Abstract:
Data swapping is a statistical disclosure limitation method used to protect the confidentiality of data by interchanging variable values between records. We propose a risk-utility framework for selecting an optimal swapped data release when considering several swap variables and multiple swap rates. Risk and utility values associated with each such swapped data file are traded off along a frontier of undominated potential releases, which contains the optimal release(s). Current Population Survey data are used to illustrate the framework for categorical data swapping.
Keywords:
constrained swaps; data confidentiality; Hellinger distance; optimal release; risk measure; risk-utility frontier; statistical disclosure limitation; swap rate; swapping attribute; unconstrained swaps, utility measure.
tr132.pdf