| Complementary Cell Suppression for Statistical Disclosure Control in Tabular Data with Linear Constraints (2007) | |||||||||||||||
Abstract | |||||||||||||||
| In this paper we provide new theoretical models and practical solution techniques for protecting condentiality in statistical tables containing sensitive information that cannot be disseminated. This is an issue of primary importance in practice. In particular, we study the problem of protecting sensitive information in a statistical table whose entries are subject to any system of linear constraints. This very general setting covers, among others, k-dimensional tables with marginals as well as hierarchical and linked tables. In particular, we address the NP-hard problem known in the literature as the (complementary) Cell Suppression Problem. We propose a new integer Linear Programming (LP) model, and give an interesting interpretation of the (possibly fractional) optimal solution of its pure LP relaxation, in terms of range protection as opposed to cell suppression. We also describe additional inequalities used to strengthen the integer model. We introduce an eective branch-and-cut algorithm for the exact solution of the problem, which can also be used as a heuristic procedure to nd near-optimal solutions. Preliminary computational results are promising. | |||||||||||||||
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