Abstract
In this paper, we consider how the security of a disclosure control mechanism based on randomised, but uncontrolled, rounding can be assessed by Bayesian methods. We develop a methodology, based on Markov chain Monte Carlo, for estimating the conditional (posterior) probability distribution for the original cell counts given the released rounded values. An effective rounding-based disclosure control will result in high posterior uncertainty about the true value. Conversely, a posterior distribution concentrated on a single value provides evidence of ineffective disclosure control.
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Forster, J.J., Gill, R.C. (2008). Bayesian Assessment of Rounding-Based Disclosure Control. In: Domingo-Ferrer, J., Saygın, Y. (eds) Privacy in Statistical Databases. PSD 2008. Lecture Notes in Computer Science, vol 5262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87471-3_5
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DOI: https://doi.org/10.1007/978-3-540-87471-3_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87470-6
Online ISBN: 978-3-540-87471-3
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