Attack Classification of Imbalanced Intrusion Data for IoT network Using Ensemble Learning-based Deep Neural Network

With the increase in popularity of Internet of Things (IoT) and rise in interconnected devices, the need to foster effective security mechanism to handle vulnerabilities and risks in IoT networks has become evident. Security mechanisms such as Intrusion Detection System (IDS) are designed and deploy...

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Vydané v:	IEEE internet of things journal Ročník 10; číslo 13; s. 1
Hlavní autori:	Thakkar, Ankit, Lohiya, Ritika
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.07.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Artificial neural networks Bagging Class Imbalance Class Weights Classification Classification algorithms Cybersecurity Datasets Deep learning Deep Neural Network Ensemble learning Internet of Things Intrusion detection Intrusion Detection System Intrusion detection systems Machine learning Neural networks Rank tests Training
ISSN:	2327-4662, 2327-4662
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