I am a researcher and faculty member at the intersection of Edge AI Security, Hierarchical Federated Learning, and Assistive Human-Machine Intelligence. My PhD (Newcastle University, 2025) focused on adversarial attack analysis and modular detection for distributed IoT systems. I am driven by one question — how do we make AI systems secure, private, and trustworthy for the humans who depend on them?
Newcastle University, United Kingdom
Security of artificial intelligence, Edge and distributed AI systems
University of Essex, United Kingdom
Imam Abdulrahman Bin Faisal University, Saudi Arabia
My research bridges Edge AI Security and Assistive Human-Machine Intelligence. From securing hierarchical federated learning systems against adversarial attacks, to building modular detection for IoT networks, to applying brain-computer interfaces for human communication — every thread connects to one goal: making AI systems safe for real people in the real world.
Adversarial attack analysis and discrimination scoring of client models at the edge server in distributed AI systems.
Lightweight, edge-deployable detection for early-stage botnet and intrusion threats in constrained IoT environments.
Motor imagery signal processing and ML for sign language recognition — bridging neural signals and human communication.
Applying secure, privacy-preserving edge AI to hearing assistive devices — ensuring neural data remains protected.
End-to-end security assessment for hierarchical federated deep learning systems deployed at scale in critical infrastructure.
Security and privacy for AI systems in large-scale IoT deployments — directly aligned with Saudi Arabia's Vision 2030.
I welcome collaboration on Edge AI security, federated learning, IoT systems, and assistive AI research. Whether you are a researcher, industry partner, or student — feel free to reach out.
Dalqattan@tvtc.gov.sa