Engineering privacy requirements in business intelligence applications

Annamaria Chiasera, Fabio Casati, Florian Daniel, Yannis Velegrakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)


In this paper we discuss the problem of engineering privacy requirements for business intelligence applications, i.e., of eliciting, modeling, testing, and auditing privacy requirements imposed by the source data owner on the business intelligence applications that use these data to compute reports for analysts. We describe the peculiar challenges of this problem, propose and evaluate different solutions for eliciting and modeling such requirements, and make the case in particular for what we experienced as being the most promising and realistic approach: eliciting and modeling privacy requirements on the reports themselves, rather than on the source or as part of the data warehouse.

Original languageEnglish
Title of host publicationSecure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings
Number of pages10
Volume5159 LNCS
Publication statusPublished - 2008
Externally publishedYes
Event5th VLDB Workshop on Secure Data Management, SDM 2008 - Auckland, New Zealand
Duration: 24 Aug 200824 Aug 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5159 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference5th VLDB Workshop on Secure Data Management, SDM 2008
CountryNew Zealand


  • Business intelligence
  • Compliance
  • Meta-reports
  • Outsourcing
  • Privacy
  • Provenance
  • Reports

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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