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Session A5: Aviation and Aeronautics

Identification and Analysis of GNSS Spoofing Using ADS-B Data
Benoit Figuet, Okuary Osechas, Michael Felux, ZHAW
Date/Time: Friday, Sep. 20, 11:48 a.m.

Aviation relies on Global Navigation Satellite Systems (GNSS), both for navigation services and for dependent surveillance. GNSS is firmly established as the primary means of navigation for most phases of flight. Air Traffic Management (ATM) services, on the other hand, leverage the flexibility and accuracy of Automatic Dependent Surveillance Broadcast (ADS-B) to inform their situational awareness about the airspace. Unfortunately, the industry has faced significant challenges due to large-scale radio frequency interference (RFI) events in recent years. Notably, localized events near Denver and Dallas airports in 2022 (Dacus et al., 2023; Liu et al. 2024), and widespread disturbances in the Eastern Mediterranean, Baltic States, Russia, Southeastern Europe, across the Black Sea into Türkiye, and Iraq have been documented (Berz et al. 2016, Osechas et al., 2022, Felux et al. 2023, Fol and Felux 2022). Until late 2023, civil aviation's struggle with RFI was predominantly due to GNSS signal jamming. Various studies have explored and detailed the consequences of jamming on aircraft systems, ADS-B data integrity, and the broader implications for airspace safety and air traffic control (ATC) operations.
More recently, an increasing number of reports suggest that civil air traffic is also being compromised by GNSS spoofing, which could cause even more severe disruptions. Our analysis spans from October 2023 to February 2024, utilizing ADS-B data from the OpenSky Network (Schäfer et al. 2014). The focus area of our study is a geographical rectangle extending from Egypt to India and reaching up to Finland, encompassing regions such as the Black Sea and the Eastern Mediterranean where spoofing activities have been previously reported and observed.
During GNSS spoofing attacks, the simultaneous reporting of identical positions by multiple aircraft emerged as a key indicator. Our analysis focused on detecting such events by examining instances of anomalously similar aircraft positions on the horizontal plane. We applied unsupervised machine learning algorithms to discern clusters based on time and position, facilitating the successful identification of over 30 spoofing incidents, predominantly in Lebanon, Israel, Egypt, Crimea, and Russia. This examination unveiled three distinct spoofing techniques: static location spoofing, circle spoofing, and movement simulation along an airport runway.
Further examination of these occurrences revealed that not only latitude and longitude data were manipulated, but geometric altitude and ground speed indicators were also altered. A notable finding was that, upon spoofing, the reported geometric altitude of an aircraft is precisely 3,150 feet lower than its genuine barometric altitude.
By providing a detailed analysis of GNSS spoofing events and their characteristics, our study lays the groundwork for the aviation community to develop robust identification and mitigation methods, paving the way for enhanced security measures against this increasingly sophisticated threat.
Berz, G., Barret, P., Disselkoen, B., Richard, M., Bleeker, O., Rocchia, V., ... & Bigham, T. (2016, September). Interference Localization using a Controlled Radiation Pattern Antenna (CRPA). In Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016) (pp. 3053-3062).
Dacus, M., Liu, Z., Lo, S., & Walter, T. (2023, September). Approximating Regional GNSS Interference Sources as a Convex Optimization Problem Using ADS-B Data. In Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023) (pp. 815-823).
Felux, Michael, Figuet, Benoit, Waltert, Manuel, Fol, Patric, Strohmeier, Martin, Olive, Xavier, "Analysis of GNSS disruptions in European Airspace," Proceedings of the 2023 International Technical Meeting of The Institute of Navigation, Long Beach, California, January 2023, pp. 315-326.
Figuet, Benoit, Manuel Waltert, Michael Felux, and Xavier Olive. 2022. "GNSS Jamming and Its Effect on Air Traffic in Eastern Europe" Engineering Proceedings 28, no. 1: 12. https://doi.org/10.3390/engproc2022028012
Fol, P., & Felux, M. (2022). Identification and operational impact analysis of GNSS RFI based on flight crew reports and ADS-B data. In Proceedings of International Workshop on ATM/CNS 2022 International Workshop on ATM/CNS (pp. 33-40). Electronic Navigation Research Institute.
Liu, Z., Lo, S., Blanch, J., & Walter, T. (2024, January). Localizing the October 2022 Texas Jamming Incident Using ADS-B Data with an Improvement in Model Confidence. In Proceedings of the 2024 International Technical Meeting of The Institute of Navigation (pp. 524-531).
Osechas, Okuary, et al. "Impact of GNSS-band radio interference on operational avionics." NAVIGATION: Journal of the Institute of Navigation 69.2 (2022).
Osechas, Okuary, et al. "Impact of RFI on GNSS and avionics–A view from the cockpit." Proceedings of the 34th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2021). 2021.
Schäfer, M., Strohmeier, M., Lenders, V., Martinovic, I., and Wilhelm, M. (2014). Bringing up opensky: A large-scale ADS-B sensor network for research. In IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, pages 83–94. IEEE.

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