论文标题

与无人机套餐交付系统的隐私路线

Routing with Privacy for Drone Package Delivery Systems

论文作者

Ding, Geoffrey, Berke, Alex, Gopalakrishnan, Karthik, Degue, Kwassi H., Balakrishnan, Hamsa, Li, Max Z.

论文摘要

无人驾驶汽车(无人机)或无人机越来越多地用于将货物从供应商交付给客户。为了安全地进行大规模进行这些操作,需要无人机来广播远程标识(远程ID)规定中编码的位置信息。但是,包装交付无人机的位置广播为使用这些送货服务的客户带来了隐私风险:第三方观察者可能会利用广播无人机轨迹将客户与他们的购买联系起来,可能导致广泛的隐私风险。我们提出了基于将客户与供应商相关联的可能性的可能性的概率定义。接下来,我们量化这些风险,使无人机操作员在计划交货路线时可以评估隐私风险。然后,我们评估各种因素(例如无人机容量)对隐私的影响,并考虑隐私和交付等待时间之间的权衡。最后,我们提出了启发式方法,以生成具有隐私保证的路线,以避免对所有可能的路线进行详尽的枚举,并在几种现实的交付方案上评估其绩效。

Unmanned aerial vehicles (UAVs), or drones, are increasingly being used to deliver goods from vendors to customers. To safely conduct these operations at scale, drones are required to broadcast position information as codified in remote identification (remote ID) regulations. However, location broadcast of package delivery drones introduces a privacy risk for customers using these delivery services: Third-party observers may leverage broadcast drone trajectories to link customers with their purchases, potentially resulting in a wide range of privacy risks. We propose a probabilistic definition of privacy risk based on the likelihood of associating a customer to a vendor given a package delivery route. Next, we quantify these risks, enabling drone operators to assess privacy risks when planning delivery routes. We then evaluate the impacts of various factors (e.g., drone capacity) on privacy and consider the trade-offs between privacy and delivery wait times. Finally, we propose heuristics for generating routes with privacy guarantees to avoid exhaustive enumeration of all possible routes and evaluate their performance on several realistic delivery scenarios.

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