Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers

Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers

Cyber-attacks have become a significant concern today, particularly in IoT environments where security poses a substantial challenge due to the distributed nature and heterogeneity of protocols. To efficiently detect threats in IoT networks, it is crucial to develop a robust intrusion-detection syst...

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Bibliographic Details
Main Authors: Jawad Ashraf, Ghulam Musa Raza, Byung-Seo Kim, Abdul Wahid, Hye-Young Kim
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Applied Sciences
Subjects:
intrusion detection
anomaly detection
IoT
machine learning
cyber-attacks
network security
Online Access:https://www.mdpi.com/2076-3417/15/4/2043
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