Estimation of Disclosure Risk and Statistical Methods for Disclosure Limitations

披露风险的估计和披露限制的统计方法

• 批准号: 7004015
• 负责人: RODERICK J. LITTLE
• 金额: $ 3.1万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-02-23 至 2008-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7004015
• 关键词: behavioral /social science research tag; clinical research; confidentiality; data collection; data collection methodology /evaluation; human data; information system analysis; information systems; informed consent; statistics /biometry

The recent explosion in demands for microdata from researchers and policy makers, especially when the data collection is paid for with public funds, has increased concerns about confidentiality protection. Confidentiality of responses is a serious commitment made by data-collecting agencies to participants in the study. A similar commitment is expected of any agency that disseminates the data to researchers and policy makers. Along with the increased demands for microdata, a number of commercial databases with the identifying information such as names and addresses and demographic information have also become accessible. These databases raise the concern that an intruder can potentially link the anonymous survey data released by the data collection agencies for public use with the commercial databases to identify one or more respondents to the survey. This research proposal has three primary objectives: (1) To assess the risk of disclosure using data from four test-bed national probability surveys covering a wide variety of topics. The risk will be addressed using two broad classes of intruder models. Type I, where an individual, personally known to the intruder, is known by the intruder to be in the survey; and Type II, where an intruder with access to an external database with names and addresses is seeking to identify respondents in the survey and hence gain access to confidential information; (2) To develop and evaluate new methods to avoid disclosure, and (3) To develop strategies for replacing variables in public-use data sets deemed to increase the risk of disclosure by summary variables that allow users to adjust or control for these variables without knowing their actual values.

研究人员和政策制定者对微数据的最新爆炸爆炸，尤其是当数据收集以公共资金支付时，人们对保密保护的担忧增加了。 响应的机密性是数据收集机构对研究参与者做出的严重承诺。任何将数据传播给研究人员和政策制定者的机构都期望的。随着对微数据的需求增加，许多具有识别信息的商业数据库，例如名称和地址和人口统计信息，也可以访问。这些数据库引起了这样的担忧，即入侵者可以潜在地将数据收集机构发布的匿名调查数据与商业数据库公开使用，以识别调查的一个或多个受访者。该研究建议有三个主要目标：（1）评估 使用来自四个测试床国家概率调查的数据披露，涵盖了各种各样的主题。风险将使用两个广泛的入侵者模型来解决。 I型（I型人都知道，入侵者都知道，入侵者已知在调查中；和II型，其中一个具有访问具有名称和地址的外部数据库的入侵者正在寻求确定调查中的受访者，从而获得访问机密信息； （2）开发和评估新方法以避免披露，以及（3）制定策略，以替换公共使用数据集中的变量，该数据集被认为是通过摘要变量来增加披露风险的，这些变量允许用户在不知道其实际值的情况下对这些变量进行调整或控制。