Aviation technology is vulnerable to a wide range of cyber threats. Hackers can easily spoof “ghost” aircraft into the sky.
In order to tackle this issue, Angelina Tsuboi, a pilot and a cybersecurity researcher developed a device called Fly Catcher to detect instances of aircraft spoofing on ADS-B. She also flew it on a plane over the coast of Los Angeles.
Fly Catcher monitors the ADS-B 1090MHz frequency to detect spoofed aircraft by ground-based hackers using a custom AI model and neural network.
The device consists of a 1090MHz antenna, FlightAware SDR, a custom 3D chassis and a Raspberry Pi, and scans nearby ADS-B messages and runs them through a neural network to detect fake aircraft transmitted by bad actors.
You can check out the project GitHub here.
You can also read the project article on Medium here.
Watch Fly Catcher in action on YouTube
Angelina’s Website: https://www.angelinatsuboi.net/