IoT device identification based on network traffic

With the rapid development of IoT technology, a large of number complex and diverse IoT devices are widely deployed, which brings new challenges for device identification due to the heterogeneous nature of devices. This paper proposes a network traffic-based IoT device recognition method, in order to solve the high cost problem of traditional recognition methods in the feature extraction process and the potential privacy leakage problem. The proposed method requires only a short period of time in the network traffic data of IoT devices, and extracts the protocol statistical features and flow-level statistical features of this data. It avoids in-depth inspection of packet payloads and reduces the cost of feature extraction effectively. It is demonstrated that the proposed method can improve the performance of device identification while ensuring privacy security through empirical studies on two widely recognized public datasets. The proposed method provides users with a low-cost, high-efficiency IoT device identification solution with strong privacy protection, which promotes wider and more secure application of IoT technology.