Maximum utility-minimum information loss table server design for statistical disclosure control of tabular data

Abstract

Statistical agencies typically serve a diverse group of end users with varying information needs. Accommodating the conflicting needs for information in combination with stringent rules for statistical disclosure limitation (SDL) of statistical information creates a special challenge. We provide a generic table server design for SDL of tabular data to meet this challenge. Our table server design works equally well with counts data and magnitude data, and is compatible with commonly used cell perturbation methods and cell suppression methods used for the statistical disclosure control of sensitive tabular data. We demonstrate the scope and the effectiveness of our table server design on counts and magnitude data by using a simplified controlled tabular adjustment procedure proposed by Dandekar (2003). In addition to ad hoc queries, the information compiled using our table server design could be used to capture multi-way interactions of counts data and magnitude data either in a static environment or in dynamic mode.