Do you need to remove the individualizing characteristics in your files
so that a person or item stored in the original field cannot be identified?
Once anonymized, the data
cannot be linked to any source. The benefit of anonymization over filtering and encrypting is that
the original field layout (position, size, and data type) can remain the same, and look realistic
in test data environments.
Solutions:
With either IRI's FieldShield package or CoSortSortCL tool, you can
obfuscate or masks sensitive files at the field level. Methods include:
• using expressions and functions on numeric fields
• byte-shifting, data manipulation, or conversion
• masking real characters with alternate characters
• transforming data with your own field functions
The method you choose will determine the appearance of the anoymized fields
and the likelihood of recovering the field values. And remember, these techniques
are among several other choices that both FieldShield and SortCL provide for protecting data at risk,
including encryption, de-identification, and pseudonymization.
In addition to masking real data, IRI also has a standalone solution for creating realistic test data. The RowGen (test data) package uses the same metadata as SortCL to either randomly generate realistic, or select real, data. The RowGen product is especially useful if you need to provide anonymous data in custom file formats but do have have access to the actual data.
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