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Design and Evaluation of a Privacy-Preserving Architecture for Vehicle-to-Grid Interaction

机译:车辆与网格交互的隐私保护架构的设计与评估

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Charging battery-electric vehicles can pose a significant load to the power grid. Letting a central instance control vehicle charging processes can reduce the grid load and allows for vehicles to be used as distributed grid resources. It is commonly assumed that vehicle owners are willing to reveal their driving patterns to the control instance. As we show, current privacy-preserving technologies can be used to construct an architecture that reduces the need to reveal such sensitive information. Yet, we identify limitations to such an approach and demonstrate how an adversary can use information inherent to the context to decrease vehicle owner privacy. As a concrete case, we discuss an adversary algorithm based on travel times and show how to obtain anonymity sets for individual vehicles. This allows us to make an important step towards understanding and quantifying privacy achievable in practice.
机译:给电动汽车充电会给电网带来很大的负担。让中央实例控制车辆的充电过程可以减少电网负荷,并允许将车辆用作分布式电网资源。通常假定车主愿意向控制实例显示他们的驾驶模式。正如我们所展示的,当前的隐私保护技术可用于构建减少显示此类敏感信息的需求的体系结构。但是,我们确定了这种方法的局限性,并演示了对手如何利用上下文固有的信息来减少车主的隐私。作为一个具体案例,我们讨论了一种基于行驶时间的对手算法,并展示了如何获取单个车辆的匿名集。这使我们朝着理解和量化实践中可实现的隐私迈出了重要的一步。

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