Future Intelligent Transport Systems (ITS) will require that vehicles are equipped with Dedicated Short Range Communications (DSRC). With these DSRC capabilities, new privacy threats are emerging that can be taken advantage of by threat actors with little experience and cheap components. However, the origins of these privacy threats are not limited to the vehicle and its communications, but extend to non-vehicular devices carried by the driver and passengers. A shortcoming of existing work is that it tends to focus on a specific aspect of privacy leakage when attempting to protect location privacy. In doing so, interactions between privacy threats are not considered. In this work, we investigate the privacy surface of a vehicle by considering the many different ways in which location privacy can be leaked. Following this, we identify techniques to protect privacy and that it is insufficient to provide location privacy against a single threat vector. A methodology to calculate the interactions of privacy preserving techniques is used to highlight the need to consider the wider threat landscape and for techniques to collaborate to ensure location privacy is provided against multiple sources of privacy threats where possible.

中文翻译：

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保护实时车辆位置上下文的隐私挑战


未来的智能交通系统（ITS）将要求车辆配备专用短程通信（DSRC）。借助这些 DSRC 功能，新的隐私威胁正在出现，经验不足且组件廉价的威胁行为者可以利用这些威胁。然而，这些隐私威胁的根源不仅限于车辆及其通信，还延伸到驾驶员和乘客携带的非车载设备。现有工作的一个缺点是，在尝试保护位置隐私时，它往往关注隐私泄露的特定方面。这样做时，不考虑隐私威胁之间的相互作用。在这项工作中，我们通过考虑可能泄露位置隐私的多种不同方式来调查车辆的隐私表面。在此之后，我们确定了保护隐私的技术，并且不足以针对单一威胁向量提供位置隐私。使用计算隐私保护技术的相互作用的方法来强调需要考虑更广泛的威胁形势以及协作技术以确保在可能的情况下针对多个隐私威胁源提供位置隐私。