
Lineage-Preserving Anonymization of the Provenance of Collection-Based Workflows
Belhajjame, Khalid (2020), Lineage-Preserving Anonymization of the Provenance of Collection-Based Workflows, in Bonifati, Angela; Zhou, Yongluan; Salles, Marcos Antonio Vaz, Proceedings of the 23rd International Conference on Extending Database Technology, EDBT, OpenProceedings.org : Konstanz, p. 229-240. 10.5441/002/edbt.2020.21
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Type
Communication / ConférenceDate
2020Conference title
23rd International Conference on Extending Database Technology, EDBT, 2020Conference date
2020-03Conference city
CopenhagenConference country
DenmarkBook title
Proceedings of the 23rd International Conference on Extending Database Technology, EDBTBook author
Bonifati, Angela; Zhou, Yongluan; Salles, Marcos Antonio VazPublisher
OpenProceedings.org
Published in
Konstanz
ISBN
978-3-89318-083-7
Pages
229-240
Publication identifier
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Show full item recordAuthor(s)
Belhajjame, KhalidLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
We examine in this paper the problem of anonymizing the provenance of collection-oriented workflows, in which the constituent modules use and generate sets of data records. Despite their popularity, this kind of workflows has been overlooked in the literature w.r.t privacy. We, therefore, set out in this paper to examine the following questions: How the provenance of a collection-basedmodule can be anonymized? Can lineage information be preserved? Beyond a single module, how can the provenance of a whole workflow be anonymized? As well as addressing the above questions, we report on evaluation exercises that assess the effectiveness and efficiency of our solution. In particular, we tease apart the parameters that impact the quality of the obtained anonymized provenance information.Subjects / Keywords
workflowsRelated items
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