Privacy preservation for data cubes

Sam Y. Sung, Yao Liu, Hui Xiong, Peter A. Ng

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)38-61
Number of pages24
JournalKnowledge and Information Systems
Volume9
Issue number1
DOIs
StatePublished - Jan 2006

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Human-Computer Interaction
  • Hardware and Architecture
  • Artificial Intelligence

Keywords

  • OLAP
  • Privacy preservation
  • Random data distortion
  • Range query

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