I-Corps: Privacy-preserving data sharing software platform

I-Corps项目的更广泛影响/商业潜力是为医疗保健、金融和政府等受到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、违反法规和声誉受挫的风险，这些垂直行业的数据保管人必须将机密数据资产保存在孤岛中。提出的技术可以使这些企业建立一个集中的数据库，并安全地将这些数据公开给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与人类服务部、司法系统和社区服务部的不同部门了解监禁的风险因素，如无家可归和严重精神疾病，从而更好地分配资源，设计有效的干预措施，减少社会不平等。构建集中式数据库的挑战是安全和隐私，该项目将把最好的安全和隐私技术带到最前沿。这个I-Corps项目是基于一个保护隐私的数据仓库和分析引擎的开发。此仓库连接到异构数据源和联邦数据源，同时确保原始机密数据保留在数据保管人的数据源中。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的记录。安全分析引擎使链接数据可用于查询，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披露其记录存在于数据中的个人的身份。基于基础研究，数据仓库和分析引擎包括用于联邦查询的新颖系统架构、用于大数据工作负载的性能和可伸缩性的设计优化以及用于匿名的严格算法。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。

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.