Federated IoT/PC Network Traffic Datasets for FTARL IDS

The dataset comprises CSV files for training and testing an Intrusion Detection System (IDS) that integrates a Transformer‑based Autoencoder, Federated Learning, and Reinforcement‑Learning‑tuned thresholding (FTARL). Contents - IoT training: `iot_devices_dataset_for_traning.csv` (30000 rows) - IoT testing: `iot_devices_dataset_for_testing.csv` (10000 rows) - PC training: `PCs_devices_dataset_for_training.csv` (20005 rows) - PC testing: `PCs_devices_dataset_for_testing.csv` (9883 rows) Schema & Labels See `data_dictionary.csv` for per‑column metadata. Label columns (if present) are listed with distributions in the README. Resolution / Format All files are UTF‑8 CSV with headers. Numeric features are scaled to [0,1] where applicable; sequences were formed over 20‑packet windows during modeling. Intended Use Benchmarking anomaly/attack detection in mixed IoT/PC environments, federated learning experiments, and threshold‑selection research. Suitable for reproduction of the FTARL results. Ethics & Privacy Data contains no PII; IPs/device identifiers are synthetic/anonymized. Third‑party sources (e.g., BoT‑IoT) must be cited by downstream users. Funding INCIBE–USAL SCRIN Project (C068/23), Recovery, Transformation and Resilience Plan (NextGenerationEU).