A survey of spoofer detection techniques via radio frequency fingerprinting with focus on the GNSS pre-correlation sampled data

Wenbo Wang, Ignacio Aguilar Sanchez, Gianluca Caparra, Andy McKeown, Tim Whitworth, Elena Simona Lohan

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
4 Downloads (Pure)

Abstract

Radio frequency fingerprinting (RFF) methods are becoming more and more popular in the context of identifying genuine transmitters and distinguishing them from malicious or non-authorized transmitters, such as spoofers and jammers. RFF approaches have been studied to a moderate-to-great extent in the context of non-GNSS transmitters, such as WiFi, IoT, or cellular transmitters, but they have not yet been addressed much in the context of GNSS transmitters. In addition, the few RFF-related works in GNSS context are based on post-correlation or navigation data and no author has yet addressed the RFF problem in GNSS with pre-correlation data. Moreover, RFF methods in any of the three domains (pre-correlation, post-correlation, or navigation) are still hard to be found in the context of GNSS. The goal of this paper was two-fold: first, to provide a comprehensive survey of the RFF methods applicable in the GNSS context; and secondly, to propose a novel RFF methodology for spoofing detection, with a focus on GNSS pre-correlation data, but also applicable in a wider context. In order to support our proposed methodology, we qualitatively investigated the capability of different methods to be used in the context of pre-correlation sampled GNSS data, and we present a simulation-based example, under ideal noise conditions, of how the feature down selection can be done. We are also pointing out which of the transmitter features are likely to play the biggest roles in the RFF in GNSS, and which features are likely to fail in helping RFF-based spoofing detection.

Original languageEnglish
Article number3012
JournalSensors
Volume21
Issue number9
DOIs
Publication statusPublished - 25 Apr 2021
Publication typeA1 Journal article-refereed

Keywords

  • Classifiers
  • Feature extractors
  • Global navigation satellite systems (GNSS)
  • I/Q (pre-correlation) data
  • Radio frequency fingerprinting (RFF)
  • Spoofing
  • Support vector machines (SVM)

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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