Federated learning
& network security
Distributed and peer-to-peer learning for cyberattack detection in 5G, vehicle-to-everything and Open RAN environments.
PhD candidate · Montréal
Learning together.
Securing what
connects us.
I’m Fahdah Alalyan. I study machine learning for secure wireless networks, bringing together federated learning, quantum ML and cyberattack detection.
École de technologie supérieurePhD in Computer Engineering · In progressMontréal, Canada
01 / Research focus
Intelligence at the
network’s edge.
My work explores how learning systems can detect attacks and support resilience across next-generation mobile networks.
Federated learning
Quantum ML
& anomaly detection
Investigating quantum machine-learning approaches to identify anomalous behavior in 5G and beyond mobile networks.
Statistical learning
& data modeling
Classification and clustering for binary and categorical data using mixture models, similarity measures and probabilistic methods.
Alongside model development, I have studied RF jamming resilience in experimental O-RAN networks.
Explore my research datasets ↗02 / Publications
From questions
to published research.
Collaborative research in secure communication, distributed learning and statistical data analysis.
2026
2026
2025
2024
Earlier publications · 2019–2020
2020
2019
2019
Manuscript under review
Quantum GAN-Assisted Peer-to-Peer Federated Learning for Decentralized O-RAN Cyberattacks Detection
Submitted to IEEE Transactions on Machine Learning in Communications and Networking.03 / Experience
A research path
across data
and networks.
Research experience at ÉTS, Carleton University and Concordia, supported by training in cyber defence and data science.
January 2023–present
Research Assistant
École de technologie supérieure
Developing AI-based algorithms for cyberattack detection in 5G and O-RAN, with a focus on federated learning and quantum machine learning.
June–August 2026
Summer Research Assistant
Carleton University
Conducted experimental research on RF jamming resilience in O-RAN-based terrestrial and non-terrestrial networks.
July 2021–January 2022
CyberPro+ Trainee
National Cybersecurity Authority and SITE
Training in operating systems, networking, cyber defence, penetration testing, and threat detection.
December 2020–February 2021
Data Scientist Intern
General Assembly
Built and evaluated machine-learning models for data-science problems.
January 2018–October 2020
Research Assistant in ML and Data Mining
Concordia University
Developed methods for binary-data clustering, mixture-model hierarchical clustering, and probabilistic kernels.
04 / Foundations
Education & methods.
2023–present
PhD in Computer Engineering
École de technologie supérieure
Université du Québec · Montréal
Expected completion: August 2027
2020
MASc in Information Systems Security
Concordia University · Montréal
Read my master’s thesis ↗2013
BSc in Information Systems
Princess Nourah bint Abdulrahman University · Riyadh
Research toolkit
Additional training in cyber defence, network auditing and security controls. Credentials earned: GIAC GCCC (2022), CompTIA CySA+ (2021) and CompTIA Security+ (2021).
05 / Contact
Let’s connect
around research.
For research collaborations and conversations in machine learning, cybersecurity and wireless networks.