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Detection of Random False Data Injection Cyberattacks in Smart Water Systems Using Optimized Deep Neural Networks

A cyberattack detection model based on supervised deep neural network is proposed to identify random false data injection (FDI) on the tank’s level measurements of a water distribution system. The architecture of the neural network, as well as various hyper-parameters, is modified and tuned to acqui...

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Principais autores: Faegheh Moazeni, Javad Khazaei
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2022-07-01
Serier:Energies
Fag:
random false data injection cyberattacks
deep neural networks
learning-based detection algorithm
water system
Online adgang:https://www.mdpi.com/1996-1073/15/13/4832
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