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Using Noise for Disclosure Limitation of Establishment Tabular Data

Timothy Evans, Laura Zayatz, and John Slanta
Component ID: #ti332779009

Abstract

The  Bureau  of  the  Census  is  looking  into  new  methods  of  disclosure  limitation  for  use  with establishment  tabular  data. Currently  we  use  a  strategy  that  suppresses  a  cell  in  a  table  if  the publication of that cell could potentially lead to the disclosure of an individual respondent's data. As an alternative to cell suppression that would allow us to publish more data and to fulfill more requests for special tabulations, we are experimenting with adding noise to our underlying microdata. By perturbing each respondent's  data, we can provide protection to individual respondents without having to suppress cell totals.

While adding noise is a much less complicated and time-consuming procedure than cell suppression, the question remains as to the utility of the data after noise is added.  To preserve the quality of aggregate estimates that would not normally be at risk for disclosure, we tested the option of forcing estimates at  certain levels of aggregation to equal their true values before the addition of noise. Interior table cells were then raked to these aggregate cells.  In this paper we discuss the advantages and disadvantages of adding noise to microdata as compared to cell suppression, and we describe the results of using noise and raking with the Research and Development surv

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