Sehili, ZiadRohde, FlorensFranke, MartinRahm, ErhardKai-Uwe SattlerMelanie HerschelWolfgang Lehner2021-03-162021-03-162021978-3-88579-705-0https://dl.gi.de/handle/20.500.12116/35796We propose and evaluate several approaches for multi-party privacy-preserving record linkage (MP-PPRL) for multiple data sources. To reduce the number of comparisons for scalability we propose a new pivot-based metric space approach that dynamically adapts the selection of pivots for additional sources and growing data volume. We investigate so-called early and late clustering schemes that either cluster matching records per additional source or holistically for all sources. A comprehensive evaluation for different datasets confirms the high effectiveness and efficiency of the proposed methods.enPrivacy Preserving Record LinkageBloom filtermetric spacetriangle inequalityClustering10.18420/btw2021-131617-5468