Companies are often stuck with outdated legacy anonymization techniques. However, these old data anonymization tools not only destroy data utility but also endanger privacy.

Upgrading your data anonymization toolset to a synthetic data generator brings many advantages. Privacy-by-design is only one of them.

The data anonymization guide introduces common legacy anonymization techniques and how they compare to synthetic data. The guide discusses the following data anonymization tools:

  • data masking,
  • pseudonymization,
  • encryption,
  • randomization,
  • permutation,
  • generalization.

In this ebook, you'll not only learn why these tools are decreasing data utility and increasing privacy risks, but also find recommendations for replacing them state-of-the-art privacy-enhancing technologies, like homomorphic encryption, federated learning, secure multi-party computation, differential privacy and AI-generated synthetic data.