SFour: A Protocol for Cryptographically Secure Record Linkage at Scale

Abstract

The prevalence of various (and increasingly large) datasets presents the challenging problem of discovering common entities dispersed across disparate datasets. Solutions to the private record linkage problem (PRL) aim to enable such explorations of datasets in a secure manner. A two-party PRL protocol allows two parties to determine for which entities they each possess a record (either an exact matching record or a fuzzy matching record) in their respective datasets — without revealing to one another information about any entities for which they do not both possess records. Although several solutions have been proposed to solve the PRL problem, no current solution offers a fully cryptographic security guarantee while maintaining both high accuracy of output and subquadratic runtime efficiency. To this end, we propose the first known efficient PRL protocol that runs in subquadratic time, provides high accuracy, and guarantees cryptographic security in the semi-honest security model.