Abstract
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 [3]) 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.
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This report is released to inform interested parties of ongoing research and to encourage discussion of work in progress. The views expressed on statistical issues are those of the authors and not necessarily those of the U.S. Census Bureau.
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References
(CFS 2005) Commodity Flow Survey (CFS) Conference, Boston, Massachusetts, July 8-9 (2005), Participant research questions at http://www.trb.org/conferences/cfs/Workshop-DataProducts-Question.pdf
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© 2006 Springer-Verlag Berlin Heidelberg
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Massell, P., Zayatz, L., Funk, J. (2006). Protecting the Confidentiality of Survey Tabular Data by Adding Noise to the Underlying Microdata: Application to the Commodity Flow Survey. In: Domingo-Ferrer, J., Franconi, L. (eds) Privacy in Statistical Databases. PSD 2006. Lecture Notes in Computer Science, vol 4302. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11930242_26
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DOI: https://doi.org/10.1007/11930242_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49330-3
Online ISBN: 978-3-540-49332-7
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