Engineering privacy requirements in business intelligence applications

Annamaria Chiasera, Fabio Casati, Florian Daniel, Yannis Velegrakis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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 language	English
Title of host publication	Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings
Pages	219-228
Number of pages	10
Volume	5159 LNCS
DOIs	https://doi.org/10.1007/978-3-540-85259-9_15
Publication status	Published - 2008
Externally published	Yes
Event	5th VLDB Workshop on Secure Data Management, SDM 2008 - Auckland, New Zealand Duration: 24 Aug 2008 → 24 Aug 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5159 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	5th VLDB Workshop on Secure Data Management, SDM 2008
Country	New Zealand
City	Auckland
Period	24.8.08 → 24.8.08

Fingerprint

Keywords

Business intelligence
Compliance
Meta-reports
Outsourcing
Privacy
Provenance
Reports

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Cite this

Chiasera, A., Casati, F., Daniel, F., & Velegrakis, Y. (2008). Engineering privacy requirements in business intelligence applications. In Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings (Vol. 5159 LNCS, pp. 219-228). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5159 LNCS). https://doi.org/10.1007/978-3-540-85259-9_15

Engineering privacy requirements in business intelligence applications. / Chiasera, Annamaria; Casati, Fabio; Daniel, Florian; Velegrakis, Yannis.

Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings. Vol. 5159 LNCS 2008. p. 219-228 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5159 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chiasera, A, Casati, F, Daniel, F & Velegrakis, Y 2008, Engineering privacy requirements in business intelligence applications. in Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings. vol. 5159 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5159 LNCS, pp. 219-228, 5th VLDB Workshop on Secure Data Management, SDM 2008, Auckland, New Zealand, 24.8.08. https://doi.org/10.1007/978-3-540-85259-9_15

Chiasera A, Casati F, Daniel F, Velegrakis Y. Engineering privacy requirements in business intelligence applications. In Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings. Vol. 5159 LNCS. 2008. p. 219-228. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-85259-9_15

Chiasera, Annamaria ; Casati, Fabio ; Daniel, Florian ; Velegrakis, Yannis. / Engineering privacy requirements in business intelligence applications. Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings. Vol. 5159 LNCS 2008. pp. 219-228 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Access to Document

10.1007/978-3-540-85259-9_15