Static Data Anonymization Part I: Multidimensional Data
Nataraj Venkataramanan, Ashwin Shriram · 2016
In Chapter 1, we looked at various data structures such as multidimensional data, graph data, longitudinal data, transactional data, and time series data. We also understood what attributes in these data structures are to be anonymized. In this chapter, we look at how to effectively anonymize data, anonymization algorithms, quality aspects of algorithms, and privacy versus utility features. This book deals with two main applications of static data anonymization-privacy preserving data mining (PPDM) and privacy preserving test data management (PPTDM)—while the focus is on the study of various anonymization techniques in these application areas.