Linking Sensitive Data – Applications, Techniques, and Challenges

IntroductionThe linking of sensitive databases containing personal identifying information across organisations is an increasingly important task in application domains ranging from health and social science research to national censuses. Various techniques have been developed to facilitate the linking of sensitive databases while at the same time preserving the privacy of individuals represented in these databases.
 Objectives and approachWe present several case studies where the privacy-preserving linking of sensitive databases is crucial, and then discuss the advantages and limitations of existing algorithms and techniques to link sensitive databases. We discuss privacy techniques such as Bloom filter encoding, hashing, and secure multi-party computation, from the point of view of a linkage practitioner. We highlight those aspects that are important when selecting or implementing a privacy-preserving linkage technique within practical applications.
 ResultsConceptually, linkage techniques can be evaluated across three main dimensions linkage quality, scalability to linking large or multiple databases, and the privacy protection provided by a technique. From a practical