A hybrid approach for efficient feature selection in anomaly intrusion detection for IoT networks
Aya G. Ayad,
Nehal A. Sakr,
Noha A. Hikal
Abstract:The exponential growth of Internet of Things (IoT) devices underscores the need for robust security measures against cyber-attacks. Extensive research in the IoT security community has centered on effective traffic detection models, with a particular focus on anomaly intrusion detection systems (AIDS). This paper specifically addresses the preprocessing stage for IoT datasets and feature selection approaches to reduce the complexity of the data. The goal is to develop an efficient AIDS that strikes a balance b… Show more
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