A New Algorithm for Protecting Aggregate Business Microdata via a Remote Server
Yue Ma (University of Wollongong)
Releasing business microdata is a challenging problem for many statistical agencies. Businesses with distinct characteristics such as extremely high income could easily be identified while these businesses are normally included in surveys representing the population. In order to provide data users with useful statistics while maintain confidentiality, the Australian Bureau of Statistics has developed a remote server, called TableBuilder, that has the capability to allow users to specify and request tables created from business microdata. The TableBuilder automatically generates perturbed cell values using an perturbation algorithm. The perturbation algorithm is designed to protect against various attacks, such as differencing attack. However, the algorithm has limitations, including a limited scope of applicable cells, and time inefficiency. In this paper we introduce a new algorithm for generating perturbed cell values. The new algorithm produces results quicker, achieves better utility-disclosure tradeoffs in many cases, and is conjectured to be applicable to a wider scope of cells.