Protecting the Confidentiality of Survey Tabular Data by Adding Noise to the Underlying Microdata: Application to the Commodity Flow Survey

摘要

The Commodity Flow Survey (CFS) produces data on the movement of goods in the United States. The data from the CFS are used by analysts for transportation modeling, planning and decision-making. Cell suppression has been used over the years to protect responding companies' values in CFS data. Data users, especially transportation modelers, would like to have access to data tables that do not have missing data due to suppression. To meet this need, we are testing the application of a noise protection method (Evans et al) that involves adding noise to the underlying CFS microdata prior to tabulation to protect sensitive cells in CFS tables released to the public. Initial findings of this research have been positive. This paper describes detailed analyses that may be performed to evaluate the effectiveness of the noise protection.