A new method to protect privacy in data cubes

Abstract

Toprotect privacy while providing analysis on information is one of the most important issues in online analytic processing systems. One of the challenges is to prevent derivation of sensitive cases through non sensitive accumulated data. This article presents and proves a new algorithm to prevent deriving due to hiding extra data and also data itself which these extra data are necessary and efficient. based on this, this approach can provide the most information to the user and protect security. This strategy doed not effect on online running in online analytic processing system. Conducted analysises and emperical comparison indicate efficiency and possibility of forbidden minimal covering