Mitigating Spoofed GNSS Trajectories through Nature Inspired Algorithm

Abstract

Advancement in technology has resulted in the easy sharing of locations across various stakeholders. Unprotected sharing of location information makes any Global Navigation Satellite System (GNSS) device vulnerable to spoofing attacks. Spoofed GNSS signals propagate misleading trajectories to cripple any Location-Based Service (LBS). This manuscript introduces a novel algorithm for the detection and mitigation of spoofing attacks. The proposed algorithm was implemented in the Android application using the OpenStreetMap dataset. GNSS spoofing attacks were simulated and detected in real-time. The efficiency of the proposed algorithm was analyzed using the Ratio of Correctly Detected (RCD) and Ratio of Correctly Matched (RCM) spoofed points. The maximum observed values for RCD and RCM were 75% and 94%, respectively. Minimum RCD and RCM values observed during the experiment were 59% and 92%. The accuracy of the proposed algorithm was further analyzed using average positional error (APE). Maximum and minimum recorded APE values were 25.08% and 13.83% respectively. The manuscript concludes with a comparison of the proposed algorithm with that of existing techniques.