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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Bibliographic Details
Main Authors:	Khazaei, J. (Author), Moazeni, F. (Author)
Format:	Article
Language:	English
Published:	MDPI 2022
Subjects:	Cyberattack detection Cyber-attacks deep neural networks Deep neural networks Detection algorithm Detection models False data injection learning-based detection algorithm Learning-based detection algorithm Model-based OPC Multilayer neural networks Neural-networks Random false data injection cyberattack random false data injection cyberattacks Signal detection Water distribution systems water system Water system
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View Fulltext in Publisher

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

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