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An extensive examination of cyberattacks, cybersecurity, and energy management in smart grid, including new advancements and machine learning

dc.contributor.authorAlhasnawi, Bilal Naji
dc.contributor.authorSadeq, Abdellatif M.
dc.contributor.authorHomod, Raad Z.
dc.contributor.authorHussain, Firas Faeq K.
dc.contributor.authorSoběslav, Vladimír
dc.contributor.authorBureš, Vladimír
dc.date.accessioned2026-10-29T13:35:51Z
dc.date.issued2026
dc.description.abstractOften referred to as next-generation power system, smart grid is regarded as a revolutionary and progressive progression of current power grids. More significantly, smart grid is anticipated to significantly improve distributed intelligence, demand response, and the efficiency and dependability of future power systems with renewable energy sources by integrating cutting-edge computing and communication technology. Because millions of electronic devices are connected by communication networks across vital power facilities, cyber security becomes a crucial concern in addition to the silent aspects of smart grid. This directly affects the dependability of such a vast infrastructure. This study provided a thorough analysis of smart grid cyber security concerns. Then, recent Machine Learning-based detection techniques are summarized. Záznam ve Scopus aktualizován: Corrigendum to “An extensive examination of cyberattacks, cybersecurity, and energy management in smart grid, including new advancements and machine learning”. (Energy Conversion and Management: X (2026) 29, (S2590174525006038), (10.1016/j.ecmx.2025.101471)) EID: 2-s2.0-105027747574eng
dc.formatp. "articlenumber:101471"
dc.identifier.doi10.1016/j.ecmx.2025.101471
dc.identifier.issn2590-1745
dc.identifier.obd43883359
dc.identifier.scopus2-s2.0-105025442199
dc.identifier.urihttps://hdl.handle.net/20.500.12603/3413
dc.identifier.wos001662344500003
dc.language.isoeng
dc.peerreviewedyes
dc.project.IDTS01020105/Aplikace dynamických systémových modelů pro zajištění kybernetické bezpečnosti systémů energetických rozvoden
dc.publicationstatuspostprint
dc.publisherELSEVIER
dc.relation.ispartofEnergy Conversion and Management: X, volume 29, issue: Januaryeng
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S2590174525006038?pes=vor&utm_source=clarivate&getft_integrator=clarivate
dc.rights.accessOpen Access
dc.rights.licenseCC BY-NC-ND 4.0
dc.source.urlhttps://www.sciencedirect.com/science/article/pii/S2590174525006038?pes=vor&utm_source=clarivate&getft_integrator=clarivate
dc.subjectMachine learningeng
dc.subjectCybersecurity mesheng
dc.subjectEnergy managementeng
dc.subjectSmart grideng
dc.subjectAnd false data injectioneng
dc.titleAn extensive examination of cyberattacks, cybersecurity, and energy management in smart grid, including new advancements and machine learningeng
dc.typearticle

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