Monitoring and Identification of WiFi Devices for Internet of Things Security

Abstract

WiFi is the adhesive in the Internet of Things(IoT), and most wireless devices use WiFi to access the IoT. Monitorization and identification of access WiFi devices are particularly important for the security of the IoT, especially, sensitive areas. In this context, we propose a classification framework for WiFi devices based on their Power Spectral Density(PSD) and Permutation Entropy(PE) of the preamble signal. Four WLAN cards are under test to verify our method. And the K-NN classification was used. The experimental results show that the two methods have a recognition rate of more than 90% with SNR is -5 dB.