Please use this identifier to cite or link to this item:
Title: The Privacy Preservation of Data Cubes
Authors: LIU YAO
Keywords: data cube, privacy preservation, data distortion, OLAP
Issue Date: 15-Jun-2006
Citation: LIU YAO (2006-06-15). The Privacy Preservation of Data Cubes. ScholarBank@NUS Repository.
Abstract: As the development of OLAP, users are not only inner analysts or managers but also customers, partners or even third parties. This makes the privacy preservation more and more important. Based on the observation that a single data item in a data cube is not likely to be accessed alone, but a number of data are often aggregated to give summaried information and the trends of database, in this thesis, we proposed two simple but effective methods to distort sensitive individual data of data cube but the summation of range query was almost remained the same as that of the original data. The experiments were done on APB benchmark data set from OLAP council. The results showed that our methods achieved better privacy preservation and better accuracy for range queries than traditional random data distortion alternatives.
Appears in Collections:Ph.D Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
PrivacyPreserationDataCubes.pdf528.94 kBAdobe PDF



Page view(s)

checked on Apr 19, 2019


checked on Apr 19, 2019

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.