Privacy preserving record linkage with ppjoin

Abstract

Privacy-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.