Christopher Clifton (Purdue University)
Several aspects of the current American Community Survey processing pipeline pose challenges for differential privacy. We will briefly review some of these challenges, and in particular look at missing data imputation. We present a method for differentially private nearest-neighbor imputation that addresses one of these challenges based on the concept and method of smooth sensitivity.
This work supported by the U.S. Census Bureau under CRADA CB16ADR0160002. The views and opinions expressed in this talk are those of the authors and not the U.S. Census Bureau.