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GNSS spoofing detection using a fuzzy classifier based on time–frequency analysis of the autocorrelation function

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Abstract

We present a method to detect spoofing attack in Global Navigation Satellite System signals for single antenna receivers based on autocorrelation function distortion analysis in the Time–Frequency (TF) domain. In particular, Discrete Wavelet Transform (DWT) is considered as a TF tool to investigate the correlation taps outputs of the received signal. The statistical properties of the DWT coefficients of the autocorrelation function are processed in a fuzzy classifier as a feature vector to discriminate the presence of a spoofing attack. The detection performance of the method based on TF analysis of the autocorrelation function is verified using the real well-known Texas Spoofing Test Battery (TEXBAT) dataset. The findings demonstrate that the suggested technique for Pfa = 10−2 yields an average detection rate of more than 95% for the TEXBAT different cases, which shows improved detection sensitivity and robustness compared to other conventional and state-of-art methods.

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Data availability

The datasets analyzed during the current study are available at https://rnl-data.ae.utexas.edu/datastore/texbat/. The code generated during and/or analyzed during the current study will be made available on request.

References

  • Aghadadashfam M, Mosavi M, Rezaei M (2020) A new post-correlation anti-jamming technique for GPS receivers. GPS Solut 24:1–16

    Article  Google Scholar 

  • Bardout Y (2011) Authentication of GNSS position: an assessment of spoofing detection methods. In: 24th Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation GNSS ION'11, Portland, OR, pp. 436–446

  • Borhani-Darian P, Li H, Wu P, Closas P (2020) Deep neural network approach to detect GNSS spoofing attacks. In: 33th Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation GNSS ION'20, pp 3241–3252

  • Borio D (2013) PANOVA tests and their application to GNSS spoofing detection. IEEE Trans Aerosp Electron Syst 49:381–394

    Article  Google Scholar 

  • Broumandan A, Jafarnia-Jahromi A, Daneshmand S, Lachapelle G (2015) A network-based GNSS structural interference detection, classification and source localization. In: 28th Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation GNSS ION'15, Tampa, Florida, pp 3358–3369

  • Broumandan A, Jafarnia-Jahromi A, Daneshmand S, Lachapelle G (2016a) Effect of tracking parameters on GNSS receivers vulnerability to spoofing attack. In: 29th Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation GNSS ION'16, Portland, Oregon, pp 3033–3043

  • Broumandan A, Jafarnia-Jahromi A, Daneshmand S, Lachapelle G (2016b) Overview of spatial processing approaches for GNSS structural interference detection and mitigation. Proc IEEE 104:1246–1257

    Article  Google Scholar 

  • Broumandan A, Kennedy S, Schleppe J (2020) Demonstration of a multi-layer spoofing detection implemented in a high precision GNSS receiver. In: 2020 IEEE/ION Position, Location and Navigation Symposium (PLANS), IEEE, Portland, OR, USA, pp 538-547

  • Cavaleri A, Motella B, Pini M, Fantino M (2010) Detection of spoofed GPS signals at code and carrier tracking level. In: 2010 5th ESA Workshop on Satellite Navigation Technologies and European Workshop on GNSS Signals and Signal Processing (NAVITEC), Noordwijk, Netherlands, pp 1-6

  • Ceccato M, Formaggio F, Laurenti N, Tomasin S (2021) Generalized likelihood ratio test for GNSS spoofing detection in devices with IMU. IEEE Trans Inf Forensics Secur 16:3496–3509

    Article  Google Scholar 

  • Clements Z, Ellis P, Psiaki M, Humphreys TE (2022) Geolocation of terrestrial GNSS spoofing signals from low Earth orbit. In: Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation Denver, Colorado, pp 3418–3431

  • Daneshmand S, Jafarnia-Jahromi A, Broumandon A, Lachapelle G (2012) A low-complexity GPS anti-spoofing method using a multi-antenna array. In: 25th Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation GNSS ION'12, Nashville Convention Center, Nashville, Tennessee, pp 1233–1243

  • Dasgupta S, Rahman M, Islam M, Chowdhury M (2022) A sensor fusion-based GNSS spoofing attack detection framework for autonomous vehicles. IEEE Trans Intell Transp Syst 23:23559–23572

    Article  Google Scholar 

  • Duda RO, Hart PE (1973) Pattern classification and scene analysis. Wiley, New York

