Synthetic GNSS spoofing data generation using field recorded signals

Khan, Abdul Malik; Iqbal, Naveed; Khan, Muhammad Faisal

doi:10.1016/j.mex.2018.10.004

Cited by 6 publications

(5 citation statements)

References 4 publications

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“…The measured threshold ( γ m ) that produces specific P FA is used in the detector. The spoofing period has been considered to be from the onset of spoofing until the end of the dataset, as given by the spoofing delay profile (spoofer delaying/advancing the spoofing signal compared with authentic signal) as described by Humphreys et al (2012) and Lemmenes et al (2016), and synthetic data delay profile as described by Khan et al (2018).…”

Section: Resultsmentioning

confidence: 99%

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Detection of Intermediate Spoofing Attack on Global Navigation Satellite System Receiver Through Slope Based Metrics

et al. 2020

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A spoofing attack on a global navigation satellite system (GNSS) receiver is a threat to a significant community of GNSS users due to the high stakes involved. This paper investigates the use of slope based metrics for the detection of spoofing. The formulation of slope based metrics involves monitoring correlators along with tracking correlators in the receiver's channel, which are slaved to the prompt tracking correlator. In this study, using some candidate metrics, detectors have been formed through the analysis of simulated spoofing attacks. A theoretical variance of each metric has also been calculated as a reference for the threshold. A threshold is estimated using the measured variance from the clean signals, for specific false alarm rate. By using the measured threshold, detectors are formed based on slope metrics. These detectors have been tested using TEXBAT data. The results show that the differential slope metrics have good performance. The results have also been compared with some other techniques of spoofing detection.

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Section: Resultsmentioning

confidence: 99%

“…The spoofing dataset was comprised of the TEXBAT dataset and the synthetic spoofing data (Khan et al, 2018). TEXBAT is the battery of recorded spoofing cases compiled by researchers at the University of Texas, Austin.…”

Section: Introductionmentioning

confidence: 99%

Detection of Intermediate Spoofing Attack on Global Navigation Satellite System Receiver Through Slope Based Metrics

et al. 2020

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“…Also by contrasting 9 and 10, it can be seen that the proposed threshold factor is dependent on the P FA and the pdf of the noise in the correlator output. dataset contains synthetic generated spoofing data 15 and the TEXBAT dataset. 20 The spoofing data are used for calculation of detection rate.…”

Section: Proposed Methods Of Spoofing Detectionmentioning

confidence: 99%

“…The clean data are used for false alarm rate calculation. The spoofing dataset contains synthetic generated spoofing data 15 and the TEXBAT dataset 20 . The spoofing data are used for calculation of detection rate.…”

Section: Datasetmentioning

confidence: 99%

“…The proposed technique calculates a reference ACF value and a fixed threshold factor, making the threshold adjustable according to current estimated noise variance. The proposed SD technique has been validated using spoofing free data from different sources for false alarm rate and Synthetic data 15 and TEXBAT data shared by UT Austin for detection rate. A software‐defined GNSS receiver 16 has been built that has multiple correlator taps in each channel.…”

Section: Introductionmentioning

confidence: 99%

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Global Navigation Satellite Systems Spoofing Detection through measured Autocorrelation Function Shape Distortion

Khan

Ahmad

2021

Satell Commun Network

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Summary With the expansion in Global Navigation Satellite System (GNSS) constellations and emerging applications utilizing GNSS systems, the issue of detection of interference is evolving as a growing concern in the satellite navigation user community. Threats for GNSS users can be classified as unintentional interference, jamming, and spoofing. Spoofing is more harmful among them because the target receiver might not be aware of the attack and, as a consequence, generate misleading position information. Spoofing attacks are classified as simplistic, intermediate, and sophisticated depending on their complexity of implementation. We focused primarily on the detection of intermediate spoofing attacks by measuring shape distortion (SD) through multiple correlators that cover multiple chips around the prompt tracking point. The SD metric compares the measured and typical values of the autocorrelation function and decides on the spoofing using a noise variance based threshold. The proposed SD metric is found to be very effective in detecting the spoofing attack during the pull‐off phase of the attack. The method is verified through simulations, synthetic spoofing data, and the TEXBAT data shared by the University of Texas, Austin. Different formulations of the proposed method are compared to provide an optimal number of correlator taps in each channel.

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Spoofing Signal Generation Based on Manipulation of Code Delay and Doppler Frequency of Authentic GPS Signal

Seo

Jee

Lee

2020

Int. J. Control Autom. Syst.

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Synthetic GNSS spoofing data generation using field recorded signals

Abstract: Graphical abstract

Cited by 6 publications

References 4 publications

Detection of Intermediate Spoofing Attack on Global Navigation Satellite System Receiver Through Slope Based Metrics

Detection of Intermediate Spoofing Attack on Global Navigation Satellite System Receiver Through Slope Based Metrics

Global Navigation Satellite Systems Spoofing Detection through measured Autocorrelation Function Shape Distortion

Spoofing Signal Generation Based on Manipulation of Code Delay and Doppler Frequency of Authentic GPS Signal

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