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

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基于线性回归的无人机GPS欺骗检测方法

对无人机的主要安全威胁是通过GPS欺骗来捕获它，攻击者操纵无人机的GPS信号来捕获它。本文介绍了一种反欺骗模型，以减轻GPS欺骗攻击对无人机任务安全的影响。在此模型中，线性回归（LR）用于预测和建模无人机到达其目的地的最佳路线。在此基础上，提出了一种减少GPS欺骗攻击影响的对策机制。对抗基于模型的渐进式检测机制。为了更好地保证无人机的飞行安全性，该模型为欺骗信号提供了多种检测方案，以提高无人机对欺骗信号检测的敏感性。为了更好地证明建议的LR反欺骗模型，制定了动态Stackelberg游戏来模拟GPS滑板与无人机之间的相互作用。特别是对于GPS踏板车，值得一提的是，在实验中模拟了无人机在指定路线的任务环境中被GPS欺骗信号欺骗的情况。特别是，带有LR反欺骗模型的无人机作为该游戏的领导者，在检测到GPS欺骗者的攻击时会根据欺骗的攻击策略动态调整其响应策略。仿真结果表明，该方法可以在不增加无人机硬件成本的前提下，有效提高无人机抵抗GPS欺骗的能力，易于实现。此外，我们还尝试在模型的轨迹预测模块中使用长短期记忆（LSTM）网络。