Rohit Goel, Mahesh Kumar
Online analytical processing (OLAP) is one of the most popular decision support and knowledge discovery techniques in business-intelligence systems.There are issues related to the protection of private information in Online Analytical Processing (OLAP) systems, where a major privacy concern is the adversarial inference of private information from OLAP query answers. This inference problem cannot be fully addressed by access control and data sanitization techniques.