A Blockchain-Integrated Federated Learning Model and Autoencoder-Based Feature Reduction for Improving IoT Intrusion Detection
The study proposes a secure and adaptive intrusion detection model using Federated Learning and Blockchain, augmented with autoencoder-based feature reduction, showing that combining FL, blockchain, and deep feature extraction offers a viable and secure solution for intrusion detection systems in IoT.