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A Dilemma in the Communication of a UAV with its Controller

机译：与其控制器的无人机通信中的困境

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摘要

In this paper, we investigate a dilemma of employing silent mode and communication mode by an unmanned aerial vehicle (UAV) in communication with its controller. In many applications, a UAV communicates with a controller to receive instructions or accurate positioning, but such active communication poses a threat that the UAV can be hijacked through spoofing. On the other hand, during a silent mode (when the UAV does not communicate with the controller), the UAV is safe from spoofing, but is not receiving updates or other important data, and can degrade the overall UAV mission. To gain insight into the UAV risk versus benefit tradeoff, a simple game-theoretic model is presented. Additionally, this paper investigates how incomplete information about the capability of the controller to quickly learn the adversary's attack and adjust its strategy accordingly can impact the equilibrium strategies. In contrast to regular-type capability, when both the rivals maximize their payoffs simultaneously, the capability of the controller to quickly learn is modeled by having the controller apply the best-response strategy. We model this problem using a Bayesian game, where the adversary knows only a priori probabilities about what capability the controller has. Dependence of the equilibrium strategies on these a priori probabilities is illustrated.
机译：在本文中，我们调查了通过无人驾驶飞行器（UAV）与其控制器通信的无静脉模式和通信模式的困境。在许多应用中，UAV与控制器通信以接收指令或准确定位，但是此类活动通信构成了UAV可以通过欺骗来劫持的威胁。另一方面，在一个静默模式（当UAV没有与控制器通信时），UAV是安全的欺骗，但没有接收更新或其他重要数据，并且可以降低整体无人机任务。提出了一个简单的游戏理论模型，进入无人机风险与福利权衡的洞察力。此外，本文调查了对控制员的能力如何快速学习对抗的攻击，并相应地调整其战略的信息如何影响均衡策略。与常规类型的能力相比，当竞争对手同时两个竞争对图时，通过使控制器应用最佳响应策略，控制器快速学习的控制器的能力。我们使用贝叶斯游戏来模拟此问题，在那里对手仅知道控制器具有哪些能力的先验概率。均衡策略对这些先验概率的依赖性。

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