Towards a Privacy-Aware Electric Vehicle Architecture

Christian Plappert, Jonathan Stancke, Lukas Jäger
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Abstract

Connected vehicles need to generate, store, process, and exchange a multitude of information with their environment. Much of this information is privacy-critical and thus regulated by privacy laws like the GDPR for Europe. In this paper, we analyze and rate exemplary data (flows) of the electric driving domain with regard to their criticality based on a reference architecture. We classify the corresponding ECUs based on their processed privacy-critical data and propose technical mitigation measures and technologies in form of generic privacy-enhancing building blocks according to the classification and requirements derived from the GDPR.
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面向隐私感知的电动汽车架构
联网车辆需要生成、存储、处理和与环境交换大量信息。这些信息中的大部分都是隐私关键信息,因此受到隐私法(如欧洲的GDPR)的监管。在本文中,我们基于一个参考体系结构,分析和评价了电力驱动领域的示例数据(流)的临界性。我们根据处理的隐私关键数据对相应的ecu进行分类,并根据GDPR的分类和要求,以通用隐私增强构建块的形式提出技术缓解措施和技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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