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Athens OH 45701
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Russ College of Engineering and Technology
Faculty
Ahmed Oun

Ahmed Oun

Assistant Professor
Electrical Engineering and Computer Science
740-593-1251
Stocker Center 322B

Education

  • Electrical Engineering and Computer Science Department, University of Toledo, Toledo, OH, 2022
  • Master’s degree in electrical engineering from the University of Bridgeport, Bridgeport, CT, 2012

Research Interests

  • Cybersecurity
  • Hardware-assisted security for trusted embedded systems
  • VLSI
  • Computing systems
  • Secure Internet of Things (IoT) applications
  • Secure data communication using machine learning

Biography

Dr. Ahmed Oun is an Assistant Professor in the School of Electrical Engineering and Computer Science (EECS) at Ohio University, which he joined in 2024. Prior joining OU, he held a faculty position at Ohio Northern University. Before transitioning to academia, Dr. Oun held various positions in the oil and gas industry, including roles as a Gas Turbine Controls NPI Engineer and Operation Control Room Supervisor. He later served as a Project Manager at General Electric International Inc.

Dr. Oun's work also focused on adopting AI and developing new approaches for securing and protecting advanced computing systems against cyber-attacks, design thefts, and hardware Trojans.

Journal Article, Academic Journal (6)

  • Oun, A., Maheshwari, D., Ammar, A. (2026). Deep Learning-Based Relay Selection in a Decode-and-Forward Cooperative System with Energy Harvesting and Signal Space Diversity. 7. MDPI Electronics; 15: 1363. https://www.mdpi.com/2079-9292/15/7/1363.
  • Oun, A., WINCE, K., CHENG, X. (2025). The Role of Artificial Intelligence in Boosting Cybersecurity and Trusted Embedded Systems Performance: A Systematic Review on Current and Future Trends. IEEE Access; 13: 55258 - 55276. https://ieeexplore.ieee.org/abstract/document/10942377.
  • Oun, A., Hagerdorn, N., Scheideger, C., Cheng, X. (2024). Mobile Devices or Head-Mounted Displays: A Comparative Review and Analysis of Augmented Reality in Healthcare. IEEE Access; 12: 21825-21839. https://doi.org/10.1109/access.2024.3361833.
  • Oun, A., Hazari, N., Niamat, M. (2021). Analysis of Swarm Intelligence Based ANN Algorithms for Attacking PUFs. IEEE Access; 9: 121743-121758. https://doi.org/10.1109/access.2021.3109235.
  • Amsaad, F., Oun, A., Niamat, M., Razaque, A., Kose, S., Mahmoud, M., Alasmary, W., Alsolami, F. (2021). Enhancing the Performance of Lightweight Configurable PUF for Robust IoT Hardware-Assisted Security. IEEE Access; 9: 136792-136810. https://doi.org/10.1109/access.2021.3117240.
  • Hazari, N., Oun, A., Niamat, M. (2021). Machine Learning Vulnerability Analysis of FPGA-based Ring Oscillator PUFs and Counter Measures. 3. ACM Journal on Emerging Technologies in Computing Systems; 17: 1-20. https://doi.org/10.1145/3445978.

Conference Proceeding (21)

