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).