Cyber—Physical Attack Detection in Water Distribution Systems with Temporal Graph Convolutional Neural Networks

Cyber—Physical Attack Detection in Water Distribution Systems with Temporal Graph Convolutional Neural Networks

Prompt detection of cyber–physical attacks (CPAs) on a water distribution system (WDS) is critical to avoid irreversible damage to the network infrastructure and disruption of water services. However, the complex interdependencies of the water network’s components make CPA detection challenging. To...

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Bibliographic Details
Main Authors: Lydia Tsiami, Christos Makropoulos
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Water
Subjects:
cyber—physical system
cyber—physical attacks
water distribution network
anomaly detection
deep learning
graph neural networks
Online Access:https://www.mdpi.com/2073-4441/13/9/1247

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