Abstract
This peer-reviewed software paper documents sdcMicro, the R package for statistical disclosure control of microdata. It presents the package’s methods for estimating disclosure risk — including individual and global risk measures and k-anonymity — together with anonymisation techniques such as recoding, local suppression, microaggregation, and noise addition, and tools for quantifying the resulting information loss. The paper shows how the package supports a complete, reproducible anonymisation workflow on real survey data. Published in the Journal of Statistical Software, it is the standard citable reference for sdcMicro, a package used by national statistical institutes and researchers worldwide for anonymising confidential microdata.