GPS Spoofing: Detecting GPS Fraud in Unmanned Aerial Vehicles

  • Isadora Ferrão USP
  • Sherlon da Silva USP
  • Daniel Pigatto UTFPR
  • Kalinka Branco USP


The exponential growth in the Unmanned Aerial Vehicles (UAVs) market is pointed out in recent reports. It is believed that in 2022 UAVs will represent the largest share in the global market. Therefore, the rapid and growing evolution of the market must be accompanied by the improvement of solid principles of decision-making, security, and technologies. They must continually adapt to face missions where they deal with unforeseen problems. The increase in advanced functionality and the demand for computational capacity exposes UAVs to different security vulnerabilities. These vulnerabilities are growing not only in number but also in sophistication. Failures in UAVs can endanger the safety of people and the environment. The vulnerability of GPS systems has been a significant concern for civil aviation. It is the most recurrent failure, has a low level of complexity of exploration, and leads to a compromise of missions through the possibility of theft and even the destruction of the vehicle after a fall. Based on that, this work proposes to carry out three studies involving GPS attacks in UAVs. The first will be a case study to validate two proposed metrics for detecting GPS fraud. The second will be using a free app for counterfeiting GPS on a real UAV and, finally, the implementation of two metrics, one for security and one for module’s health that can be coupled to UAV architectures, enabling these vehicles to be able to detect the GPS attack.
Palavras-chave: Global Positioning System, Security, Safety, Measurement, Drones, Aircraft, Indexes, Security and Safety for UAVs, GPS Spoofing in UAVs
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FERRÃO, Isadora; DA SILVA, Sherlon; PIGATTO, Daniel; BRANCO, Kalinka. GPS Spoofing: Detecting GPS Fraud in Unmanned Aerial Vehicles. In: SIMPÓSIO BRASILEIRO DE ROBÓTICA E SIMPÓSIO LATINO AMERICANO DE ROBÓTICA (SBR/LARS), 17. , 2020, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 311-316.