Beyond data sharing: enhancing IoT intrusion detection with blockchain-enabled federated learning
Raj Mani Shukla
Federated learning (FL) is a decentralized machine learning (ML) approach that can be used for intrusion detection in Internet of Things (IoT) devices. It involves the local training of AI models and their aggregation at a central server. This methodology eliminates the need for data sharing between IoT devices while fostering collaborative model improvement. Nonetheless, concerns arise from the lack of transparency regarding the shared local models and the aggregation techniques employed. This