A privacy-preserving route planning scheme for the Internet of Vehicles
A privacy-preserving route planning scheme for the Internet of Vehicles
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DOI：
10.1016/j.adhoc.2021.102680
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发表时间：
2021
期刊：
影响因子：
4.8
通讯作者：
U. Atmaca;C. Maple;G. Epiphaniou;M. Dianati
中科院分区：
文献类型：
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作者：
U. Atmaca;C. Maple;G. Epiphaniou;M. Dianati
物联网（IoT）正在被集成到应用程序中，这些应用程序正在继续重塑我们日常生活的许多元素。其中一个主要的应用领域是车联网，它可以增强现有的能力，例如有效的车辆路线规划。这样的系统通常依赖于包括车辆的时间位置馈送的实时交通信息。尽管提供了明显的优势（如克服拥堵，节省燃料/能源/时间，并减少二氧化碳排放），隐私问题出现由于位置数据的使用。受此启发，为边缘云辅助车辆开发了一种隐私保护的车辆位置（例如定位）共享方案。此外，数据效用界限进行了理论分析，车辆路径效率进行了实证分析，以评估所提出的计划的影响。而不是在二维空间上共享扰动位置，我们提出了一个基于图的差分隐私共享位置的解决方案。这项工作的新奇依赖于将车辆地理空间数据转换为图形结构数据，以提高其在道路网络上的适用性，设计实时应用程序，并对隐私效率最优性进行实证分析。
Abstract Internet of the Things (IoT) is being integrated into applications that are continuing to reshape many elements of our daily life. One of the major application areas is the Internet of Vehicles which can enhance existing capabilities, such as efficient vehicle route planning. Such systems usually rely on real-time traffic information that includes the temporal location feed of a vehicle. Despite offering clear advantages (such as overcoming congestion, saving fuel/energy/time, and reducing C O 2 emission), privacy concerns emerge due to the use of location data. Motivated by this, a privacy-preserving vehicular location (eg positioning) sharing scheme is developed for edge cloud-assisted vehicles. In addition, data utility bounds are theoretically analysed, and vehicle routing efficacy is empirically analysed to evaluate the impact of the proposed scheme. Rather than sharing perturbed location on two-dimensional space, we propose a graph-based differential privacy solution for sharing location. The novelty of this work relies on translating the vehicular geospatial data to the graph-structured data for its higher applicability on the road network, designing a real-time application, and empirical analysis of privacy-efficacy optimality.