Lightweight Location Verification in Air Traffic Surveillance Networks

In this work, we develop a realistic threat model for attacks on modern air traffic communication networks and show that current state-of-the-art countermeasures such as multilateration are insufficient. We propose two alternatives, a statistical location verification technique and a grid-based location estimation approach, to deal with the identified threats. We evaluate our proposals using real-world flight data and quantify their effectiveness in terms of aircraft location accuracy, resilience to message injection attacks, attack detection speed, and surveillance coverage. Our results show that the statistical verification approach can increase the effective air traffic surveillance coverage compared to multilateration by a factor of more than 100. Concerning our location estimation method, we find that the mean aircraft location accuracy can be increased by up to 41% in comparison with multilateration while also being able to pinpoint ground-based attackers with a mean error of 145m for air-based attackers. Finally, we demonstrate that our proposal is lightweight as it does not require any changes to the existing air traffic protocols and transmitters, and is easily implemented using only low-cost hardware.