Deep Learning-Based Cyber–Physical Feature Fusion for Anomaly Detection in Industrial Control Systems

Deep Learning-Based Cyber–Physical Feature Fusion for Anomaly Detection in Industrial Control Systems

In this paper, we propose an unsupervised anomaly detection method based on the Autoencoder with Long Short-Term Memory (LSTM-Autoencoder) network and Generative Adversarial Network (GAN) to detect anomalies in industrial control system (ICS) using cyber–physical fusion features. This method improve...

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Bibliographic Details
Main Authors: Yan Du, Yuanyuan Huang, Guogen Wan, Peilin He
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Mathematics
Subjects:
deep learning
anomaly detection
cyber–physical
industrial control systems
Online Access:https://www.mdpi.com/2227-7390/10/22/4373

Internet

https://www.mdpi.com/2227-7390/10/22/4373

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