We will briefly introduce the basics of category theory in order to have a self-contained talk on Graph Transformation and an application to social data anonymisation. We will present the research field of social data anonymization: Huge network data sets, like social networks (describing personal relationships and cultural preferences) or communication networks (the graph of phone calls or email correspondents) become more and more common. These data sets are analyzed in many ways varying from the study of disease transmission to targeted advertising. Selling network data set to third-parties is a significant part of the business model of major internet companies. Usually, in order to preserve the confidentiality of the sold data set, only ``anonymized'' data are released: the original social networks is modified in order to avoid re-identification. The aim is to anonymize the data while keeping its use for the analyzes. We will review the most important results in this field, and we will show how graph rewriting techniques based on category theory can be used to design a more formal approach to tackle these issues.
