Survey on Privacy Preservation for Inference Control on OLAP
Maulik Joshi, Chetna Chand
Privacy, preserving, OLAP, inference problem
Online analytical processing (OLAP) is working on analysis of multidimensional data cube and it is support decision making and knowledge discovery technique. Privacy preserving is important in OLAP because private information can be shown through user query. So adversarial inference of private information its main issue in OLAP. privacy preserving OLAP had focused on single aggregate function but it is not consider important class of privacy breaches and partial information has been generated .In this paper proposed technique provide protection for exact and partial disclosure in OLAP with more than one aggregate function with reducing processing time of OLAP cube.