Secure Data Management Technology

Abstract

In this chapter, we introduce data anonymization techniques for several types of datasets. Data anonymity of anonymized datasets is an index for estimating the (maximum) reidentification risk from anonymized datasets and is generally defined as a quantitative index based on adversary models. The adversary models are implicitly defined according to the attributes in the datasets, use cases, and anonymization techniques. We first review existing anonymization techniques and the adversary models behind the data anonymity definitions for anonymization techniques; then, we propose a common anonymity definition and its adversary model, which is applicable to several types of anonymization techniques. Furthermore, some extensions of the definition, which is optimized for specific types of datasets, are presented in the chapter.