TítuloData Privacy with R
Publication TypeBook Chapter
Year of Publication2015
AuthorsAbril D, Navarro-Arribas G, Torra V
EditorNavarro-Arribas G, Torra V
Book TitleAdvanced Research in Data Privacy
Volume567
Paginación63-82
ISBN Number978-3-319-09884-5
Palabras claveDisclosure risk, Information loss, masking methods, microdata protection, privacy preserving data mining, record linkage
Resumen

Privacy Preserving Data Mining (PPDM) is an application field, which is becoming very relevant. Its goal is the study of new mechanisms which allow the dissemination of confidential data for data mining tasks while preserving individual private information. Additionally, due to the relevance of R language in the statistics and data mining communities, it is undoubtedly a good environment to research, develop and test privacy techniques aimed to data mining. In this chapter we outline some helpful tools in R to introduce readers to that field, so that we present several PPDM protection techniques as well as their information loss and disclosure risk evaluation process and outline some tools in R to help to introduce practitioners to this field.

URLhttp://dx.doi.org/10.1007/978-3-319-09885-2_5