Boosting Cyberattack Detection Using Binary Metaheuristics With Deep Learning on Cyber-Physical System Environment

The swift advancement of cyber-physical systems (CPSs) across sectors such as healthcare, transportation, critical infrastructure, and energy enhances the crucial requirement for robust cybersecurity measures to protect these systems from cyberattacks. The cyber-physical method is a hybrid of cyber...

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Vydané v:	IEEE access Ročník 13; s. 11280 - 11294
Hlavní autori:	Al Mazroa, Alanoud, Albogamy, Fahad R., Khairi Ishak, Mohamad, Mostafa, Samih M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Access control Accuracy Adaptation models Algorithms Archimedes optimization algorithm Communications traffic Computational modeling Critical infrastructure Cyber-physical systems Cyberattack cyberattack detection Cybersecurity Data models Datasets Deep learning Empirical analysis Feature extraction Heuristic methods Intrusion detection systems Machine learning metaheuristics Neural networks Optimization Security
ISSN:	2169-3536, 2169-3536
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