  In the recent time, the problem of protecting privacy in statistical data
before they are published has become a pressing one. Many reliable studies have
been accomplished, and loads of solutions have been proposed. Though, all these
researches take into consideration only the problem of protecting individual
privacy, i.e., privacy of a single person, household, etc. In our previous
articles, we addressed a completely new type of anonymity problems. We
introduced a novel kind of anonymity to achieve in statistical data and called
it group anonymity. In this paper, we aim at summarizing and generalizing our
previous results, propose a complete mathematical description of how to provide
group anonymity, and illustrate it with a couple of real-life examples.
