I am Mohammed El-hajj, a dedicated professional with a robust academic background and a fervent commitment to advancing the field of network security. My journey commenced with the attainment of my B.S. from the School of Computer Science at IUL University in Lebanon in 2004, followed by an M.S. from Kingston University in London in 2008. This journey culminated in the completion of my Ph.D. in network security at the University Saint-Joseph in Lebanon in 2020.
My career initiated as an Assistant Professor in the Department of Computer Science at the University of Sciences and Arts in Lebanon. Here, I cultivated expertise in software development, IoT, network security, programming, and teaching. Throughout this period, I showcased my dedication to research and education within this domain.
Recently, I transitioned to a new role as a Lecturer at the University of Twente, where my focus extends toward securing critical infrastructures. At the University of Twente, I am actively engaged in pioneering research initiatives that center on the security aspects of critical infrastructures, employing digital twins and harnessing advanced technologies like generative AI and federated learning within machine learning to fortify security measures.
My research interests revolve around enhancing the understanding, design, and performance of authentication protocols for IoT ecosystems. I have particularly focused on developing a hardware security platform based on Physical Un-clonable Functions (PUF) to mitigate machine learning attacks and provide robust authentication for IoT devices. Additionally, I explore the use of digital twins to bolster the security of diverse IoT applications, contributing significantly to the evolving landscape of network and IoT security.
With a proven track record in higher education and a diverse skill set encompassing software development, IoT, network security, and teaching, I continue to lead groundbreaking research in securing critical infrastructures. I embrace innovative technologies and contribute to advancing security within IoT ecosystems.
I specialize in IoT and network security, focusing on enhancing authentication protocols in IoT ecosystems using Distributed Ledger Technologies like Ethereum Blockchain and IOTA. Additionally, I'm developing a hardware security platform based on Physical Unclonable Functions (PUF) for IoT device authentication, addressing vulnerabilities to machine learning attacks.
I explore the application of digital twins to bolster Critical Infrastructure (CI) security and integrate generative AI and federated learning. Digital twins offer preemptive defense by simulating systems, while generative AI and federated learning contribute to identifying threats and strengthening CI security.
My research aims to synergize these elements—DLTs, hardware security, digital twins, generative AI, and federated learning—to fortify comprehensive security frameworks for Critical Infrastructures against evolving cyber threats.
Elhajj, M., Jradi, H., Chamoun, M. and Fadlallah, A., 2022, June. LASII: Lightweight Authentication Scheme using IOTA in IoT Platforms. In 2022 20th Mediterranean Communication and Computer Networking Conference (MedComNet) (pp. 74-83). IEEE.
El-Hajj, M., Fadlallah, A., Chamoun, M. and Serhrouchni, A., 2021. A taxonomy of PUF Schemes with a novel Arbiter-based PUF resisting machine learning attacks. Computer Networks, p.108133.
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Courses Academic Year 2023/2024
Courses Academic Year 2022/2023
I did more than 24 interviews talking about privacy, security, and IoT.
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