Specific Emitter Identification for WiFi Devices via Bezier Curve Fitting

Abstract

A well-done specific emitter identification (SEI) method via radio frequency (RF) fingerprint is a physical-layer-based approach for wireless communication network security. In this paper, we propose an efficient SEI method based on the spectrum trace skeleton and Bezier curve fitting. The method utilizes the original spectrum trace directly instead of collecting and processing time-domain data. The control points obtained by Bezier curve fitting with the spectrum trace skeleton are selected to act as the new features for identification. It can retain the information of the spectrum trace to the most extent while reducing feature dimension. It is proved that the proposed method has effective and reliable performance for identifying WiFi devices. The total identification accuracy can reach 98.4% even at a low signal-to-noise ratio (SNR). Furthermore, compared with time-domain methods, the proposed method has a lower feature dimension and saves running time and storage space.