TY - JOUR

T1 - Estimating risks of identification disclosure in partially synthetic data

AU - Reiter, Jerome P.

AU - Mitra, Robin

PY - 2009/4/1

Y1 - 2009/4/1

N2 - To limit disclosures, statistical agencies and other data disseminators can release partially synthetic, public use microdata sets. These comprise the units originally surveyed; but some collected values, for example, sensitive values at high risk of disclosure or values of key identifiers, are replaced with multiple draws from statistical models. Because the original records are on the file, there remain risks of identifications. In this paper, we describe how to evaluate identification disclosure risks in partially synthetic data, accounting for released information from the multiple datasets, the model used to generate synthetic values, and the approach used to select values to synthesize. We illustrate the computations using the Survey of Youths in Custody.

AB - To limit disclosures, statistical agencies and other data disseminators can release partially synthetic, public use microdata sets. These comprise the units originally surveyed; but some collected values, for example, sensitive values at high risk of disclosure or values of key identifiers, are replaced with multiple draws from statistical models. Because the original records are on the file, there remain risks of identifications. In this paper, we describe how to evaluate identification disclosure risks in partially synthetic data, accounting for released information from the multiple datasets, the model used to generate synthetic values, and the approach used to select values to synthesize. We illustrate the computations using the Survey of Youths in Custody.

KW - confidentiality

KW - public use data

KW - record linkage

KW - survey

M3 - Journal article

VL - 1

SP - 99

EP - 110

JO - Journal of Privacy and Confidentiality

JF - Journal of Privacy and Confidentiality

IS - 1

ER -