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This repository contains the implementation of a cybersecurity framework based on Auto-Encoders for detecting False Data Injection (FDI) attacks in smart water distribution systems.

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Moazeni-s-Concise-Lab/FDIA-Detection-using-Autoencoders

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A Holistic Cybersecurity Framework against False Data Injection Attacks in Smart Water Distribution Systems

πŸ“„ Published in: ASCE-EWRI 2024 Proceedings
πŸ† Award: Second Best Paper – Graduate Paper Competition

πŸ‘©β€πŸ’» Authors

πŸ› Department of Civil and Environmental Engineering

Lehigh University, Pennsylvania, USA


This repository contains the implementation of a cybersecurity framework based on Auto-Encoders for detecting False Data Injection (FDI) attacks in smart water distribution systems. doi link: https://doi.org/10.1061/9780784485477.096

Β© 2024 Nazia Raza & Farrah Moazeni

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This repository contains the implementation of a cybersecurity framework based on Auto-Encoders for detecting False Data Injection (FDI) attacks in smart water distribution systems.

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