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.

最近，研究人员和政策制定者对微观数据的需求激增，特别是当数据收集是用公共资金支付时，增加了人们对保密保护的担忧。 答复保密是数据收集机构对研究参与者做出的严肃承诺。任何向研究人员和政策制定者传播数据的机构都应该做出类似的承诺。随着对微数据的需求不断增加，许多包含姓名、地址和人口统计信息等识别信息的商业数据库也变得可访问。这些数据库引起了人们的担忧，即入侵者可能会将数据收集机构发布的供公众使用的匿名调查数据与商业数据库联系起来，以识别调查的一个或多个受访者。本研究计划有三个主要目标： (1) 评估风险 使用来自涵盖广泛主题的四项试验台国家概率调查的数据进行披露。将使用两大类入侵者模型来解决风险。 I 类，入侵者认识的个人参与了调查；第二类，可以访问包含姓名和地址的外部数据库的入侵者正在寻求识别调查中的受访者的身份，从而获得机密信息； (2) 开发和评估避免披露的新方法，以及 (3) 制定策略，用摘要变量替换公共使用数据集中被认为增加披露风险的变量，允许用户在不知道这些变量实际值的情况下调整或控制这些变量。