How to Protect Your Data With Synthetic Data

Synthetic data generation is a sophisticated approach to data anonymization that keeps the privacy of your data subjects perfectly protected. The traditional privacy risks of those legacy anonymization approaches are not present in synthetic data, only more manageable ones like attribute inference or membership inference. A good quality synthetic data generator takes care of those manageable privacy risks with all the additional privacy checks and features such as reare category protection,. And finally, let's summarize what we know about differential privacy. To put it very simple, differential privacy is the idea that one person should not influence the result of a query on a specific data set no matter whether this person was actually present in the data or not.