Companies are often stuck with outdated legacy anonymization techniques.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.
