Stealthy data integrity attack identification in smart grid networks utilizing deep denoising autoencoder

Smart grids arose as the largest cyber-physical systems with the integration of sophisticated control, computing, and state-of-the-art communications. Like all cyber-physical systems, the smart grids are vulnerable to malicious cyber assaults due to their enormous dependency on communication network...

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Bibliographic Details
Published in:	Heliyon Vol. 10; no. 19; p. e38470
Main Authors:	Kousar, Anila, Ahmed, Saeed, Altamimi, Abdullah, Kim, Su Min, Khan, Zafar A.
Format:	Journal Article
Language:	English
Published:	England Elsevier Ltd 15.10.2024 Elsevier
Subjects:	Cyber assaults Cyber-physical systems Deep denoising autoencoder electric power electrical equipment evolution industry Machine learning Smart grids State estimation support vector machines Cyber-physical systems Smart grids Cyber assaults State estimation Deep denoising autoencoder Machine learning
ISSN:	2405-8440, 2405-8440
Online Access:	Get full text
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