RF fingerprinting of users who actively mask their identities with artificial distortion

Abstract

Variations in the RF chain of radio transmitters caused by imperfections of manufacturing processes can be used as a signature to uniquely associate wireless devices with a given transmission. In our previous work [1], [2] we proposed a model based approach that allows for identification of wireless users with verifiable accuracy via time domain analysis of the signals received from the masquerading users. Here, more sophisticated criminals that, when masquerading, intentionally introduce nonlinear distortions to the data symbols in order to fake their signatures while allowing for proper data decoding, are considered for the first time. The method proposed in this work is based on spectral analysis and on the observation that nonlinear components cause baseband distortion and spectral regrowth of the signal that is dependent on the parameters of the nonlinearity. Hence, by analysis of the in-band distortion of the spectrum as well as the spectral regrowth, the masquerading users can be successfully identified even when they are nonlinearly modifying their data symbols. Using parameters obtained from the measurements of commercially used RF transmitters, we demonstrate the utility of our approach.