An extensive examination of cyberattacks, cybersecurity, and energy management in smart grid, including new advancements and machine learning
| dc.contributor.author | Alhasnawi, Bilal Naji | |
| dc.contributor.author | Sadeq, Abdellatif M. | |
| dc.contributor.author | Homod, Raad Z. | |
| dc.contributor.author | Hussain, Firas Faeq K. | |
| dc.contributor.author | Soběslav, Vladimír | |
| dc.contributor.author | Bureš, Vladimír | |
| dc.date.accessioned | 2026-10-29T13:35:51Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | Often 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-s2.0-105027747574 | eng |
| dc.format | p. "articlenumber:101471" | |
| dc.identifier.doi | 10.1016/j.ecmx.2025.101471 | |
| dc.identifier.issn | 2590-1745 | |
| dc.identifier.obd | 43883359 | |
| dc.identifier.scopus | 2-s2.0-105025442199 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12603/3413 | |
| dc.identifier.wos | 001662344500003 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.project.ID | TS01020105/Aplikace dynamických systémových modelů pro zajištění kybernetické bezpečnosti systémů energetických rozvoden | |
| dc.publicationstatus | postprint | |
| dc.publisher | ELSEVIER | |
| dc.relation.ispartof | Energy Conversion and Management: X, volume 29, issue: January | eng |
| dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S2590174525006038?pes=vor&utm_source=clarivate&getft_integrator=clarivate | |
| dc.rights.access | Open Access | |
| dc.rights.license | CC BY-NC-ND 4.0 | |
| dc.source.url | https://www.sciencedirect.com/science/article/pii/S2590174525006038?pes=vor&utm_source=clarivate&getft_integrator=clarivate | |
| dc.subject | Machine learning | eng |
| dc.subject | Cybersecurity mesh | eng |
| dc.subject | Energy management | eng |
| dc.subject | Smart grid | eng |
| dc.subject | And false data injection | eng |
| dc.title | An extensive examination of cyberattacks, cybersecurity, and energy management in smart grid, including new advancements and machine learning | eng |
| dc.type | article |