About Using of Autoencoders for Anomaly Detection in Cyber-physical Systems

Authors

DOI:

https://doi.org/10.17072/1993-0550-2022-4-89-94

Keywords:

deep learning, autoencoders, anomaly detection in technological process, time series

Abstract

Using of autoencoder for anomaly detection in cyberphysical systems was investigated. Some popular methods and datasets were observed. Suggested approach was applied to data and task from SWAT dataset. Achieved results was compared with existing baselines.

References

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P. Malhotra, L. Vig, G. Shroff, and P. Agarwal. Long Short Term Memory Networks for Anomaly Detection in Time Series, in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 2015.

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Описание датасета SWAT от Сингапурского университета технологии и дизайна (SUTD). URL: https://www.researchgate.net/

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Датасет SKAB (Skoltech Anomaly Benchmark). URL: https://paperswithcode. com/dataset/skab (дата обращения: 01.11.2022).

Библиотека Orion для распознавания аномалий https://pypi.org/project/orion-ml/.

Published

2022-12-22

How to Cite

Chernyshov Ю. Ю. (2022). About Using of Autoencoders for Anomaly Detection in Cyber-physical Systems. BULLETIN OF PERM UNIVERSITY. MATHEMATICS. MECHANICS. COMPUTER SCIENCE, (4 (59), 89–94. https://doi.org/10.17072/1993-0550-2022-4-89-94