FELIDS: Federated learning-based intrusion detection system for agricultural Internet of Things

•We propose a federated deep learning-based IDS for mitigating cyberattacks.•We investigate the use of three deep learning classifiers, DNN, CNN, and RNN.•The performance of each classifier is evaluated using three recent real datasets.•The results show that the FELIDS system outperforms the central...

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Vydané v:	Journal of parallel and distributed computing Ročník 165; s. 17 - 31
Hlavní autori:	Friha, Othmane, Ferrag, Mohamed Amine, Shu, Lei, Maglaras, Leandros, Choo, Kim-Kwang Raymond, Nafaa, Mehdi
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.07.2022
Predmet:	Deep learning Federated learning Internet of Things Privacy Security Deep learning Privacy Federated learning Internet of Things Security
ISSN:	0743-7315, 1096-0848
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