Contributions to record linkage for disclosure risk assessment

Abstract

This book is about reidentification methods, and, more especifically, about record linkage. This study is motivated on the need to assess in an accurate way the risk of disclosure within the fields of privacy preserving data mining (PPDM) and statistical disclosure control (SDC). Data protection methods are constructed so that disclosure is avoided when data is published. Nevertheless, before data publication, risk should be assessed as accurately as possible. Record linkage is one of the approaches to compute this risk. It is, in fact, a computational approach for risk assessment based on some assumptions about the information an intruder has. An important characteristic of record linkage methods is that they are flexible enough to be used in a large number of different scenarios. For example, they can be either used for assessing risk of data protected adding some noise, or used for assessing risk when data has been generated synthetically. In this book, record linkage methods are discussed, and new approaches are described. Specific methods are proposed. They are methods that take advantage of the available information on the protection methods. The author later shows their effectiveness in comparison to standard ones. The book also shows how the analysis of the results of risk assessment via record linkage can be used to develop new methods for data protection. In short, new data protection methods are resiliant to some of the attacks of record linkage.