Anonymization

process that removes the association between the identifying dataset and the data subject

The process in which individually identifiable data is altered in such a way that it no longer can be related back to a given individual. Among many techniques, there are three primary ways that data is anonymized. Suppression is the most basic version of anonymization and it simply removes some identifying values from data to reduce its identifiability. Generalization takes specific identifying values and makes them broader, such as changing a specific age (18) to an age range (18-24). Noise addition takes identifying values from a given data set and switches them with identifying values from another individual in that data set. Note that all of these processes will not guarantee that data is no longer identifiable and have to be performed in such a way that does not harm the usability of the data.