Enhanced Intrusion Detection with LSTM-Based Model, Feature Selection, and SMOTE for Imbalanced Data

This study introduces a sophisticated intrusion detection system (IDS) that has been specifically developed for internet of things (IoT) networks. By utilizing the capabilities of long short-term memory (LSTM), a deep learning model renowned for its proficiency in modeling sequential data, our intru...

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Autors principals:	Hussein Ridha Sayegh, Wang Dong, Ali Mansour Al-madani
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-01-01
Col·lecció:	Applied Sciences
Matèries:	cybersecurity intrusion detection system (IDS) long short-term memory (LSTM) data imbalance
Accés en línia:	https://www.mdpi.com/2076-3417/14/2/479
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