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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Towards Providing Scalable and Robust Privacy in Vehicular Networks
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Towards Providing Scalable and Robust Privacy in Vehicular Networks

机译：致力于在车载网络中提供可扩展且强大的隐私

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摘要

In vehicular networks, there is a strong correlation between a vehicle's identity and that of the driver. It follows that any effort to protect driver privacy must attempt to make the link between the two harder to detect. One of the most appealing solutions to hiding the identity of a vehicle is the use of pseudonyms, whereby each vehicle is issued one or several temporary identities (i.e., pseudonyms) that it uses to communicate with other vehicles and/or the roadside infrastructure. Due to the large number of vehicles on our roadways and city streets and of the sophistication of possible attacks, privacy protection must be both scalable and robust. The first main contribution of this work is to take a nontrivial step towards providing a scalable and robust solution to privacy protection in vehicular networks. To promote scalability and robustness we employ two strategies. First, we view vehicular networks as consisting of nonoverlapping subnetworks, each local to a geographic area referred to as a cell. Depending on the topology and the nature of the area, these cells may be as large as few city blocks or, indeed, may comprise the entire downtown area of a small town. Each cell has a server that maintains a list of pseudonyms valid for use in the cell. Instead of issuing pseudonyms to vehicles proactively, as virtually all existing schemes do, we issue pseudonyms only to those vehicles that request them. Our second main contribution is to model analytically the time-varying request for pseudonyms in a given cell. This is important for capacity planning purposes since it allows system managers to predict, by taking into account the time-varying attributes of the traffic, the probability that a given number of pseudonyms will be required at a certain time as well as the expected number of pseudonyms in use in a cell at a certain time. Empirical results obtained by detailed simulation confirmed the accuracy of our analytical predictions.
机译：在车辆网络中，车辆的身份与驾驶员的身份之间存在很强的相关性。因此，保护​​驾驶员隐私的任何努力都必须试图使两者之间的联系更难被发现。隐藏车辆身份的最吸引人的解决方案之一是使用假名，由此向每个车辆发出一个或多个临时身份（即假名），用于与其他车辆和/或路边基础设施进行通信。由于我们的道路和城市街道上的车辆数量众多，并且可能会遭到攻击，因此隐私保护必须具有可扩展性和鲁棒性。这项工作的第一个主要贡献是朝着为车辆网络中的隐私保护提供可扩展且强大的解决方案迈出了重要的一步。为了提高可伸缩性和鲁棒性，我们采用了两种策略。首先，我们将车辆网络视为由不重叠的子网络组成，每个子网络位于一个称为小区的地理区域内。根据区域的拓扑和性质，这些单元可能只有几个街区那么大，或者实际上可能包含一个小镇的整个市区。每个单元都有一个服务器，该服务器维护一个有效用于该单元的假名列表。与其像几乎所有现有方案一样，不主动向车辆发出假名，我们仅向请求它们的车辆发出假名。我们的第二个主要贡献是对给定单元格中假名的时变请求进行分析建模。这对于容量规划目的非常重要，因为它允许系统管理员通过考虑流量的时变属性来预测在特定时间需要给定数量的假名的概率以及预期的数量。某个时间在某个单元格中使用的假名。通过详细模拟获得的经验结果证实了我们的分析预测的准确性。

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