What kinds of privacy protections can Gretel Synthetics help with?

Gretel-synthetics is designed to help developers and data scientists create safe, artificial datasets with many of the same insights as the original dataset, but with greater guarantees around protecting personal data or secrets in the source data. Gretel’s implementation of differential privacy helps guarantee that individual secrets or small groups of secrets, such as a credit card number inside structured and unstructured data fields will not be memorized or repeated in the synthetic dataset. Gretel’s synthetic data library also helps to defend against re-identification and joinability attacks, where traditionally anonymized data can be joined with another dataset, even ones that have not been created yet, to re-identify users.

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