GPS-Spoofing Attack Detection Technology for UAVs Based on Kullback–Leibler Divergence

Here, we developed a method for detecting cyber security attacks aimed at spoofing the Global Positioning System (GPS) signal of an Unmanned Aerial Vehicle (UAV). Most methods UAV anomalies indicative attack use machine learning or other such that compare normal behavior with abnormal behavior. Such approaches require large amounts data and significant “training” time to prepare implement system. Instead, consider new approach based on mathematical without need first collect amount describe patterns. Doing so can simplify process creating anomaly detection system, which further facilitate easier implementation intrusion systems in UAVs. This article presents issues related ensuring information Development GPS UAVs is then described, preliminary study made it possible form apparatus solving problem. We explain necessary analysis parameters normalization, Kullback—Leibler divergence measure needed detect systems.