SGER: Blind Evaluation of Spatial Queries with Hilbert Curves to Preserve Location Privacy

该项目开发了一个全新的模型，用于在空间查询评估中保护位置隐私。 主要的新奇在于，与当前的位置隐私方法不同，该模型在常规通信模式期间不需要客户端和服务器之间的中间方。 此功能与典型的加密模型一致，其中两方（Alice和Bob）可以在不通过第三方中介发送消息的情况下进行私下通信。这是一个高风险的研究，因为设计一个加密方案，保持空间的距离属性是困难的。 也就是说，利用传统的加密方法，原始空间中的附近对象在加密空间中不再接近。 我们的想法是设计一个单向变换的空间，使变换后的空间保持原始空间的距离属性，因此空间查询可以有效地解决在变换后的空间。这种转换可以被看作是一个单向的转换功能，允许快速计算其逆给出一些额外的知识，称为transformation-key.The更广泛的影响，这项研究的空间加密是使许多用户的隐私问题，利用定制的位置服务在他们的移动的设备，而不损害他们的位置隐私。这反过来将增加许多行业和政府机构在地理空间信息系统、在线地图、汽车导航系统、基于位置的服务和军事/情报行动等领域的客户群。该项目资助了一名博士生。 加密工具和介绍这些工具的技术文件将通过该项目的网址：http://infolab.usc.edu/projects/LocationPrivacy/传播。

This project develops a fundamentally new model for preserving location privacy in spatial query evaluation. The main novelty is that unlike the current approaches for location privacy, this model does not require an intermediate party between the client and server during the regular mode of communication. This feature is consistent with the typical encryption models where two parties, Alice and Bob, can communicate privately without sending their messages through a third party intermediator. This is a high-risk research because devising an encryption scheme that maintains distance properties of space is hard. That is, with conventional encryption approaches, nearby objects in the original space are no longer close in the encrypted space. The idea is to devise a one-way transformation on the space such that the transformed space maintains the distance properties of the original space and hence spatial queries can be resolved efficiently in the transformed space. This transformation can be viewed as encryption of the space with a one-way transformation function that allows fast computation of its inverse given some extra knowledge, termed transformation-key.The broader impact of this study is to enable many users with privacy concerns to utilize customized location services in their mobile devices without compromising their location privacy. This in turn would increase the customer base for many industries and government agencies in the areas of geospatial information systems, online maps, car navigation systems, Location-Based Services, and military/intelligence operations. One PhD student is supported by this project. The encryption tools and the technical papers describing them will be disseminated through the project's web site: http://infolab.usc.edu/projects/LocationPrivacy/.