Optimal univariate microaggregation with data suppression

Author(s)

Michael J. Laszlo, Nova Southeastern UniversityFollow
Sumitra Mukherjee, Nova Southeastern UniversityFollow

Document Type

Article

Publication Title

Journal of Systems and Software

ISSN

0164-1212

Publication Date

3-1-2013

Abstract

Microaggregation is a disclosure limitation method that provides security through k-anonymity by modifying data before release but does not allow suppression of data. We define the microaggregation problem with suppression (MPS) to accommodate data suppression, and present a polynomial-time algorithm, based on dynamic programming, for optimal univariate microaggregation with suppression. Experimental results demonstrate the practical benefits of suppressing a few carefully selected data points during microaggregation using our method.

DOI

10.1016/j.jss.2012.10.901

Volume

86

Issue

3

First Page

677

Last Page

682

NSUWorks Citation

Laszlo, Michael J. and Mukherjee, Sumitra, "Optimal univariate microaggregation with data suppression" (2013). CCE Faculty Articles. 2.
https://nsuworks.nova.edu/gscis_facarticles/2