Privacy in Multidimensional Databases

Privacy in Multidimensional Databases

Francesco M. Malvestuto (University of Roma - La Sapienza, Italy) and Marina Moscarini (University of Roma - La Sapienza, Italy)
Copyright: © 2003 |Pages: 51
DOI: 10.4018/978-1-59140-053-0.ch011
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Abstract

When answering queries that ask for summary statistics, the query-system of a multidimensional database should guard confidential data, that is, it should avoid revealing (directly or indirectly) individual data, which could be exactly calculated or accurately estimated from the values of answered queries. In order to prevent the disclosure of confidential data, the query-system should be provided with an auditing procedure which, each time a new query is processed, checks that its answer does not allow a (knowledgeable) user to disclose any sensitive data. A promising approach consists in keeping track of (or auditing) answered queries by means a dynamic graphical data structure, here called the answer map, whose size increases with the number of answered queries and with the number of dimensions of the database, so that the problem of the existence of an efficient auditing procedure naturally arises. This chapter reviews recent results on this problem for “additive” queries (such as COUNT and SUM queries) by listing some polynomially solvable problems as well as some hard problems, and suggests directions for future work.

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Table of Contents
Preface
Maurizio Rafanelli
Chapter 1
Basic Notions  (pages 1-45)
Maurizio Rafanelli
This chapter presents the basic notions regarding multidimensional (aggregate) databases by referring to different definitions given for them in the... Sample PDF
Basic Notions
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Chapter 2
Arie Shoshani
The term “multidimensional databases” refers to data that can be viewed conceptually in a multidimensional space, where each dimension represents... Sample PDF
Multidimensionality in Statistical, OLAP and Scientific Databases
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Chapter 3
Riccardo Torlone
A variety of multidimensional data models have recently been proposed by both academic and industry communities. but consensus on formalism or even... Sample PDF
Conceptual Multidimensional Models
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Chapter 4
Hierarchies  (pages 91-115)
Elaheh Pourabbas, Maurizio Rafanelli
In this chapter we will focus on the rules of aggregation hierarchies in analysis dimensions of a cube. We give an overview of the related works on... Sample PDF
Hierarchies
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Chapter 5
Maurizio Rafanelli
In this chapter the author proposes the different approaches for defining operators able to manipulate this multidimensional structure. In... Sample PDF
Operators for Multidimensional Aggregate Data
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Chapter 6
Alberto O. Mendelzon, Alejandro A. Vaisman
In spite of the obvious importance of time in data warehousing and OLAP, current commercial systems do not support tracking the history of a data... Sample PDF
Time in Multidimensional Databases
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Chapter 7
Mirek Riedewald, Divyakant Agrawal, Amr El Abbadi
Data cubes are ubiquitous tools in data warehousing, online analytical processing, and decision support applications. Based on a selection of... Sample PDF
Dynamic Multidimensional Data Cubes
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Chapter 8
Stefano Paraboschi, Giuseppe Sindoni, Elena Baralis, Ernst Teniente
This chapter presents materialized views in the context of multidimensional databases (MDDBs). A materialized view is a view whose content is... Sample PDF
Materialized Views in Multidimensional Databases
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Chapter 9
Leonardo Tininini
A powerful and easy-to-use querying environment is certainly one of the most important components in a multidimensional database, and its... Sample PDF
Querying Multidimensional Data
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Chapter 10
Cirtis E. Dyreson, Torben Bach Pedersen, Christian S. Jensen
While incomplete information is endemic to real-world data, current multidimensional data models are not engineered to manage incomplete information... Sample PDF
Incomplete Information in Multidimensional Databases
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Chapter 11
Francesco M. Malvestuto, Marina Moscarini
When answering queries that ask for summary statistics, the query-system of a multidimensional database should guard confidential data, that is, it... Sample PDF
Privacy in Multidimensional Databases
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Chapter 12
Andrea Cali, Domenico Lembo, Maurizio Lenzerini, Riccardo Rosati
While the main goal of a data warehouse is to provide support for data analysis and management’s decisions, a fundamental aspect in design of a data... Sample PDF
Source Integration for Data Warehousing
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Chapter 13
Elaheh Pourabbas
The purpose of this chapter is to create cooperation between geographic databases (GDBs) and multidimensional databases (MDDBs), which are... Sample PDF
Cooperation with Geographic Databases
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About the Authors