Estimation,” Signal Processing and Communications Applications Conference (SIU 2021), Istanbul, Turkey, Jun. 2021.
• [C7] M.A. Aygül, M. Nazzal, and H. Arslan, “Deep Learning-Based Optimal RIS Interaction Exploiting Previously Sampled Channel Correlations,” 2021 IEEE Wireless Communications and Networking Conference (WCNC 2021), Nanjing, China, Mar. 2021.
• [C6] M.A. Aygül, M. Nazzal, A.R. Ekti, A. Gorcin, D.B. da Costa, H.F. Ates, and H. Arslan, “Spectrum Occupancy Prediction Exploiting Time and Frequency Correlations Through 2D-LSTM,” 2020 IEEE 91st Vehicular Technology Conference: VTC2020-Spring, Antwerp, Belgium, May 2020.
• [C5] M. Nazzal, O. Hasekioğlu, A.R. Ekti, A. Gorcin, and H. Arslan, “Compressed spectrum sensing using sparse recovery convergence patterns through machine learning classification,” IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2019), Istanbul, Turkey, Sept. 2019.
• [C4] M. Nazzal, M.A. Aygül, A. Görçün, and H. Arslan, “Dictionary learning-based beamspace channel estimation in millimeter-wave massive MIMO systems with a lens antenna array,” The International Wireless Communications & Mobile Computing Conference (IWCMC 2019), Tangier, Morocco, Jun. 2019.
• [C3] M. Nazzal, M.A. Aygül, A. Görçün, and H. Arslan, “Sparse Coding for transform domain-based sparse OFDM channel estimation,” Signal Processing and Communications Applications Conference (SIU 2019), Sivas, Turkey, Apr. 2019.
• [C2] M. Nazzal, H.M. Furqan, and H. Arslan, “FDD massive MIMO channel estimation by sparse coding over AoA/AoD cluster dictionaries,” IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2018), Bologna, Italy, Sept. 2018.
• [C1] H.M. Furqan, M. Nazzal, and H. Arslan, “Iterative tap pursuit for channel shortening equalizer design,” 7th International Conference on Computer and Communication Engineering (ICCCE 2018), Kuala Lumpur, Malaysia, Sept. 2018.

• [P7] M. Nazzal, I. Khalil, A. Khreishah, and N.H. Phan, “Method and System for Prompt Optimization for Secure Generation of Functional Source Code with Large Language Models,” US Patent, Application No.: US63/561,573, Washington, D.C., USA, Filing date: Mar. 5, 2024.
• [P6] M.A. Aygül, M. Nazzal, and H. Arslan, “Learning-Based Spectrum Occupancy Prediction Exploiting Multi-Dimensional Correlation,” US Patent, Patent No.: US20230388809A1, Washington, D.C., USA, Publication date: Nov. 30, 2023.
• [P5] M.A. Aygül, H.M. Furqan, M. Nazzal, and H. Arslan, “Primary User Emulation / Signal Jamming Attack Detection Method,” US Patent, Patent No.: US20230025147A1, Washington, D.C., USA, Publication date: Jan. 26, 2023.
• [P4] M.A. Aygül, H.M. Furqan, M. Nazzal, and H. Arslan, “Primary User Emulation / Signal Jamming Attack Detection Method,” Patent Cooperation Treaty (PCT), Patent No.: EP4082135A1, Munich, Germany, Publication date: Nov. 2, 2022.
• [P3] M.A. Aygül, M. Nazzal, and H. Arslan, “Learning-Based Spectrum Occupancy Prediction Exploiting Multi-Dimensional Correlation,” Patent Cooperation Treaty (PCT), Patent No.: EP3989626A1, Munich, Germany, Publication date: Apr. 27, 2022.
• [P2] M.A. Aygül, M. Nazzal, and H. Arslan, “Learning-Based Spectrum Occupancy Prediction Exploiting Multi-Dimensional Correlation,” European Patent Office (EPO) Patent Pending, Patent No.: WO2022084096A1, Munich, Germany, Publication date: Apr. 28, 2022.
• [P1] M.A. Aygül, H.M. Furqan, M. Nazzal, and H. Arslan, “Primary User Emulation / Signal Jamming Attack Detection Method,” World Intellectual Property Organization (WIPO), Patent No.: WO2021133312A1, Geneva, Switzerland, Publication date: Jul. 1, 2021.

• [BC1] M. Nazzal, M.A. Aygül, et al., “Channel Modeling for 5G and Beyond,” In: H. Arslan, E. Basar, Flexible and Cognitive Radio Access Technologies, Institution of Engineering and Technology, 2020.

Back to Homepage