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SaTC: CORE: Medium: Collaborative: User-Centered Deployment of Differential Privacy

SaTC：核心：媒介：协作：以用户为中心的差异隐私部署

基本信息

批准号：
1931441
负责人：
Aiping Xiong
金额：
$ 8.01万
依托单位：
Pennsylvania State Univ University Park
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-01-01 至 2023-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931441&HistoricalAwards=false
关键词：
SaTC CORE Medium Collaborative User

项目摘要

Differential privacy (DP) has been accepted as the de facto standard for data privacy in the research community and beyond. Both companies and government agencies are trying to deploy DP technologies. Broader deployments of DP technology, however, face challenges. This project aims to understand the needs of different stakeholders in data privacy, and to develop algorithms and software to enable broader deployment of private data sharing. The project's novelty is combining the expertise of social science researchers with that of computer scientists who have both theoretical and system research experiences related to DP to develop a hybrid approach to private data sharing to achieve better privacy-utility tradeoff. The project's impacts are in advancing the state-of-the-art with regard to DP deployment in particular and privacy protection in general. More specifically the project identifies the workflow of DP data sharing, improve understanding of DP communication, and develop new algorithms, privacy concepts, and privacy mechanisms to support deployment of DP. The project has four tasks that will advance the understanding of user-centered DP and lay a foundation for its deployment. (1) Examine individual human users' perception, comprehension and acceptance of the concept and guarantee of DP and the effect of privacy parameter, and to investigate effective ways to communicate those concepts. (2) Implement methods from the domains of human factors and human-computer interaction to identify tasks, goals, and workflow in private data sharing. (3) Develop key algorithms and software for a hybrid approach of private data sharing. In the hybrid approach, one first publishes a private synopsis of dataset using carefully selected low-degree marginals. From these marginals, one can either synthesize new datasets, or answer queries directly using inference under the maximum entropy principle. The hybrid approach enhances this with interactive query answering, enabling extraction of information not covered by low-degree marginals. (4) Develop techniques to further improve the privacy-utility tradeoff in private data sharing, including a theory of differential privacy under publishable information.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

差分隐私（DP）已被接受为数据隐私的事实标准在研究界和超越。公司和政府机构都在尝试部署DP技术。然而，DP技术的广泛应用面临着挑战。该项目旨在了解不同利益相关者在数据隐私方面的需求，并开发算法和软件，以便更广泛地部署私人数据共享。该项目的新颖之处在于将社会科学研究人员的专业知识与具有DP相关理论和系统研究经验的计算机科学家的专业知识相结合，开发一种混合方法来共享私人数据，以实现更好的隐私-效用权衡。该项目的影响是推动了DP部署方面的最新技术，以及总体上的隐私保护。更具体地说，该项目确定了DP数据共享的工作流程，提高了对DP通信的理解，并开发了新的算法、隐私概念和隐私机制，以支持DP的部署。该项目有四项任务，将促进对以用户为中心的DP的理解，并为其部署奠定基础。(1)考察个人用户对DP概念和保障以及隐私参数的影响的感知、理解和接受程度，并探讨这些概念的有效沟通方式。(2)实现人因和人机交互领域的方法，以识别私有数据共享中的任务、目标和工作流。(3)为私有数据共享的混合方法开发关键算法和软件。在混合方法中，首先使用精心选择的低度边缘发布数据集的私人摘要。从这些边缘，可以合成新的数据集，或者直接使用最大熵原理下的推理来回答查询。混合方法通过交互式查询回答增强了这一点，可以提取未被低度边缘覆盖的信息。(4)开发技术以进一步改善隐私数据共享中的隐私-效用权衡，包括可发布信息下的差分隐私理论。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Exploring Use of Explanative Illustrations to Communicate Differential Privacy Models

探索使用解释性插图来传达差异隐私模型

DOI：
10.1177/21695067231195006
发表时间：
2023
期刊：
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
影响因子：
0
作者：
Xiong, Aiping;Wu, Chuhao;Wang, Tianhao;Proctor, Robert W.;Blocki, Jeremiah;Li, Ninghui;Jha, Somesh
通讯作者：
Jha, Somesh

Effect of Facts Box on Users’ Comprehension of Differential Privacy: A Preliminary Study

事实框对用户理解差异隐私的影响：初步研究