mirzaakhi/UL-WSN-DDoS-Attack-H-IoT2023: Initial public release

This dataset and preprocessing notebook support the poster paper presented at the 12th IEEE International Conference on Healthcare Informatics (IEEE ICHI 2024), held in Orlando, Florida, USA: "Time Series Anomaly Detection with CNN for Environmental Sensors in Healthcare-IoT" (IEEE ICHI 2024) The dataset captures Distributed Denial-of-Service (DDoS) attacks in a Wireless Sensor Network (WSN) deployed within a Healthcare-IoT (H-IoT) environment. It is generated using the Cooja IoT network simulator, with environmental sensors primarily monitoring room temperature and humidity. The final dataset includes engineered features used to train a CNN-based anomaly detection model. If you use this dataset or the preprocessing notebook in your research or applications, please cite the following paper. This dataset is shared under the [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) license. Plain Text: M. A. Khatun, M. Bhattacharya, C. Eising and L. L. Dhirani, "Time Series Anomaly Detection with CNN for Environmental Sensors in Healthcare-IoT,"* 2024 IEEE 12th International Conference on Healthcare Informatics (ICHI), Orlando, FL, USA, 2024, pp. 522–524, doi: [10.1109/ICHI61247.2024.00075](https://doi.org/10.1109/ICHI61247.2024.00075) 🔗 [View paper on IEEE Xplore](https://ieeexplore.ieee.org/abstract/document/10628718)