Abstract: Highlights•A comparative study of IoT datasets used for different Ml model training;•Comparison of attacks, datasets and algorithms for protecting IoT devices;•Proposing a taxonomy with respect to various IoT attacks;•Identification of potential features to detect different attack types;•Research directions for building a robust IoT intrusion detection system.
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