An Approach of Linear Regression-Based UAV GPS Spoofing Detection

A prominent security threat to unmanned aerial vehicle (UAV) is capture it by GPS spoofing, in which the attacker manipulates signal of UAV it. This paper introduces an anti-spoofing model mitigate impact spoofing attack on mission security. In this model, linear regression (LR) used predict and optimal route its destination. On basis, a countermeasure mechanism proposed reduce attack. Confrontation based progressive detection model. order better ensure flight UAV, provides more than one scheme for improve sensitivity deception detection. For proving LR dynamic Stackelberg game formulated simulate interaction between spoofer UAV. particular, spoofer, worth mentioning that scenario cheated environment designated simulated experiment. with as leader game, dynamically adjusts response strategy according deception’s when upon spoofer’s The simulation results show method can effectively enhance ability resist without increasing hardware cost easy implement. Furthermore, we also try use long short-term memory (LSTM) network trajectory prediction module experimental far LSTM terms accuracy.