Dr. Aliya Tabassum
BIO
Dr. Aliya Tabassum is a cybersecurity and artificial intelligence academic, researcher, and trainer with around 10 years of experience spanning higher education, research, and professional cybersecurity training. She holds a PhD in Computer Science from Qatar University, specializing in cybersecurity, intrusion detection systems, Internet of Things (IoT) security, and deep learning. She is also a Cisco Certified Network Associate (CCNA) and Certified Ethical Hacker (CEH).
Her academic and research experience includes appointments at Qatar University, Hamad Bin Khalifa University, and the Community College of Qatar. Her research interests span AI-driven cybersecurity, intrusion detection, IoT and network security, privacy-preserving machine learning, deep learning, federated learning, AI security, and responsible applications of artificial intelligence.
Alongside her academic work, Dr. Tabassum has contributed to applied cybersecurity training in Qatar. She served as a Cyber Range Trainer for a national cybersecurity awareness, preparedness, and resilience program ahead of the FIFA World Cup Qatar 2022, delivering hands-on training in cyberattack detection, incident response, cyber defence, and red-team/blue-team scenarios to participants from government, semi-government, and private-sector organizations.
Academic Qualifications
- PhD in Computer Science, Qatar University, Qatar, 2022 Specialization: Cybersecurity, Intrusion Detection Systems, IoT Security and Deep Learning Dissertation: Privacy-Preserving Decentralized Intrusion Detection System for IoT Devices Using Deep Learning
- Master of Technology, Jawaharlal Nehru Technological University Hyderabad (JNTUH), India, 2015
- Bachelor of Technology,, Jawaharlal Nehru Technological University Hyderabad (JNTUH), India, 2014 Completed as a five-year integrated B.Tech–M.Tech dual degree programme
Research Interests
- Cybersecurity, Network Security & Incident Response
- AI-Driven Cybersecurity & Intrusion Detection
- IoT & Cyber-Physical Systems Security
- Machine Learning, Deep Learning & Federated Learning
- Privacy-Preserving & Trustworthy AI
Teaching Area
- Cybersecurity, Ethical Hacking & Security Auditing
- Network Security & Advanced Networking
- Artificial Intelligence & Machine Learning
- Programming & Data Science
Selected Publications
- Tabassum, A., Erbad, A., Lebda, W., Mohamed, A., & Guizani, M. (2022). FedGAN-IDS: Privacy-Preserving IDS Using GAN and Federated Learning. Computer Communications, 192, 299–310.
- Tabassum, A., Erbad, A., Mohamed, A., & Guizani, M. (2021). Privacy-Preserving Distributed IDS Using Incremental Learning for IoT Health Systems. IEEE Access, 9, 14271–14283.
- Tabassum, A., Erbad, M., & Guizani, M. (2019). A Survey on Recent Approaches in Intrusion Detection System in IoTs. 15th International Wireless Communications & Mobile Computing Conference (IWCMC).
- Google scholar: https://scholar.google.com/citations?user=nlme36YAAAAJ&hl=en&oi=ao
- LinkedIn profile: https://www.linkedin.com/in/aliya-tabassum-21051993/
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