A semantic-based k-anonymity scheme for health record linkage

Abstract

Record linkage is a technique for integrating data from sources or providers where direct access to the data is not possible due to security and privacy considerations. This is a very common scenario for medical data, as patient privacy is a significant concern. To avoid privacy leakage, researchers have adopted kanonymity to protect raw data from re-identification however they cannot avoid associated information loss, e.g. due to generalisation. Given that individual-level data is often not disclosed in the linkage cases, but yet remains potentially rediscoverable, we propose semantic-based linkage k-anonymity to de-identify record linkage with fewer generalisations and eliminate inference ..