Privacy preserving record linkage

隐私保护记录联动

• 批准号: 492830-2016
• 负责人: Hamilton, Howard
• 金额: $ 0.91万
• 依托单位: University of Regina
• 依托单位国家: 加拿大
• 项目类别: Engage Plus Grants Program
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=602215
• 关键词: Privacy; preserving; record; linkage

We will perform research on Record Linkage algorithms for cases where the privacy of record holders must be preserved. The goal of Record Linkage is to recognize records from different databases that correspond to the same entity. With the increasing size of today's databases, the complexity and slow speed of the linking process has become one of the major challenges for performing Record Linkage. Furthermore, when databases that contain confidential information are linked across different organizations, the issue of protecting the privacy and confidentiality of the data becomes crucial. We seek to devise and evaluate methods for efficient and accurate linking of two or more databases that ensure no privacy breach occurs. Efficiency is important because the databases may be very large. In the future, Canadian companies may apply the Record Linkage algorithms created by this project to large collections of data from a diversity of clients including health, medical, and governmental organizations. The data from such organizations almost always include confidential information. Since commonly identifying data, such as names, addresses, and date of births of record holders are typically used to link records, methods for preserving the privacy of individuals are a key concern. We will also try to identify quantitative measures of trade offs between levels of privacy versus efficiency of operations.

我们将对记录链接算法进行研究，以解决必须保护记录持有人隐私的问题。记录链接的目标是识别来自不同数据库的对应于同一实体的记录。随着当今数据库规模的增加，链接过程的复杂性和缓慢的速度已经成为执行记录链接的主要挑战之一。此外，当包含机密信息的数据库在不同组织之间连接时，保护数据隐私和机密性的问题就变得至关重要。我们致力于设计和评估两个或多个数据库的有效和准确链接方法，以确保不会发生隐私泄露。效率很重要，因为数据库可能非常大。未来，加拿大公司可能会将该项目创建的记录链接算法应用于来自各种客户的大量数据，包括健康，医疗和政府组织。这些组织提供的数据几乎总是包含机密信息。由于通常使用记录持有人的姓名、地址和出生日期等识别数据来链接记录，因此保护个人隐私的方法是一个关键问题。我们还将尝试确定隐私级别与操作效率之间的权衡的量化措施。