In recent years the amount of digital data in the world has risen immensely.
But, the more information exists, the greater is the possibility of its
unwanted disclosure. Thus, the data privacy protection has become a pressing
problem of the present time. The task of individual privacy-preserving is being
thoroughly studied nowadays. At the same time, the problem of statistical
disclosure control for collective (or group) data is still open. In this paper
we propose an effective and relatively simple (wavelet-based) way to provide
group anonymity in collective data. We also provide a real-life example to
illustrate the method.Comment: 10 pages, 2 tables. Published by Springer in "Information Processing
and Management of Uncertainty in Knowledge-Based Systems. Applications". The
final publication is available at
http://www.springerlink.com/content/u701148783683775