  • Singh, H., Oun, A. (2026). A Hardware-Efficient TinyML-Based Fault Detection Framework for Reliable AI Accelerators. 69th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS).
  • Foysal, M., Oun, A. (2026). Detecting the Undetectable: Blind Spots of Clustering and Anomaly Detection in PUF Trojan Defense. 69th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS).
  • Chowdhury , S., Oun, A. (2026). Post-Quantum Safe and Side Channel Attack Resilient ARM Cortex M4 Satellite Uplink. 69th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS).
  • Foysal, M., Oun, A. (2026). REMIX-PUF: A Temporal Response Mixing PUF Design Resistant to Machine Learning Attacks. 69th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS).
  • Chowdhury , S., Hammad, A., Dragos , J., Oun, A. (2026). Post-Compilation Side- Channel Attack Countermeasure Framework for STM32. Cincinnati, OH. USA: 69th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS); https://mwscas2026.org/.
  • Richards, L., Oun, A. (2026). Evaluating CNN Model Accuracy and FPGA Resource Utilization in Quadrant-Based Facial Emotion Recognition. Houston, TX, USA: 2026 IEEE 2nd International Conference on Secure IoT, Assured and Trusted Computing (SATC); 1-4. https://ieeexplore.ieee.org/abstract/document/11542421.
  • Oun, A., Das, R., Hess, C., Barat, A., Kaya, S. (2026). A PUF-Based Security Framework for Fault and Intrusion Detection. Dubai: 2026 IEEE 44th International Conference on Consumer Electronics (ICCE); 1-6. https://ieeexplore.ieee.org/abstract/document/11449811.
  • Oun, A., Das, R., Hess, C., Barat, A., Kaya, S. (2026). A PUF-Based Security Framework for Fault and Intrusion Detection.
  • Nur Nabilah, N., Jamal Chowdhury, S., Oun, A., Raghavendra Kulkarni, A., Annamalai, A. (2025). DeepAttack: X-Deep Side-Channel Attacks on Encryption Algorithm. Denver, CO: 2025 IEEE Physical Assurance and Inspection of Electronics (PAINE); https://ieeexplore.ieee.org/document/11320217.
  • Barat, A., Kaya, S., Oun, A., Karanth , A. (2025). Design & Verification of a Novel PUF for Enhanced IC Security Based on Total Harmonic Distortion in CMOS Inverters. IEEE; 887-891. https://ieeexplore.ieee.org/document/11244491.
  • Barat, A., Kaya, S., Canan, T., Oun, A., Karanth , A. (2025). Use of Current Transient Spectroscopy for Process Authentication and Device Reliability. IEEE; 637-641. https://ieeexplore.ieee.org/document/11244491.
  • Ammar, A., Oun, A., Martell, W., Khan, M. (2024). Relay Selection Machine Learning-Based for a DF Cooperative System with Energy Harvesting and Signal Space Diversity. Springfield, MA: 2024 IEEE 67th International Midwest Symposium on Circuits and Systems (MWSCAS); https://ieeexplore.ieee.org/abstract/document/10658834/authors#authors.
  • Berei, E., Khan, M., Oun, A. (2024). Machine Learning Algorithms for DoS and DDoS Cyberattacks Detection in Real-Time Environment. IEEE; 1048-1049. https://doi.org/10.1109/ccnc51664.2024.10454755.
  • Berei, E., Oun, A., Khan, M. (2023). Enhancing cybersecurity: A pipeline approach for efficient machine learning intrusion detection. New York, NY: 2023 IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON); https://ieeexplore.ieee.org/abstract/document/10316023.
  • Oun, A., Niamat, M. (2023). PUF-Based Authentication for the Security of IoT Devices. Romeoville, IL: 2023 IEEE International Conference on Electro Information Technology (eIT); https://ieeexplore.ieee.org/abstract/document/10187363.
  • Oun, A., Niamat, M. (2021). Design of a Delay-Based FPGA PUF Resistant to Machine Learning Attacks. IEEE; 865-868. https://doi.org/10.1109/mwscas47672.2021.9531815.
  • Oun, A., Niamat, M. (2020). Defense mechanism vulnerability analysis of ring oscillator PUFs against neural network modeling attacks using the dragonfly algorithm. Chicago, IL: 2020 IEEE International Conference on Electro Information Technology (EIT); https://ieeexplore.ieee.org/abstract/document/9208320.
  • Hazari, N., Alsulami, F., Oun, A., Niamat, M. (2020). Performance analysis of XOR-inverter based ring oscillator PUF for hardware security. Dayton, OH: 2019 IEEE National Aerospace and Electronics Conference (NAECON); https://ieeexplore.ieee.org/abstract/document/9058002.
  • Razaque, A., Frej, M., Sabyrov, D., Shaikhyn, A., Amsaad, F., Oun, A. (2020). Detection of Phishing Websites using Machine Learning. IEEE; 103-107. https://doi.org/10.1109/ieeecloudsummit48914.2020.00022.
  • Gulsezim, D., Zhansaya, S., Razaque, A., Ramina, Y., Amsaad, F., Almiani, M., Ganda, R., Oun, A. (2019). Two Factor Authentication using Twofish Encryption and Visual Cryptography Algorithms for Secure Data Communication. IEEE; 405-411. https://doi.org/10.1109/iotsms48152.2019.8939261.
  • Hazari, N., Oun, A., Niamat, M. (2019). Analysis and Machine Learning Vulnerability Assessment of XOR-Inverter based Ring Oscillator PUF Design. IEEE; 590-593. https://doi.org/10.1109/mwscas.2019.8885037.