POSE: Phase II: Building the Differential Privacy Ecosystem through OpenDP

POSE：第二阶段：通过 OpenDP 构建差分隐私生态系统

• 批准号: 2303681
• 负责人: Salil Vadhan
• 金额: $ 150万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2303681&HistoricalAwards=false
• 关键词: POSE; Phase; II; Building; Differential

Data science and artificial intelligence can offer many benefits for society. Large important data sets containing private information about individuals, such as electronic medical records or online shopping behavior, could be used to help researchers understand human health and behavior, help governments evaluate policies, and help companies offer custom products and services. However, even when the data are stripped of identifying information, it may still be possible to link specific people back to the data and violate their privacy. Because the owners of these datasets are obligated to protect the privacy of the people whose data have been collected, the potential to make the data available for research to benefit society is lost. To address this problem the OpenDP software, an open-source suite of tools and algorithms for differential privacy, can be used to ensure that no individual whose personal data is in a dataset can be identified. This project supports a community effort to develop a self-sustaining ecosystem around the OpenDP software. The project creates a sustainable OpenDP ecosystem of developers, contributors and users, together with a governing board that can guide future development and respond to community needs. Workshops, conferences, and media connect new contributors, creating new ways to contribute, credit, and manage volunteer effort. Outreach to industry and researchers in public health and genomics grows the OpenDP user base. Planning for future growth of and finding new applications for OpenDP will ensure the ecosystem's long-term stability. Through this award, users of and contributors to OpenDP will have a stable community that will assist them in developing privacy solutions for the future.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.

数据科学和人工智能可以为社会带来许多好处。包含个人隐私信息的大型重要数据集，如电子医疗记录或网购行为，可用于帮助研究人员了解人类健康和行为，帮助政府评估政策，并帮助公司提供定制产品和服务。然而，即使数据被剥夺了识别信息，仍有可能将特定人员链接回数据并侵犯他们的隐私。由于这些数据集的所有者有义务保护其数据被收集的人的隐私，因此失去了将数据用于造福社会的研究的可能性。为了解决这个问题，可以使用OpenDP软件，这是一套开放源代码的工具和算法，用于区分隐私，以确保个人数据在数据集中的个人无法被识别。该项目支持社区围绕OpenDP软件开发一个自给自足的生态系统。该项目创建了一个由开发者、贡献者和用户组成的可持续的OpenDP生态系统，以及一个可以指导未来发展和响应社区需求的管理委员会。研讨会、会议和媒体将新的贡献者联系在一起，创造了贡献、表彰和管理志愿者工作的新方式。与公共卫生和基因组学行业和研究人员的接触增加了OpenDP的用户基础。规划OpenDP的未来增长并为其寻找新的应用程序将确保生态系统的长期稳定。通过这一奖项，OpenDP的用户和贡献者将拥有一个稳定的社区，帮助他们开发未来的隐私解决方案。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。