Slade-99/IoMT_FL: v1.0 – Initial Release of IoMT Federated Learning Framework

Initial Research Release (v1.0) This release provides the implementation of the federated learning framework used in our research on intrusion detection for Internet of Medical Things (IoMT) environments. The repository includes the revised implementation used for all experimental evaluations described in the associated research work. Key Components Federated learning training framework Privacy-preserving and lightweight encryption mechanisms Experimental notebooks for model training and evaluation Implementation for intrusion detection experiments on IoMT datasets Repository Structure Revised_Implementation/ – Main implementation used in the experiments Previous_Implementation/ – Deprecated prototype retained for reference Jupyter notebooks containing individual experiment workflows Datasets Experiments utilize publicly available IoT/IoMT cybersecurity datasets including: CICIoMT2024 TON_IoT Datasets must be downloaded separately before running the experiments. Reproducibility Dependencies required to reproduce the experiments are provided in: requirements.txt Related Research This code accompanies the research work on Trust-Aware Federated Intrusion Detection Framework for IoMT Environments. License This repository is provided for academic research purposes.