Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks

Extracting Optimal Number of Features for Machine Learning Models in Multilayer IoT Attacks

The rapid integration of Internet of Things (IoT) systems in various sectors has escalated security risks due to sophisticated multilayer attacks that compromise multiple security layers and lead to significant data loss, personal information theft, financial losses etc. Existing research on multila...

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Bibliographic Details
Main Authors: Badeea Al Sukhni, Soumya K. Manna, Jugal M. Dave, Leishi Zhang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
IoT attacks
multilayer security
feature selection
feature weighting
machine learning
human–machine teaming
Online Access:https://www.mdpi.com/1424-8220/24/24/8121
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