Strategies for measuring risk in public use microdata files

Abstract
Statistical agencies have the responsibility to design data release strategies which will not violate pledges of nondisclosure either through intent or neglect. In addition to ethical and legal concerns, statistical offices must be mindful that violating pledges of confidentiality may undermine an agency's ability to collect data due to loss of public trust. Statistical organizations also have the obligation to make information available to a variety of individuals and institutions to allow for informed discussion from differing perspectives on a range of issues. However, it is through fine, accurate detail on a file that risks of disclosure arise. In this report we discuss strategies for controlling risk in the release of public use microdata files. The equivalence class structure of a microdata file is defined and we show how the classic entropy function can be employed on the equivalence class structure to provide a measure of relative risk.

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