GNSS Spoofing Jamming Detection Based on Generative Adversarial Network

Li, Junzhi; Ouyang, Mingjun; Li, Wanqing; Chen, Zhengkun; Fu, Qun

doi:10.1109/jsen.2021.3105404

Cited by 39 publications

(20 citation statements)

References 23 publications

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“…That is, (9) shall meet the following constraints: (11) where According to (9), the spoofer calculates the measurement deviation required for spoofing according to the system deviation of the GNSS/IMU required for a single epoch and estimated gain matrix K i . The position constraint in (10) is taken as the objective function of the product of gain matrix K i and measured value deviation; (11) is taken as the constraints to solve the optimal measured value deviation.…”

Section: Avoiding Parameter Rationality Checkmentioning

confidence: 99%

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A Slowly Varying Spoofing Algorithm on Loosely Coupled GNSS/IMU Avoiding Multiple Anti-Spoofing Techniques

Gao

2022

Sensors

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When satellite navigation terminal sensors encounter malicious signal spoofing or interference, if attention is not paid to improving their anti-spoofing ability, the performance of the sensors will be seriously affected. The global navigation satellite system (GNSS) spoofing has gradually become a research hotspot of the jammer because of its great harm and high concealment. In the face of more and more sensors coupling GNSS and inertial measurement unit (IMU) to varying degrees and configuring a variety of anti-spoofing techniques to effectively detect spoofing, even if the spoofer intends to gradually pull the positioning results, if the spoofing strategy is unreasonable, the parameters of the coupled filter output and spoofing observation measurement will lose their rationality, which will lead to the spoofing being detected. To solve the above problems, in order to effectively counter the non-cooperative target sensors of assembling loosely coupled GNSS/IMU using GNSS spoofing, based on the analysis of the influence mechanism of spoofing on the positioning of loosely coupled GNSS/IMU, a slowly varying spoofing algorithm to avoid loosely coupled GNSS/IMU with multiple anti-spoofing techniques is proposed in this paper, and a measurement deviation determination method to avoid multiple anti-spoofing techniques is proposed, which can gradually pull the positioning results of the coupled system and successfully avoid the detection of anti-spoofing techniques of innovation sequence monitoring and a rationality check on parameters. Simulation experimental results show that the proposed algorithm gradually changes the positioning of loosely coupled GNSS/IMU, the north and east displacements achieve the purpose of spoofing, and error with expected offset is −0.2 m and 2.3 m, respectively. Down displacement also basically achieves the purpose of spoofing, and error with the expected offset is 13.2 m. At the same time, the spoofer avoids the detection of multiple anti-spoofing techniques, does not trigger the system alarm, and realizes the purpose of spoofing; thus, the effectiveness and high concealment of the spoofing algorithm are verified.

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Section: Avoiding Parameter Rationality Checkmentioning

confidence: 99%

“…At present, there are many spoofing detection methods based on the single GNSS module [9,10], but any method is difficult when dealing with all spoofing methods [11]. In GNSS and the inertial measurement unit (IMU) system, IMU constantly uses measurement information of GNSS to correct its own error.…”

Section: Introductionmentioning

confidence: 99%

A Slowly Varying Spoofing Algorithm on Loosely Coupled GNSS/IMU Avoiding Multiple Anti-Spoofing Techniques

Gao

2022

Sensors

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“…Countermeasures for jamming and spoofing threats have been extensively discussed and proposed in the literature [11], and, as far as spoofing is concerned and targeted by our test campaign, a brief review will be covered in this article. As recalled later on, many of the proposed spoofing detection techniques require the implementation of sophisticated algorithms that need to have access to the low-level signal processing stages of the GNSS receiver in order to be effective against simplistic to advanced spoofing attacks [12]- [17].…”

Section: Introductionmentioning

confidence: 99%

Improving GNSS Spoofing Awareness in Smartphones via Statistical Processing of Raw Measurements

Rustamov

Minetto

Dovis

2023

IEEE Open J. Commun. Soc.

