Efficient traffic-based IoT device identification using a feature selection approach with Lévy flight-based sine chaotic sub-swarm binary honey badger algorithm

Boxiong Wang, Hui Kang, Geng Sun, Jiahui Li

Abstract: Highlights•A traffic-based IoT device identification model including wrapper feature selection is proposed.•An improved binary honey badger algorithm for IoT traffic datasets (denoted as LS2-BHBA) is designed.•A wrapper feature selection method based on LS2-BHBA is designed.•Extensive experiments are conducted on three real-world datasets to demonstrate the effectiveness and generalization of the proposed method.•The results are tested statistically and the feasibility of using decomposition methods is analyzed.