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

基于位置的应用的快速发展导致对位置隐私的日益关注。 当前的移动的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和低效的。 大多数现有的位置混淆机制是基于语法隐私模型，不考虑移动性，因此容易受到推理攻击。 这个项目的目标是开发严格的和可定制的隐私概念和位置扰动机制，个人位置共享在基于位置的应用程序，并研究其影响的背景下，基于位置的查询和地理空间众包。 构建可由移动的用户直接使用的隐私机制将最小化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披露他们的精确位置和轨迹。 通过解决时空隐私障碍，该项目有望在实现和促进采用基于位置的应用程序，同时确保个人隐私的重大影响。 该项目还包括一系列综合教育活动，包括黑客活动、研究生和本科生的参与以及鼓励妇女和少数民族的参与。1）基于差分隐私及其变体开发严格的隐私概念以用于位置保护，同时通过移动性建模来考虑用户位置的时空相关性，2）扩展隐私保护方案以保护轨迹或时间-位置对序列;以及3）通过策略图，考虑用户偏好，时空语义，和隐私效用的权衡。 在基于位置的应用（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效用权衡。 有关此项目的更多信息，请访问http://www.mathcs.emory.edu/aims/stprivacy

项目成果

PriSTE: Protecting Spatiotemporal Event Privacy in Continuous Location-Based Services

• DOI: 10.14778/3352063.3352086
• 发表时间: 2019-08
• 期刊: Proc. VLDB Endow.
• 作者: Yang Cao;Yonghui Xiao;Li Xiong;Liquan Bai;Masatoshi Yoshikawa