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

SGER：使用希尔伯特曲线对空间查询进行盲评估以保护位置隐私

• 批准号: 0742811
• 负责人: Cyrus Shahabi
• 金额: --
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2009-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0742811&HistoricalAwards=false
• 关键词: SGER; Blind; Evaluation; Spatial; Queries

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/.

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。主要的新颖之处在于，与当前的位置隐私方法不同，该模型在常规通信模式中不需要客户机和服务器之间的中间方。这个特性与典型的加密模型是一致的，其中双方Alice和Bob可以私下通信，而无需通过第三方中介发送消息。这是一个高风险的研究，因为设计一个保持空间距离属性的加密方案是困难的。也就是说，使用传统的加密方法，原始空间中的附近对象在加密空间中不再接近。其思想是在空间上设计一个单向变换，使变换后的空间保持原空间的距离属性，从而在变换后的空间中有效地解决空间查询问题。这个变换可以看作是用单向变换函数对空间进行加密，该变换函数允许在给定一些额外的知识（称为变换密钥）的情况下快速计算其逆。这项研究的更广泛的影响是使许多关心隐私的用户能够在他们的移动设备上使用定制的位置服务，而不会损害他们的位置隐私。这反过来又会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/情报行动领域的客户群。该项目资助1名博士生。加密工具和描述它们的技术文件将通过该项目的网站：http://infolab.usc.edu/projects/LocationPrivacy/发布。