    Google Scholar 

  • Gross JN, Kilic C, Humphreys TE (2019) Maximum-likelihood power-distortion monitoring for GNSS-signal authentication. IEEE Trans Aerosp Electron Syst 55:469–475

    Article  Google Scholar 

  • Heng L, Work DB, Gao GX (2014) GPS signal authentication from cooperative peers. IEEE Trans Intell Transp Syst 16:1794–1805

    Article  Google Scholar 

  • Humphreys TE (2013) Detection strategy for cryptographic GNSS anti-spoofing. IEEE Trans Aerosp Electron Syst 49:1073–1090

    Article  Google Scholar 

  • Humphreys TE, Ledvina BM, Psiaki ML, O’Hanlon BW, Kintner PM (2008) Assessing the spoofing threat: development of a portable GPS civilian spoofer. In: Proceedings of the 21st international technical meeting of the satellite division of the Institute of Navigation (ION GNSS 2008), September, Savannah, GA, 2314–2325

  • Kaplan ED, Hegarty C (2017) Understanding GPS/GNSS: principles and applications. Artech house.

  • Khan AM, Ahmad A (2022) Global navigation satellite systems spoofing detection through measured autocorrelation function shape distortion. Int J Satell Commun Netw 40:148–156

    Article  Google Scholar 

  • Kuncheva LI (2000) How good are fuzzy if-then classifiers? IEEE Trans Syst, Man, Cybern Part B (cybernetics) 30:501–509

    Article  CAS  Google Scholar 

  • Landry RJ, Mouyon P, Lekaïm D (1998) Interference mitigation in spread spectrum systems by wavelet coefficients thresholding. Eur Trans Telecommun 9:191–202

    Article  Google Scholar 

  • Ledvina BM, Bencze WJ, Galusha B, Miller I (2010) An in-line anti-spoofing device for legacy civil GPS receivers. In: Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation, San Diego, CA, pp 698–712

  • Li J, Zhu X, Ouyang M, Li W, Chen Z, Dai Z (2020) Research on multi-peak detection of small delay spoofing signal. IEEE Access 8:151777–151787

    Article  Google Scholar 

  • Lo S, Chen YH, Reid T, Perkins A, Walter T, Enge P (2017) Keynote: the benefits of low cost accelerometers for GNSS anti-spoofing. In: Proceedings of the ION 2017 Pacific PNT Meeting, Honolulu, Hawaii, pp 775–796

  • McMilin E, De Lorenzo DS, Walter T, Lee TH, Enge P (2014) Single antenna GPS spoof detection that is simple, static, instantaneous and backwards compatible for aerial applications. In: 27th Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation GNSS ION'14, Tampa, Florida, pp 2233–2242

  • Mosavi MR, Pashaian M, Rezaei MJ, Mohammadi K (2015) Jamming mitigation in global positioning system receivers using wavelet packet coefficients thresholding. IET Signal Proc 9:457–464

    Article  Google Scholar 

  • Mubarak OM, Dempster A (2007) Carrier phase analysis to mitigate multipath effect. IGNSS2007 Symp. on GPS/GNSS, Sydney, Australia

  • Mubarak OM, Dempster AG (2010) Analysis of early late phase in single-and dual-frequency GPS receivers for multipath detection. GPS Solut 14:381–388

    Article  Google Scholar 

  • Munoz Diaz E, Rubio Hernan JM, Jurado Romero F, Karite A, Vervisch-Picois A, Samama N (2023) Advanced smartphone-based identification of transport modes: resilience under GNSS-based attacks. Future Transp 3:568–583

    Article  Google Scholar 

  • Orouji N, Mosavi M (2021) A multi-layer perceptron neural network to mitigate the interference of time synchronization attacks in stationary GPS receivers. GPS Solut 25:1–15

    Article  Google Scholar 

  • Phelts RE (2001) Multicorrelator techniques for robust mitigation of threats to GPS signal quality. Stanford University.

