Edge-IIoTset: A New Comprehensive Realistic Cyber Security Dataset of IoT and IIoT Applications for Centralized and Federated Learning

In this paper, we propose a new comprehensive realistic cyber security dataset of IoT and IIoT applications, called Edge-IIoTset, which can be used by machine learning-based intrusion detection systems in two different modes, namely, centralized and federated learning. Specifically, the dataset has...

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Vydané v:	IEEE access Ročník 10; s. 40281 - 40306
Hlavní autori:	Ferrag, Mohamed Amine, Friha, Othmane, Hamouda, Djallel, Maglaras, Leandros, Janicke, Helge
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Communications traffic Computer crime Computer security Cybersecurity Cybersecurity applications Data analysis Datasets Deep learning edge {computing} Feature extraction Federated learning Heart rate Industrial Internet of Things IoT datasets Machine learning Malware Moisture effects Protocols Security Sensors Soil moisture Temperature sensors Water levels
ISSN:	2169-3536, 2169-3536
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