Implementation of USAD (UnSupervised Anomaly Detection on multivariate time series) in PyTorch Lightning.

Original implementation by: Francesco Galati. Original code can be found in: USAD.

To start, first download the data.

Data can be found in:

• Normal data: SWaT Dataset Normal
• Attack data: SWaT Dataset Attack

After downloading them put them in data/raw.

dvc exp run

All the parameters (for example epoch size) can be found in params.yaml.

• pytorch 1.9
• dvc
• pytorch-lighting
• python 3.8

If you use this software, please cite the following paper as appropriate:

Audibert, J., Michiardi, P., Guyard, F., Marti, S., Zuluaga, M. A. (2020).
USAD : UnSupervised Anomaly Detection on multivariate time series.
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, August 23-27, 2020