I-Corps: Privacy-preserving data sharing software platform

I-Corps：隐私保护数据共享软件平台

• 批准号: 2243653
• 负责人: Trinabh Gupta
• 金额: $ 5万
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2243653&HistoricalAwards=false
• 关键词: Corps; Privacy; preserving; data; sharing

The broader impact/commercial potential of this I-Corps project is the development of a data sharing product for enterprises in highly regulated verticals such as healthcare, finance, and the government. Today, data custodians in these verticals must keep their confidential data assets in silos due to risks of data breaches, regulatory violations, and reputational setbacks. The proposed technology may enable these enterprises to build a centralized database and expose this data safely for the application of artificial intelligence and machine learning, leading to direct economic and societal benefit. As an example, in the government sector, the proposed technology may enable different departments of Health and Human Services, Judicial System, and Community Services to understand risk factors for incarcerations such as homelessness and serious mental illness, to better allocate resources, design effective interventions, and reduce social inequities. The challenge in building the centralized database is security and privacy, and the project will bring to the forefront the very best of security and privacy technologies. This I-Corps project is based on the development of a privacy-preserving data warehouse and analytics engine. This warehouse connects to heterogeneous and federated data sources, while ensuring that the original confidential data stays at source with the data custodians. The data warehouse links records from different systems of records while removing duplicates in a privacy-preserving manner. The secure analytics engine makes the linked data available for queries, while providing anonymity guarantees through the state-of-the-art technology of differential privacy. The query results obtained do not disclose the identity of an individual whose record is present in the data. Based on fundamental research, the data warehouse and analytics engine include novel system architectures for federated queries, design optimizations for performance and scalability to big data workloads, and rigorous algorithms for anonymity.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.

这个I-Corps项目更广泛的影响/商业潜力是为医疗保健、金融和政府等高度监管的垂直行业的企业开发数据共享产品。如今，由于数据泄露、违反监管规定和声誉受损的风险，这些垂直行业的数据托管人必须将其机密数据资产保存在孤岛中。所提出的技术可以使这些企业能够建立一个集中的数据库，并安全地将这些数据公开用于人工智能和机器学习的应用，从而产生直接的经济和社会效益。例如，在政府部门，拟议的技术可以使卫生和人类服务，司法系统和社区服务的不同部门了解无家可归和严重精神疾病等监禁的风险因素，以更好地分配资源，设计有效的干预措施，并减少社会不平等。建立集中式数据库的挑战是安全和隐私，该项目将带来最好的安全和隐私技术。这个I-Corps项目基于隐私保护数据仓库和分析引擎的开发。该仓库连接到异构和联合数据源，同时确保原始机密数据与数据托管人保持在源位置。数据仓库链接来自不同记录系统的记录，同时以保护隐私的方式删除重复记录。安全分析引擎使链接的数据可用于查询，同时通过最先进的差异隐私技术提供匿名保证。所获得的查询结果不会透露数据中记录的个人的身份。基于基础研究，数据仓库和分析引擎包括用于联合查询的新颖系统架构，针对大数据工作负载的性能和可扩展性的设计优化，以及严格的匿名算法。该奖项反映了NSF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评审标准进行评估，被认为值得支持。