It has been demonstrated that malicious users can infer sensitive knowledge from online corporate databases and data cubes that do not adopt effective privacy preserving countermeasures. From this breaking evidence, a plethora of Privacy Preserving Data Mining (PPDM) techniques has been proposed during the last years. Each of these techniques focuses on supporting the privacy preservation of a specialized KDD/DM task such as frequent item set mining, clustering etc. Privacy Preserving OLAP (PPOLAP) is a specific PPDM technique dealing with the privacy preservation of data cubes.
