AI/ML Techniques for ADS-B to Support Base Security and Defense

We are developing a low-cost, ad-hoc ground network of sensors to monitor air traffic around specific areas, for example, to support security and defense around air bases and other installations. This can be seen an air traffic monitoring system in a box, which can be rapidly deployed in an ad-hoc manner, both on the ground and on aerial (manned and unmanned) nodes. The system generates millions of data points per day, which can be mined using Artificial Intelligence and Machine Learning (AI/ML) techniques to identify anomalous behavior of manned and unmanned air traffic. For example, spoofed air traffic (ADS-B) messages (underlying an area denial attack), emergent air routes (for trafficking, illegal entry), etc. In addition, this can also be done from space-based nano satellite sensors, and other open/crowd-sourced data.