Charlotte Olivia Namagembe, Mohamad Ibrahim, Md Arafatur Rahman*, Prashant Pillai
CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.070316
- 09 December 2025
Abstract The rapid proliferation of commercial unmanned aerial vehicles (UAVs) has revolutionized fields such as precision agriculture and disaster response. However, their heavy reliance on GPS navigation leaves them highly vulnerable to spoofing attacks, with potentially severe consequences. To mitigate this threat, we present a machine learning-driven framework for real-time GPS spoofing detection, designed with a balance of detection accuracy and computational efficiency. Our work is distinguished by the creation of a comprehensive dataset of 10,000 instances that integrates both simulated and real-world data, enabling robust and generalizable model development. A comprehensive evaluation of multiple classification More >