Research Excellence Award
Zahraa Ghabriess
ENSTA Bretagne, Lebanon
| Zahraa Ghabriess | |
|---|---|
| Affiliation | ENSTA Bretagne |
| Country | Lebanon |
| Google Scholar | rkoyQ8oAAAAJ&hl |
| Subject Area | Cybersecurity, Artificial Intelligence, Federated Learning, IoT Security |
| Event | World Science Awards |
| ORCID | 0009-0003-5746-9504 |
Zahraa Ghabriess is a cybersecurity researcher and doctoral candidate whose academic and professional activities focus on intelligent threat detection, access control systems, federated learning architectures, and security solutions for IoT-enabled 5G and beyond networks. Her work integrates artificial intelligence, machine learning, edge computing, and cybersecurity engineering to address contemporary challenges in digital infrastructure protection. Through research internships, software engineering practice, and doctoral investigations, she has contributed to emerging approaches for intrusion detection and access control automation in distributed environments.[1]
Abstract
Zahraa Ghabriess has developed an interdisciplinary research profile that combines cybersecurity, artificial intelligence, machine learning, and distributed computing systems. Her ongoing doctoral research at ENSTA Bretagne investigates federated edge architectures for intrusion detection in IoT-enabled 5G and beyond communication networks. Through conference publications, submitted journal manuscripts, and collaborative research projects, she contributes to the development of scalable, privacy-preserving, and intelligent security frameworks designed for modern networked environments. Her work addresses emerging cybersecurity challenges associated with large-scale connected systems while promoting advanced detection mechanisms based on federated learning and artificial intelligence methodologies.[2]
Keywords
Cybersecurity, Federated Learning, Intrusion Detection Systems, Internet of Things, 5G Networks, Edge Computing, Artificial Intelligence, Machine Learning, Access Control, Process Mining, Threat Detection, Secure Computing.
Introduction
The rapid expansion of interconnected digital systems has increased the need for innovative cybersecurity solutions capable of protecting large-scale networks from sophisticated threats. Researchers working at the intersection of artificial intelligence and cybersecurity play a crucial role in developing adaptive security mechanisms for future communication infrastructures. Zahraa Ghabriess represents a new generation of cybersecurity researchers whose work focuses on integrating machine learning, federated learning, and edge intelligence into practical security frameworks for IoT-enabled environments. Her academic trajectory demonstrates a commitment to addressing complex security challenges through rigorous research and technological innovation.[3]
Research Profile
Following the completion of a Bachelor of Computer Science and a Master of Science in Cybersecurity from the Lebanese University – Faculty of Sciences, Zahraa Ghabriess expanded her expertise through software engineering practice, research internships, and doctoral studies. Her technical competencies encompass cybersecurity, ethical hacking, artificial intelligence, machine learning frameworks, process mining, data mining, secure programming, web development, mobile application development, and database management systems.[1]
Her current doctoral research at ENSTA Bretagne focuses on intelligent intrusion detection frameworks designed for IoT-enabled 5G and beyond networks. The research combines federated learning methodologies with edge computing architectures to enhance detection accuracy while preserving privacy and reducing centralized processing constraints. These investigations contribute to the broader development of resilient and scalable cybersecurity infrastructures.[2]
Research Contributions
- Development of the FEDGE framework, a federated edge architecture for attack detection in IoT-enabled 5G and beyond networks.
- Research on semi-decentralized federated learning models aimed at improving intrusion detection performance and scalability.
- Investigation of automated extraction of Attribute-Based Access Control (ABAC) rules from Object-Centric Event Logs (OCEL).
- Application of machine learning techniques for detecting unauthorized access attempts through HTTP request and response analysis.
- Comparative evaluation of emerging technologies for attack detection in advanced wireless communication networks.
Publications
The publication record of Zahraa Ghabriess reflects active engagement in cybersecurity research, particularly in intelligent attack detection and federated learning applications. Her notable conference publication examines the integration of advanced technologies for attack detection in IoT-enabled 5G and beyond networks and was presented at the International Wireless Communications and Mobile Computing Conference (IWCMC 2025). Additional submitted manuscripts address forward-looking security visions for future networks and introduce novel federated edge frameworks for intrusion detection.[2]
- Ghabriess, Z., Harb, H., Mansour, A., Yao, K. C., & Osswald, C. (2025). Attacks Detection in IoT-enabled 5G and Beyond Networks: Performance Evaluation of Integrating Cutting-Edge Technologies. IEEE IWCMC 2025.
- IoT-Enabled 5G and Beyond Networks: A Forward Security Vision (Submitted Survey Paper).
- FEDGE: A Federated Edge Framework for Attack Detection in IoT-Enabled 5G and Beyond Networks (Submitted Journal Paper).
- SD-FEDGE: A Semi-Decentralized Federated Edge Framework for Attack Detection in IoT-Enabled 5G Networks (Ongoing Journal Paper).
Research Impact
The significance of Zahraa Ghabriess’s research lies in its practical relevance to next-generation communication networks and critical digital infrastructures. Her investigations into federated edge learning seek to overcome limitations associated with centralized security systems while supporting privacy preservation, scalability, and real-time threat detection. Such contributions are increasingly important as IoT deployments continue to expand across industrial, commercial, and public sectors. Her work also demonstrates the growing convergence of artificial intelligence and cybersecurity as complementary disciplines for addressing emerging security risks.[3]
Award Suitability
Zahraa Ghabriess demonstrates strong suitability for recognition within emerging researcher and cybersecurity innovation award categories. Her academic achievements include advanced graduate education, active doctoral research, conference dissemination, interdisciplinary collaboration, and the development of novel cybersecurity frameworks addressing contemporary technological challenges. The combination of theoretical contributions and practical implementation experience positions her research within areas of growing international importance, particularly those involving intelligent security systems, federated learning architectures, and future communication networks.[2]
Conclusion
Zahraa Ghabriess has established a promising academic profile characterized by research excellence in cybersecurity, artificial intelligence, and federated learning systems. Through doctoral investigations, collaborative research initiatives, and scientific dissemination activities, she contributes to the advancement of secure and intelligent digital infrastructures. Her work reflects contemporary priorities in cybersecurity research and demonstrates the potential for meaningful impact on the protection of future IoT-enabled communication environments.[1]
External Links
References
- Professional curriculum vitae and academic profile of Zahraa Ghabriess, including educational background, professional experience, technical competencies, certifications, and doctoral research activities.
- Ghabriess, Z., Harb, H., Mansour, A., Yao, K. C., & Osswald, C. (2025). Attacks Detection in IoT-enabled 5G and Beyond Networks: Performance Evaluation of Integrating Cutting-Edge Technologies. Proceedings of the International Wireless Communications and Mobile Computing Conference (IWCMC 2025).
https://doi.org/10.1109/IWCMC62903.2025 - ENSTA Bretagne and Lab-STICC Research Activities. Doctoral research information relating to federated learning, intrusion detection systems, and cybersecurity applications for IoT-enabled communication infrastructures.
https://www.ensta-bretagne.fr
