Probabilistic Analysis of GPS Spoofing Attack Failures Using Poisson Point Process

This study presents a geospatial analysis approach to derive the failure probability of GPS spoofing attacks by utilizing Poisson Point Process (PPP) modeling. The research begins by establishing a robust framework for characterizing GPS spoofing attacks based on available data and historical attack patterns. Leveraging the PPP model, which is commonly used in spatial point process analysis, the study integrates real-world information such as GPS receiver locations, environmental conditions, and spoofing device parameters to simulate the spatial distribution of spoofing attack attempts across a given area. Through the application of PPP modeling, the study aims to estimate the failure probability of GPS spoofing attacks, which is defined as the likelihood of the spoofer's signal being successfully received and accepted by a targeted GPS receiver. This approach allows for the incorporation of various geospatial factors, including receiver density, signal propagation, and environmental interference, to provide a more accurate representation of the vulnerability of the GPS system to spoofing attacks in specific geographic areas. The findings from this research are expected to contribute to enhancing the understanding of GPS vulnerability and improving countermeasures against spoofing attacks. The closed form expression for GPS Spoofing attack failure probability is derived using the Poisson point process. The simulation is compared with the theoretical results and observed that it is exactly close to each other.