Synonyms
Post-randomization method
Definition
The Post-RAndomization Method (PRAM) is a probabilistic, perturbative masking method for disclosure protection of categorical microdata. In the masked file, the scores on some categorical attributes for certain records in the original file are changed to a different score according to a prescribed probability mechanism, namely a Markov matrix. The Markov approach makes PRAM very general, because it encompasses noise addition, data suppression and data recoding.
Key Points
The PRAM matrix contains a row for each possible value of each attribute to be protected. This rules out using the method for continuous data. PRAM was invented by Gouweleeuw et~al. [1]. The information loss and disclosure risk in data masked with PRAM largely depend on the choice of the Markov matrix and are still (open) research topics [2].
Cross-References
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Gouweleeuw JM, Kooiman P, Willenborg LCRJ, DeWolf P-P. Post randomisation for statistical disclosure control: theory and implementation, 1997. Statistics Netherlands. Voorburg: Research Paper No. 9731; 1997.
de Wolf P-P. Risk, utility and PRAM. In: Domingo-Ferrer J, Franconi L, editors. Privacy in statistical databases LNCS, vol. 4302. 2006. p. 189–204.
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Domingo-Ferrer, J. (2018). PRAM. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1499
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DOI: https://doi.org/10.1007/978-1-4614-8265-9_1499
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