Precisely Answering Multi-Dimensional Range Queries without Privacy Breach

This paper studies the privacy breaches caused by multi-dimensional range (MDR) sum queries in online analytical processing (OLAP) systems. We show that existing inference control methods are generally infeasible for controlling MDR queries. We then consider restricting users to even MDR queries (th...

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Bibliographic Details
Main Authors: WANG, Lingyu, LI, Yingjiu, Wijesekera, Duminda, Jajodia, Sushil
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2003
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/556
http://dx.doi.org/10.1007/b13237
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Institution: Singapore Management University
Language: English
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Summary:This paper studies the privacy breaches caused by multi-dimensional range (MDR) sum queries in online analytical processing (OLAP) systems. We show that existing inference control methods are generally infeasible for controlling MDR queries. We then consider restricting users to even MDR queries (that is, the MDR queries involving even numbers of data values). We show that the collection of such even MDR queries is safe if and only if a special set of sum-two queries (that is, queries involving exactly two values) is safe. On the basis of this result, we give an efficient method to decide the safety of even MDR queries. Besides safe even MDR queries we show that any odd MDR query is unsafe. Moreover, any such odd MDR query is different from the union of some even MDR queries by only one tuple. We also extend those results to the safe subsets of unsafe even MDR queries.