Ruba Al Omari
Assistant Professor, Teaching Stream, P.Eng
Department:
Electrical Engineering & Computer Science
Email: alomari@yorku.ca
Bio
Dr. Ruba Al Omari is an Assistant Professor, Teaching Stream, in the Department of Electrical Engineering and Computer Science at York University.
She holds a PhD in Computer Science and a Master of Information Technology Security (MITS) degree from Ontario Tech University, where she received the Doctoral Excellence Award.
Her teaching and research interests focus on cybersecurity, with an emphasis on the application of artificial intelligence and machine learning to security challenges.
Prior to joining York University, Dr. Al Omari taught at Ontario Tech University and Durham College.
Before transitioning to academia, Dr. Al Omari gained more than 15 years of industry experience in information technology, with roles spanning user support, network administration, and cybersecurity.
Courses taught
Graduate Level:
- Attack and Defense
- Special Topics in IT: AI in Cybersecurity
- Secure Software Systems
- Security Policies and Risk Management
- Biometrics/Access Control and Smart Card Technology
Undergraduate Level:
- Malware Analysis
- Network Security and Forensics
- Applied Cryptography
- Introduction to Pen Testing
- Hacking and Exploits
- Incident Handling and Response
- IT Security Policies and Procedures
- Introduction to Machine Learning
- Introduction to AI and Logic Programming
- Operating System Fundamentals
- Operating Systems
- Network Administration I & II
Capstone Courses:
- Computer Security Project
- Capstone I & II
Publications
- Alomari, R., Martin, M. V., MacDonald, S., Maraj, A., Liscano, R., & Bellman, C. Inside out-A study of users’ perceptions of password memorability and recall. Journal of Information Security and Applications, Vol. 47:223-234. Elsevier, August, 2019.
- Alomari, R., & Thorpe, J. On password behaviours and attitudes in different populations. Journal of Information Security and Applications, Vol. 45:79-89. Elsevier, April, 2019.
- Alomari, R., Martin, M. V., MacDonald, S., & Bellman, C. Using EEG to predict and analyze password memorability. IEEE International Conference on Cognitive Computing (ICCC), (pp. 42-49). IEEE, July 2019.
- Alomari, R., & Martin, M. V. Classification of EEG signals using neural networks to predict password memorability. In 17th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 791-796). IEEE, 2018.
- Alomari, R., Martin, M. V., MacDonald, S., Bellman, C., Liscano, R., & Maraj, A. What your brain says about your password: Using brain-computer interfaces to predict password memorability. In 15th annual conference on privacy, security and trust (PST) (pp. 127-12709). IEEE, 2017.
- Bellman, C., Martin, M. V., MacDonald, S., Alomari, R., & Liscano, R. Have we met before? Using consumer-grade brain-computer interfaces to detect unaware facial recognition. Computers in Entertainment (CIE), 16(2), 1-17. ACM, 2018.
- Bellman, C., Vargas Martin, M., Liscano, R., Alomari, R., & MacDonald, S. Excuse me, Do I know you from somewhere? Unaware facial recognition using brain-computer interfaces, In Proceedings of the IEEE International Conference on Cognitive Computing (ICCC) (pp. 143-150). IEEE, 2017.
- Bellman, C., Alomari, R., Fung, A., Vargas Martin, M., & Liscano, R. Challenges in the effectiveness of image tagging using consumer-grade brain-computer interfaces. In Augmented Reality, Virtual Reality, and Computer Graphics: Third International Conference. Proceedings, Part II 3 (pp. 55-64). Springer, 2016.