Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications for Centralized and Federated Learning. - Mohamed Amine Ferrag; Othmane Friha; Djallel Hamouda; Leandros Maglaras; Helge Janicke (IEEE Access, 2022)

Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications: Centralized and Federated Learning. - Mohamed Amine Ferrag; Othmane Friha; Djallel Hamouda; Leandros Maglaras; Helge Janicke (IEEE DataPort, 2022)

Generative Adversarial Networks-Driven Cyber Threat Intelligence Detection Framework for Securing Internet of Things. - Mohamed Amine Ferrag; Djallel Hamouda; Mérouane Debbah; Leandros Maglaras; Abderrahmane Lakas (DCOSS-IoT, 2023)

Edge Learning for 6G-Enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses. - Mohamed Amine Ferrag; Othmane Friha; Burak Kantarci; Norbert Tihanyi; Lucas C. Cordeiro; Mérouane Debbah; Djallel Hamouda; Muna Al-Hawawreh; Kim-Kwang Raymond Choo (IEEE Commun. Surv. Tutorials, 2023)

PPSS: A privacy-preserving secure framework using blockchain-enabled federated deep learning for Industrial IoTs. - Djallel Hamouda; Mohamed Amine Ferrag; Nadjette Benhamida; Hamid Seridi (Pervasive Mob. Comput., 2023)

Advancing Cybersecurity with LLMs: A Comprehensive Review of Intrusion Detection Systems and Emerging Application. - Djallel Hamouda; Mohamed Amine Ferrag; Nadjette Benhamida; Hamid Seridi (IAM, 2024)

Revolutionizing intrusion detection in industrial IoT with distributed learning and deep generative techniques. - Djallel Hamouda; Mohamed Amine Ferrag; Nadjette Benhamida; Hamid Seridi; Mohamed Chahine Ghanem (Internet Things, 2024)

From Prompt Injections to Protocol Exploits: Threats in LLM-Powered AI Agents Workflows. - Mohamed Amine Ferrag; Norbert Tihanyi; Djallel Hamouda; Leandros Maglaras; Mérouane Debbah (CoRR, 2025)