This monograph is a comprehensive treatment of statistical disclosure control (SDC) for microdata, covering the full pipeline from measuring disclosure risk to applying anonymisation methods and assessing the resulting information loss. It brings together methods for both categorical and continuous variables — including k-anonymity, recoding and local suppression, microaggregation, noise addition, and synthetic data — and explains when each is appropriate. Every method is accompanied by reproducible R code, much of it built on the author’s sdcMicro and simPop packages, so readers can apply the techniques to their own data. Published by Springer, it serves as both a textbook and a practitioner’s reference for anonymising confidential microdata.