A process that re-establishes, under a strict set of controls, the original values from a dataset that has been previously de-identified (masked). Typically, this involves the reversing of the tokenization of a direct identifier or the decryption of encrypted values.

Privitar supports Unmasking on a column-by-column basis. That is, it limits the operation to specific data attributes, and strictly requires special permissions to govern the process.

Various use cases rely on this ability to reverse de-identification. For example, when a follow-up is required on selected, raw records, or when moving the data between environments that require different kinds of protection from a less secure environment to a more secure one.

An example of the use of Unmasking could be for a de-identified dataset created for medical analysis in which patient identities have been obscured. As a result of the analysis, there may be a requirement to reveal some patient identities in order to contact them to arrange a medical examination or treatment.

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