Identification of Wireless Devices of Users Who Actively Fake Their RF Fingerprints With Artificial Data 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 modelbased approach that allows for identification of wireless devices based on signatures obtained with time domain analysis of a pair of received and decoded signals. Here, we consider strong adversaries who intentionally introduce distortions to the data symbols before the symbols are exposed to the transmitter's inherent nonlinearities, with the intention of faking the signatures of their devices while still allowing for proper data decoding. The method proposed in this work is based on spectral analysis and on the observation that nonlinear components cause in-band 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, we show that wireless devices can be successfully identified even when the users are digitally modifying their data symbols. The utility of the proposed identification approach is demonstrated with simulations based on parameters obtained from the measurements of commercially employed WLAN RF transmitters.Index Terms-radiometric identification, likelihood ratio test, wireless security, process variations 1536-1276 (c)

Physical Layer Authentication for Massive MIMO Systems With Hardware Impairments

“…Recently, physical layer authentication techniques, which exploit the intrinsic and unique features of physical layer for authentication, have received significant attention to enhance the conventional cryptography-based authentication solutions [12]- [23]. So far, extensive research efforts have been devoted to the study of effective physical layer authentication methods for non-massive MIMO systems.…”

“…The basic principle of fingerprinting authentication is that the radio frequency-distinct native attribute (RF-DNA) can hardly be mimicked after being manufactured, such that RF-DNA can be used to uniquely identify devices. The authors in [12] explore the analysis of distortion signals resulting from hardware impairments to identify wireless devices. Carrier frequency offset caused by hardware impairments is investigated to identify wireless transmitters in [13].…”

Specific Emitter Identification Techniques for the Internet of Things

“…This information is then associated with the individual emitter and its platform and weapon system. The SEI designates the individual emitter by discriminating it from all other emitters [1]- [4]. uch features are extracted from the received signal and termed as radio frequency fingerprints.…”

PHY-layer Authentication for IoT Devices Using Frequency Offset Feature

“…The authors of [1] explore minor non-ideal hardware parameters to authenticate a message's transmitter-of-origin by accurately analyzing radio-frequency signals. The authors of [8] show that time domain analysis of a pair of distortion signals caused by imperfections of manufacturing processes can be used to discriminate wireless transmitters. It is proved that using hardware fingerprinting could achieve authentication for transmitters based on transmitterspecific hardware features [16,18].…”