Randomizing, A Practical Method for Protecting Statistical Databases Against Compromise

This paper reports on a method for protecting statistical databases against inference, developed over the past four years. The method, called randomizing, is conceptually elegant, easy to implement at very small additional cost, and requires no on-going maintenance. It can be equally applied to small and medium-size as well as large databases, because it does not depend on sampling techniques in the conventional sense. Thus we feel that randomizing is an eminently practical and effective method if the protection of statistical data against inference is of concern.