TWC: Small: Rigorous and Customizable Spatiotemporal Privacy for Location Based Applications

TWC：小型：基于位置的应用程序的严格且可定制的时空隐私

• 批准号: 1618932
• 负责人: Li Xiong
• 金额: $ 45.64万
• 依托单位: Emory University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618932&HistoricalAwards=false
• 关键词: TWC; Small; Rigorous; Customizable; Spatiotemporal

Rapid advances in location based applications are leading to increased concern about location privacy. Current mobile operating systems only provide users with rudimentary location access controls - either to block or allow location access - which are inadequate and inefficient in mitigating privacy threats. Most existing location obfuscation mechanisms are based on syntactic privacy models that do not consider mobility and are hence vulnerable to inference attacks. The goal of this project is to develop rigorous and customizable privacy notions and location perturbation mechanisms for individual location sharing in location based applications, and study their impact in the context of location based queries and geospatial crowdsourcing. Building privacy mechanisms that can be directly used by mobile users will minimize unnecessary disclosure of their precise locations and trajectories to location based applications and other possibly malicious third parties. By addressing the spatiotemporal privacy barrier, this project promises significant impact in enabling and promoting adoption of location based applications while ensuring individual privacy. The project also includes a set of integrated educational activities including hackathon events, involvement of graduate and undergraduate students, and encouragement of participation by women and minorities.The project has several objectives: 1) Develop rigorous privacy notions based on differential privacy and its variants for location protection while accounting for spatiotemporal correlations of a user's locations through mobility modeling, and to investigate optimal and heuristic perturbation mechanisms to achieve privacy guarantees with optimal utility; 2) Extend privacy solutions for protecting a trajectory or a sequence of time-location pairs; and 3) Develop customizable privacy solutions for location and trajectory protection through policy graphs, considering user preferences, spatiotemporal semantics, and privacy-utility tradeoffs. Privacy-utility tradeoffs using perturbed locations are studied in the context of location based applications such as predictive range queries and k-nearest neighbor queries as well as geospatial crowdsourcing. More information on this project can be found at http://www.mathcs.emory.edu/aims/stprivacy

基于位置的应用程序的快速发展导致人们对位置隐私的日益关注。 当前的移动操作系统仅向用户提供基本的位置访问控制（阻止或允许位置访问），这在减轻隐私威胁方面是不充分且低效的。 大多数现有的位置混淆机制基于句法隐私模型，不考虑移动性，因此容易受到推理攻击。 该项目的目标是为基于位置的应用程序中的个人位置共享开发严格且可定制的隐私概念和位置扰动机制，并研究它们在基于位置的查询和地理空间众包背景下的影响。 建立移动用户可以直接使用的隐私机制将最大限度地减少向基于位置的应用程序和其他可能恶意的第三方不必要地泄露他们的精确位置和轨迹。 通过解决时空隐私障碍，该项目有望在确保个人隐私的同时，在支持和促进基于位置的应用程序的采用方面产生重大影响。 该项目还包括一系列综合教育活动，包括黑客马拉松活动、研究生和本科生的参与以及鼓励女性和少数族裔的参与。该项目有几个目标：1）基于差异隐私及其变体制定严格的隐私概念位置保护，同时通过移动建模考虑用户位置的时空相关性，并研究最佳和启发式扰动机制，以实现具有最佳效用的隐私保证； 2) 扩展用于保护轨迹或时间位置对序列的隐私解决方案； 3) 通过策略图开发可定制的隐私解决方案，用于位置和轨迹保护，同时考虑用户偏好、时空语义和隐私与实用性的权衡。 在基于位置的应用程序（例如预测范围查询和 k 最近邻查询以及地理空间众包）的背景下，研究了使用扰动位置的隐私与效用权衡。 有关该项目的更多信息，请访问 http://www.mathcs.emory.edu/aims/stprivacy

项目成果

PGLP: Customizable and Rigorous Location Privacy Through Policy Graph

PGLP：通过策略图实现可定制且严格的位置隐私

• DOI: 10.1007/978-3-030-58951-6_32
• 发表时间: 2020-09
• 期刊: Computer Security – ESORICS 2020
• 作者: Cao, Yang;Xiao, Yonghui;Takagi, Shun;Xiong, Li;Yoshikawa, Masatoshi;Shen, Yilin;Liu, Jinfei;Jin, Hongxia;Xu, Xiaofeng
• 通讯作者: Xu, Xiaofeng

PriSTE: protecting spatiotemporal event privacy in continuous location-based services

PriSTE：在连续的基于位置的服务中保护时空事件隐私

• DOI: 10.14778/3352063.3352086
• 发表时间: 2019-08
• 期刊: Proceedings of the VLDB Endowment
• 影响因子: 2.5
• 作者: Cao, Yang;Xiao, Yonghui;Xiong, Li;Bai, Liquan;Yoshikawa, Masatoshi
• 通讯作者: Yoshikawa, Masatoshi