Developing a Low-Cost Raspberry Pi Device for ADS-B Spoofing Detection
Explore the development of Fly Catcher, a low-cost Raspberry Pi-based device designed to detect aircraft spoofing, in this DEF CON 32 conference presentation. Learn how this innovative device combines a 1090 MHz antenna, Flight Aware RTL SDR, custom 3D printed case, and portable battery to monitor malicious ADS-B signals. Discover the implementation of a Convolutional Neural Network written in Python that analyzes aircraft signals for potential spoofing by examining discrepancies in location, velocity, and identification data. Follow along as the presenter shares real-world testing results from an hour-long flight, demonstrating how the device's radar screen display system effectively identifies suspicious aircraft signals through machine learning trained on both valid and spoofed ADS-B datasets.