Encryption is the process of transforming information into a meaningless "ciphertext" form. Only those with the proper key can decrypt and read the information. CoSort's SortCL tool now has the ability to encrypt data at the field level while manipulating one or more sequential files of any size or format. You can use SortCL's built-in 256-bit Advanced Encryption Standard (AES) algorithm, or link in your own encryption and decryption routine as a custom, field-level transformation. You can use different encryption keys or routines on different fields at the same time, as your security rules require.


Masking: Anonymization & Pseudonymization
Obfuscate Fields with Gibberish or Mask Them with Lookup Values

Data masking refers generically to any process that replaces real data with fake data. CoSort’s SortCL tool can mask data through anonymization and pseudonymization, as well as through data-type conversion, alternate character masking, and custom, field-level transformations.

Anonymization is the process of removing information from a data source (e.g. file) that can be used to backtrack to an actual person. Once anonymized, the data cannot be linked to any source. Unlike filtering and encryption, this technique allows the original field layout (position, size, and data type) to remain the same, and look realistic in test data environments. CoSort’s SortCL tool can obfuscate fields using the other techniques listed above, as well as through random (safe test) data generation, mathematical expressions, character shifting and bit manipulation.

Pseudonymization is the process of replacing a personally identifiable field (like a patient's name) in a data record with an artificial identifier (a pseudonym). Unlike anonymization, this technique allows data to be traced back to its origin, and the resulting hash or lookup value can appear very real. SortCL uses lookup files to substitute pseudonyms for real field values.

De-Identification & Re-Identification
CoSort's SortCL Also Includes Field Encoding and Decoding

De-identifcation is the process of removing personally identifying data from a record. In the medical and insurance industries, HIPAA regulations require the protection of both obvious and remotely connected patient information. CoSort's SortCL tool can also de-identify field data with a special encoding routine where the code holder can re-identify the field. To re-identify the field, specify the same code in another job script. De-identification can also occur through the techniques above or through filtering (described below).


Filtering (Redaction)
Just Don't Output the Sensitive Fields

Filtering is the process of removing (redacting) those fields or records within your input files that do not need to be in the load files, hand-offs, or custom report formats that SortCL can output. Specify only the output fields you desire, or use condition logic to filter records, according to you business rules.


Safe Test Data
Randomly Generate or Select Field Values Instead

Safe test data is different than traditional test data, which are inherently unsafe snippets of real production files or tables. The test data generated by CoSort V9's SortCL tool, or the CoSort Test Data (RowGen) product, looks real, but is safe because it comes from random value generation and/or randomized lookups. Simultaneous transformation and custom reporting of the test data is also possible, and the metadata is the same between products. You can therefore use your file layouts for both data transformation and test data generation.


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