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Review
. 2024 Jun 28;24(13):4210.
doi: 10.3390/s24134210.

Recent Advances on Jamming and Spoofing Detection in GNSS

Katarina Radoš  1 , Marta Brkić  2 , Dinko Begušić  1
Affiliations
Review

Recent Advances on Jamming and Spoofing Detection in GNSS

Katarina Radoš et al. Sensors (Basel). .

Abstract

Increased interest in the development and integration of navigation and positioning services into a wide range of receivers makes them susceptible to a variety of security attacks such as Global Navigation Satellite Systems (GNSS) jamming and spoofing attacks. The availability of low-cost devices including software-defined radios (SDRs) provides a wide accessibility of affordable platforms that can be used to perform these attacks. Early detection of jamming and spoofing interferences is essential for mitigation and avoidance of service degradation. For these reasons, the development of efficient detection methods has become an important research topic and a number of effective methods has been reported in the literature. This survey offers the reader a comprehensive and systematic review of methods for detection of GNSS jamming and spoofing interferences. The categorization and classification of selected methods according to specific parameters and features is provided with a focus on recent advances in the field. Although many different detection methods have been reported, significant research efforts toward developing new and more efficient methods remain ongoing. These efforts are driven by the rapid development and increased number of attacks that pose high-security risks. The presented review of GNSS jamming and spoofing detection methods may be used for the selection of the most appropriate solution for specific purposes and constraints and also to provide a reference for future research.

Keywords: GNSS; detection methods; jamming; machine learning models; software-defined radio; spoofing.

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Conflict of interest statement

Author Marta Brkić was employed by the company Ericsson Nikola Tesla. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Main principle of spoofing and jamming attack.
Figure 2
Figure 2
Types of spoofing attack: (a) simplistic, (b) intermediate, (c) sophisticated [37].
Figure 3
Figure 3
Real satellite signal in the capture phase [23].
Figure 4
Figure 4
A spoofed signal exists in the capture phase with a delay of 100 chips [23].
Figure 5
Figure 5
Comparison of C/N0 for different satellites with and without spoofing attack [70].
Figure 6
Figure 6
Time of arrival of real and fake GNSS signal (* denotes that tm is modification time of the real GNSS signals in the spoofer).
Figure 7
Figure 7
Block diagram for spoofing detection using ML methods [15].
Figure 8
Figure 8
(A,B) Confusion matrix for spoofing attack detection in TEXBAT dataset [14].
Figure 9
Figure 9
Expected trend for AGC and C/N0 [77].
Figure 10
Figure 10
FOS DOA estimation for three jammers [96].
See this image and copyright information in PMC

References

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