IoT device multi-classification using traffic behavior analysis
Jiaqi Shi, Tieming Liu, Yuanyuan Zhang, Huajuan Ren · 2023
The management of Internet of Things (IoT) devices is becoming increasingly complex. One of the reasons is that IoT device manufacturers are different, and there are different degrees of heterogeneity in service, technology, protocol and other aspects. Accurate identification IoT devices connected to the organization network is an effective way to maintain the organization network security. In this paper, we propose a two-stage machine learning method to identify IoT devices by analyzing network traffic. This method uses the futures of the original traffic advance to classify the types of IoT devices. The method is tested on two public datasets, our method classified IoT devices with an accuracy rate of over 99%.