  • Pirsiavash A, Broumandan A, Lachapelle G (2016) Two-dimensional signal quality monitoring for spoofing detection. In: Proceedings of the ESA/ESTEC NAVITEC 2016 Conference, Noordwijk, Netherlands, pp 14–16

  • Psiaki ML, Humphreys TE (2016) GNSS spoofing and detection. Proc IEEE 104:1258–1270

    Article  Google Scholar 

  • Psiaki M, Humphreys T (2020) Civilian Gnss spoofing, detection, and recovery. Position, navigation, and timing technologies in the 21st Century: Integrated Satellite Navigation, Sensor Systems, and Civil Applications 1:655-680

  • Psiaki ML, O’Hanlon BW, Bhatti JA, Shepard DP, Humphreys TE (2013a) GPS spoofing detection via dual-receiver correlation of military signals. IEEE Trans Aerosp Electron Syst 49:2250–2267

    Article  Google Scholar 

  • Psiaki ML, Powell SP, O'Hanlon BW (2013b) GNSS spoofing detection using high-frequency antenna motion and carrier-phase data. In: 26th Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation GNSS ION'13, Nashville, Tennessee, pp 2949–2991

  • Rothmaier F, Chen YH, Lo S, Walter T (2021) GNSS spoofing detection through spatial processing. Navigation 68:243–258

    Article  Google Scholar 

  • Roy D, Mukherjee T, Riden A, Paquet J, Pasiliao E, Blasch E (2022) GANSAT: a GAN and satellite constellation fingerprint-based framework for GPS spoof-detection and location estimation in GPS deprived environment. IEEE Access 10:45485–45507

    Article  Google Scholar 

  • Schmidt E, Gatsis N, Akopian D (2020) A GPS spoofing detection and classification correlator-based technique using the LASSO. IEEE Trans Aerosp Electron Syst 56:4224–4237

    Article  Google Scholar 

  • Shang S, Li H, Peng C, Lu M (2020) A novel method for GNSS meaconer localization based on a space–time double-difference model. IEEE Trans Aerosp Electron Syst 56(5):3432–3449

    Article  Google Scholar 

  • Sun C, Cheong JW, Dempster AG, Zhao H, Bai L, Feng W (2021) Robust spoofing detection for GNSS instrumentation using Q-channel signal quality monitoring metric. IEEE Trans Instrum Meas 70:1–15

    Google Scholar 

  • Tanil C, Khanafseh S, Pervan B (2015) GNSS spoofing attack detection using aircraft autopilot response to deceptive trajectory. In: 28th Int. Tech. Meeting of the Satellite Division of the U.S. Inst. of Navigation GNSS ION'15, Tampa, Florida, pp 3345–3357

  • Tohidi S, Mosavi M (2023) Fuzzy-based acquisition in GPS receivers for spoofing mitigation. Microprocess Microsyst 101:104886

    Article  Google Scholar 

  • Vagle N, Broumandan A, Lachapelle G (2018) Multiantenna GNSS and inertial sensors/odometer coupling for robust vehicular navigation. IEEE Internet Things J 5:4816–4828

    Article  Google Scholar 

  • White NA, Maybeck PS, DeVilbiss SL (1998) Detection of interference/jamming and spoofing in a DGPS-aided inertial system. IEEE Trans Aerosp Electron Syst 34:1208–1217

    Article  Google Scholar 

  • Wu Z, Liu R, Cao H (2019) ECDSA-based message authentication scheme for BeiDou-II navigation satellite system. IEEE Trans Aerosp Electron Syst 55(4):1666–1682

    Article  Google Scholar 

  • Zadeh LA (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst 1:3–28

    Article  Google Scholar 

  • Zhou W, Lv Z, Deng X, Ke Y (2022) A new induced GNSS spoofing detection method based on weighted second-order central moment. IEEE Sens J 22:12064–12078

    Article  Google Scholar 

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Acknowledgements

This work is based upon research supported by Iran National Science Foundation (INSF) and under project No.4023276.

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The authors did not receive any funding for this study.

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  1. Department of Electrical Engineering, Iran University of Science and Technology, Narmak, Tehran, 16846-13114, Iran

    S. Tohidi & M. R. Mosavi

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  1. S. Tohidi
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This work was carried out in close collaboration among authors. The authors have contributed equally to the completion of the work.

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Correspondence to M. R. Mosavi.

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The authors declare that this manuscript “GNSS spoofing detection using a fuzzy classifier based on time–frequency analysis of the autocorrelation function” is original, has not been full or partly published before and is not currently being considered for publication elsewhere. The authors confirm that there are no other persons who satisfied the criteria for authorship but are not listed. The authors have no competing interests to declare that are relevant to the content of this article.

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Tohidi, S., Mosavi, M.R. GNSS spoofing detection using a fuzzy classifier based on time–frequency analysis of the autocorrelation function. GPS Solut 28, 146 (2024). https://doi.org/10.1007/s10291-024-01674-y

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