Engineering privacy requirements in business intelligence applications

Annamaria Chiasera; Fabio Casati; Florian Daniel; Yannis Velegrakis

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

Engineering privacy requirements in business intelligence applications

Annamaria Chiasera^*
, Fabio Casati
, Florian Daniel
, Yannis Velegrakis

^*Corresponding author for this work

Sub Data Intensive Systems

University of Trento

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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
DOIs	https://doi.org/10.1007/978-3-540-85259-9_15
Publication status	Published - 27 Oct 2008
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/Territory	New Zealand
City	Auckland
Period	24/08/08 → 24/08/08

Keywords

Business intelligence
Compliance
Meta-reports
Outsourcing
Privacy
Provenance
Reports

Access to Document

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

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 (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

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title = "Engineering privacy requirements in business intelligence applications",

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.",

keywords = "Business intelligence, Compliance, Meta-reports, Outsourcing, Privacy, Provenance, Reports",

author = "Annamaria Chiasera and Fabio Casati and Florian Daniel and Yannis Velegrakis",

year = "2008",

month = oct,

day = "27",

doi = "10.1007/978-3-540-85259-9\_15",

language = "English",

isbn = "3540852581",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "219--228",

booktitle = "Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings",

note = "5th VLDB Workshop on Secure Data Management, SDM 2008 ; Conference date: 24-08-2008 Through 24-08-2008",

}

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. 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, 24/08/08. https://doi.org/10.1007/978-3-540-85259-9_15

Engineering privacy requirements in business intelligence applications. / Chiasera, Annamaria; Casati, Fabio; Daniel, Florian et al.
Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings. 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 › Academic › peer-review

TY - GEN

T1 - Engineering privacy requirements in business intelligence applications

AU - Chiasera, Annamaria

AU - Casati, Fabio

AU - Daniel, Florian

AU - Velegrakis, Yannis

PY - 2008/10/27

Y1 - 2008/10/27

N2 - 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.

AB - 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.

KW - Business intelligence

KW - Compliance

KW - Meta-reports

KW - Outsourcing

KW - Privacy

KW - Provenance

KW - Reports

UR - https://www.scopus.com/pages/publications/54249099152

U2 - 10.1007/978-3-540-85259-9_15

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

M3 - Conference contribution

AN - SCOPUS:54249099152

SN - 3540852581

SN - 9783540852582

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 219

EP - 228

BT - Secure Data Management - 5th VLDB Workshop, SDM 2008, Proceedings

T2 - 5th VLDB Workshop on Secure Data Management, SDM 2008

Y2 - 24 August 2008 through 24 August 2008

ER -

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. 2008. p. 219-228. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-85259-9_15

Engineering privacy requirements in business intelligence applications

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