Cell suppression problem: A genetic-based approach
Computers and Operations Research
Statistical confidentiality: Optimization techniques to protect tables
Computers and Operations Research
Adjusting the τ-argus modular approach to deal with linked tables
Data & Knowledge Engineering
Three ways to deal with a set of linked SBS tables using τ-ARGUS
PSD'10 Proceedings of the 2010 international conference on Privacy in statistical databases
Scaling up a hybrid genetic linear programming algorithm for statistical disclosure control
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Harmonizing table protection: results of a study
PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
Initial application of ant colony optimisation to statistical disclosure control
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Information Sciences: an International Journal
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This paper describes a heuristic approach to find suppression patterns in tables that exhibit a hierarchical structure in at least one of the explanatory variables. The hierarchical structure implies that there exist (many) sub-totals, i.e., that (many) sub-tables can be constructed. These sub-tables should be protected in such a way that they cannot be used to undo the protection of any of the other tables. The proposed heuristic approach has a top-down structure: when a table of high level (sub-)totals is suppressed, its interior turns into the marginals of possibly several tables on a lower level. These lower level tables are then protected while keeping the marginals fixed.