Linking Sensitive Data: Methods and Techniques for Practical Privacy-Preserving Information Sharing

Linking records across organizations can make research and public services more informative—but it also raises a hard question: how can useful matches be made without unnecessarily exposing the personal information behind them? Linking Sensitive Data brings the technical methods, privacy risks, regulatory context, and practical trade-offs of that problem into one detailed treatment.

Across fourteen chapters, Peter Christen, Thilina Ranbaduge, and Rainer Schnell explain privacy-preserving record linkage: identifying records that refer to the same person or entity while limiting the sharing of sensitive values. The book is aimed at researchers and practitioners who need to understand not only how linkage methods work, but how to assess their performance and risks in real settings.

From privacy principles to working methods

The discussion starts with the purpose and challenges of linking sensitive databases, including data quality and the regulatory frameworks that shape information sharing. It then develops the technical foundations: protocols for sharing data, ways to assess privacy and risk, and methods for encoding and comparing sensitive values.

Bloom filters—and the risks they bring

A substantial section examines Bloom filter-based encoding, a widely used approach to privacy-preserving linkage. The authors cover how it is applied, where it has limitations, and how cryptanalysis attacks can seek to recover encoded values. Hardening techniques are discussed alongside those attacks, keeping the security analysis connected to the method’s practical use.

Putting linkage into practice

Privacy is only part of the implementation challenge. The book also addresses computational efficiency, blocking and indexing, parallel and distributed computing, and linkage across multiple databases. Practical chapters consider dirty, incomplete, missing, heterogeneous, temporal, and dynamic data, followed by empirical evaluation and real-world applications.

For researchers and data stewards

This reference is suited to applied scientists, data practitioners, and advanced readers in computer science and related fields who work with sensitive administrative, commercial, or medical data. Its coverage also gives decision-makers and data custodians a structured view of the choices involved in sharing and linking records while managing privacy and risk.

The result is a technically grounded guide to a consequential task: making data linkable for legitimate analysis without treating confidentiality as an afterthought.