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Due to the low received power of Global Navigation Satellite Signals (GNSS), the performance of GNSS receivers can be disrupted by anthropogenic radio frequency interferences, with intentional jamming and spoofing activities being among the most critical threats. It is reported in the literature that modern, GNSS-equipped Android smartphones are generally resistant to simplistic spoofing, and many recent contributions support such a biased belief. In this paper, we present the results of a test campaign designed to further stress the resilience of such devices to simplistic spoofing attacks and highlight their actual vulnerability. We then propose an effective spoofing detection technique, that exploits the spatial and temporal correlation of the counterfeit signals by leveraging the statistical analysis of raw GNSS measurements. By not requiring access to the low signal processing level of the GNSS receiver, the proposed solution applies to any device embedding a GNSS receiver that provides raw GNSS measurements, such as current Android smartphones. Vulnerability analysis and validation of the proposed technique were conducted in a controlled environment by transmitting realistic, counterfeit Global Positioning System L1/CA navigation signals to a variety of Android smartphones embedding also different GNSS chipsets. We show that, under proper conditions, the devices were vulnerable to the attacks and that the effects were visible through their raw measurements, i.e., Carrier-to-noise ratio (C/N 0 ), pseudo-range measurements, and position estimates. In particular, the study demonstrates that cross-correlation between the C/N 0 time series provided by each device for different GNSS satellites increases under spoofing conditions, thus constituting an effective metric to detect the attack within a few seconds.

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“…These methods include received power monitoring (RPM) [9], signal quality monitoring (SQM) [10], [11], carrier-to-noise ratio (C/N0) monitoring [12], and carrier Doppler monitoring [13], [14]. Techniques based on artificial neural networks (NNs) are another recent novel approach for detecting spoofing attacks [15], [16]. In [16], a generative adversarial network was proposed for spoofing detection based on the characteristics of the counterfeit signals in the acquisition results.…”

Section: Introductionmentioning

confidence: 99%

“…Techniques based on artificial neural networks (NNs) are another recent novel approach for detecting spoofing attacks [15], [16]. In [16], a generative adversarial network was proposed for spoofing detection based on the characteristics of the counterfeit signals in the acquisition results. However, the abovementioned techniques can only detect counterfeit attacks, but cannot mitigate spoofing.…”

Section: Introductionmentioning

confidence: 99%

Mitigation of GNSS Time Synchronization Attacks in a Multicorrelator Receiver

et al. 2022

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Global navigation satellite systems (GNSSs) are widely used in various fields to provide highprecision timing. However, their low signal power and open signal structure render GNSS receivers vulnerable to time synchronization attacks (TSAs). In this study, we propose a novel single-antenna-based TSA mitigation algorithm. First, a multicorrelator estimator was adopted to calculate the parameters of the authentic and counterfeit signals. Then, the predicted pseudorange was derived for spoofing validation, and the counterfeit signals were subtracted. Finally, a robust extended Kalman filter was adopted to resist gross errors in the estimation results. A series of Monte Carlo simulations were conducted to evaluate the performance of the proposed method with different relative delays and power advantages of the spoofing signals. The Texas Spoofing Test Battery spoofing datasets were used in the experiments to verify the effectiveness of the proposed algorithm. The results indicated that the timing errors decreased from 2.0 µs (600 m) to 53.4 ns (16 m), and the spoofing signals were considerably mitigated. The proposed anti-spoofing algorithm can ensure the availability of GNSS timing under TSAs and only requires a single antenna, greatly simplifying the GNSS receiver installation and reducing costs.INDEX TERMS Global navigation satellite system (GNSS), multicorrelator receiver, predicted pseudorange, spoofing mitigation, time-synchronization attack (TSA)

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GNSS Spoofing Jamming Detection Based on Generative Adversarial Network

Cited by 39 publications

References 23 publications

A Slowly Varying Spoofing Algorithm on Loosely Coupled GNSS/IMU Avoiding Multiple Anti-Spoofing Techniques

A Slowly Varying Spoofing Algorithm on Loosely Coupled GNSS/IMU Avoiding Multiple Anti-Spoofing Techniques

Improving GNSS Spoofing Awareness in Smartphones via Statistical Processing of Raw Measurements

Mitigation of GNSS Time Synchronization Attacks in a Multicorrelator Receiver

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