Map

Goal

Use map to create a mapping file describing how production data is anonymized, in key=value pairs of the form production_data=anonymized_data.

• Use map with output to produce a mapping file containing key=value pairs resulting from an anonymization rule
• Use map with input to update a column according to the key=value pairs in the provided mapping file
• Use map with input-output to first update a column according to the mapping file, and then update the mapping file in cases there are missing key=value pairs

Warning

• Mapping files contain production data. Protect it as such.
• Run a map Work Task only once on a column of a data set
  • Running a map rule twice on the same column in the same data set may result in data integrity problems
    • the first map will work on production data, the second map will work on anonymized data
    • After the second run, in the cases of output and input-output, the mapping file created/updated will no longer properly map production values to anonymized values

Use cases for map

Use map when table values is to be anonymized equally across

• Different databases or schemas
• Different versions of the same database, e.g., equally over time
• Tables in the same database, but that are not connected properly
• Different .csv files

Encryption

You may encrypt the mapping file using the encrypted keyword, and provide your own encryption key when configuring the application.

Ano Structure and Examples

Structure

        ...
            format <format-string>
            <input-source>
                map <map-file.txt> output encrypted?
        ...
            format <format-string>
            <input-source>
                map <map-file.txt> input encrypted?
        ...
            format <format-string>
            <input-source>
                map <map-file.txt> input-output encrypted?

structure

• The type of <input-source> does not matter. It may be a file, random-[type], randomize-[type], shuffle, etc.
• The result from the <format-string> is what is stored into the mapping file as anonymized_data

Output Example

    update ADDRESS
        mask HOMEADDRESS
            format %s
            file src/main/resources/address.txt random-order
                map address_map.txt output

output

1. Creates anonymized values using values from src/main/resources/address.txt
2. Save the anonymizations as mappings of the form production_data=anonymized_data into address_map.txt

Input Example

    ...
    update ADDRESS
        mask HOMEADDRESS
            format %s
            file src/main/resources/address.txt random-order
                map address_map.txt input
    ...

input

1. Anonymize values using mappings in address_map.txt
2. If mappings does not exist, then create new anonymizations using values from the input-source src/main/resources/address.txt
   • Values created from the input source will not be stored to the mapping file. Use input-output for this.

Input-Output Example

    ...
    update ADDRESS
        mask HOMEADDRESS
            format %s
            file src/main/resources/address.txt random-order
                map address_map.txt input-output
    ...

input-output

1. Anonymize values using mappings in address_map.txt
2. If mappings does not exist, then create a new anonymizations using values from the input-source src/main/resources/address.txt
3. Update the mapping file address_map.txt with the new anonymizations

Mapping File Structure

The first two rows contain metadata about the mapping file. Further lines are anonymizations with one value per line, of the form production_data=anonymized_data.

id_number_map.txt Example

#*** identity_number ***
#Fri Oct 15 11:26:58 CEST 2021
13071311390=241360601360
17041711981=948029768029
13081310255=816447276447
29012912169=24136061360
30103011145=905948545948
26062610647=90594895948