For decades, national statistical agencies and other data custodians have been publishing frequency tables based on census, survey and administrative data. In order to protect the confidentiality of individuals represented in the data, tables based on original data are modified before release. Recently, in response to user demand for more flexible and responsive table publication services, frequency table publication schemes have been augmented with on-line table generating servers such as the US Census Bureau FactFinder and the Australian Bureau of Statistics (ABS) TableBuilder. These systems allow users to build their own custom tables, and make use of automated perturbation routines to protect confidentiality. Motivated by the growing popularity of table generating servers, in this paper we study confidentiality protection for perturbed frequency tables, including the trade-off with analytical utility, focusing on a version of the ABS TableBuilder as a concrete example of a data release mechanism, and examining its properties. Confidentiality protection is assessed in terms of the differential privacy standard, and this paper can be used as a practical introduction to differential privacy, to calculations related to its application, to the relationship between confidentiality protection and utility and to confidentiality in general.