Privacy preservation for data cubes

Authors:
Y. Sung;Yao Liu;Hui Xiong;A. Ng
Affiliations:
Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore;Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore;MSIS Department, Rutgers University, 3 Science Drive 2, 117543, USA;Department of Computer Science, University of Texas—Pan American, 3 Science Drive 2, 117543, Edinburg, TX, USA
Venue:
Knowledge and Information Systems
Year:
2006

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Abstract

A range query finds the aggregated values over all selected cells of an online analytical processing (OLAP) data cube where the selection is specified by the ranges of contiguous values for each dimension. An important issue in reality is how to preserve the confidential information in individual data cells while still providing an accurate estimation of the original aggregated values for range queries. In this paper, we propose an effective solution, called the zero-sum method, to this problem. We derive theoretical formulas to analyse the performance of our method. Empirical experiments are also carried out by using analytical processing benchmark (APB) dataset from the OLAP Council. Various parameters, such as the privacy factor and the accuracy factor, have been considered and tested in the experiments. Finally, our experimental results show that there is a trade-off between privacy preservation and range query accuracy, and the zero-sum method has fulfilled three design goals: security, accuracy, and accessibility.