Overview of Cell Suppression Methods

Statistical agencies widely use cell suppression methods for economic censuses and establishment surveys to protect sensitive tabular data from disclosure to the public. The goal is to reduce the risk of disclosure by first identifying sensitive cells as primary suppression cells and then finding additional cells as the complementary (secondary) suppression cells to protect the primary cells against an attacker. In general, the cell suppression problems (CSP) can be described as a linear programming problems. In this paper, we review the cell suppression problem, with a focus on the network flow model of two-dimensional tables as well as the heuristic solutions and the exact optimal solutions. Applications of cell suppression methods from statistical agencies are highlighted. The extension of the solutions to high-dimensional, hierarchical, and linked tables is also discussed.