The sixth-generation (6G) communication technology has been attracting great interests from both industry and academia, as it is regarded as a promising approach to achieve more stable and low-latency communication. These promising features of 6G make it an enabler for cybertwin, a technique to create digital representations for physical objects to implement various functionalities. In this article, we consider a cybertwin-based spatiotemporal keyword query service over a dynamic message data set in intelligent transportation system (ITS) scenarios. Particularly, in the considered service, publishers upload messages to the cloud, and each cybertwin predictively launches queries to retrieve messages on behalf of the corresponding vehicle, such that each vehicle can timely receive messages that are of its interest whenever it arrives at a location. Nevertheless, as the cloud is not fully trustable, there exist privacy concerns related to the messages and queries. Up to now, although many schemes have been proposed to handle privacy-preserving spatial, temporal, or keyword queries, none of them can simultaneously support queries containing both spatial, temporal, and keyword criteria on dynamic data sets. Aiming at the issue, we design a layered index based on segment trees to dynamically organize messages containing both spatial, temporal, and keyword information. Moreover, based on a symmetric homomorphic encryption scheme, we encrypt the messages and queries and present a two-server privacy-preserving spatiotemporal keyword query scheme. We analyze the security of the proposed scheme and also conduct extensive experiments to evaluate its performance. The results show that our proposed scheme is indeed privacy preserving and computationally efficient.

中文翻译：

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6G时代基于Cyber​​twin的ITS隐私保护时空关键词查询


第六代（6G）通信技术引起了工业界和学术界的极大兴趣，因为它被认为是实现更稳定和低延迟通信的有前途的方法。 6G 的这些有前途的功能使其成为 cybertwin 的推动者，cybertwin 是一种为物理对象创建数字表示以实现各种功能的技术。在本文中，我们考虑在智能交通系统（ITS）场景中基于动态消息数据集的基于cybertwin的时空关键字查询服务。特别是，在所考虑的服务中，发布者将消息上传到云端，并且每个网络孪生代表相应的车辆预测性地启动查询以检索消息，使得每辆车在到达某个位置时都可以及时接收其感兴趣的消息。然而，由于云并不完全可信，因此存在与消息和查询相关的隐私问题。到目前为止，尽管已经提出了许多方案来处理隐私保护的空间、时间或关键字查询，但它们都不能同时支持动态数据集上包含空间、时间和关键字标准的查询。针对这个问题，我们设计了一种基于线段树的分层索引来动态组织包含空间、时间和关键字信息的消息。此外，基于对称同态加密方案，我们对消息和查询进行加密，并提出了一种双服务器隐私保护时空关键字查询方案。我们分析了所提出方案的安全性，并进行了大量的实验来评估其性能。结果表明，我们提出的方案确实能够保护隐私并且计算效率高。