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Privacy preserving record linkage with ppjoin

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dc.contributor.authorSehili, Ziad
dc.contributor.authorKolb, Lars
dc.contributor.authorBorgs, Christian
dc.contributor.authorSchnell, Rainer
dc.contributor.authorRahm, Erhard
dc.contributor.editorSeidl, Thomas
dc.contributor.editorRitter, Norbert
dc.contributor.editorSchöning, Harald
dc.contributor.editorSattler, Kai-Uwe
dc.contributor.editorHärder, Theo
dc.contributor.editorFriedrich, Steffen
dc.contributor.editorWingerath, Wolfram
dc.date.accessioned2017-06-30T11:40:54Z
dc.date.available2017-06-30T11:40:54Z
dc.date.issued2015
dc.description.abstractPrivacy-preserving record linkage (PPRL) becomes increasingly important to match and integrate records with sensitive data. PPRL not only has to preserve the anonymity of the persons or entities involved but should also be highly efficient and scalable to large datasets. We therefore investigate how to adapt PPJoin, one of the fastest approaches for regular record linkage, to PPRL resulting in a new approach called P4Join. The use of bit vectors for PPRL also allows us to devise a parallel execution of P4Join on GPUs. We evaluate the new approaches and compare their efficiency with a PPRL approach based on multibit trees.en
dc.identifier.isbn978-3-88579-635-0
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2015)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-241
dc.titlePrivacy preserving record linkage with ppjoinen
dc.typeText/Conference Paper
gi.citation.endPage104
gi.citation.publisherPlaceBonn
gi.citation.startPage85
gi.conference.date2.-3. März 2015
gi.conference.locationHamburg

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