Enhanced IoT malware detection via robust and scalable federated learning
A decentralised federated learning (FL)-based IoT malware detection framework, evaluated using the recent IoT-23 dataset and systematically assessed in terms of robustness and scalability, highlighting the feasibility of robust and scalable FL-based security systems in real-world IoT deployments.