Numeric (integer)
Below is a list of available numeric (integer) mask functions.
Hasher
The Hasher function uses the Hasty Pudding Cipher algorithm to create a one-to-one mapping between input and hashed values, ensuring consistent anonymization. It maintains the sign of numbers, always hashing negative values to negative outputs and positive values to positive outputs, using an internal encoding mechanism. This method ensures stable, deterministic, and repeatable transformations, making it ideal for anonymization while preserving numerical relationships. To ensure accurate ordering, please see ordering and indexing considerations.
Parameters
No parameters.
Note: The default fallback range aligns with 32-bit integer limits (-2,147,486,647 to 2,147,486,647), though actual range depends on database support. Note that 0 is never hashed.
Example
If you configure:
The results will be:
Numeric Noise
Adds noise to numeric data based on a uniform distribution, ensuring that the values are randomized while preserving the overall structure of the dataset. This is useful for anonymizing numerical fields where consistency and distribution must be maintained.
Parameters
Maximum negative noise: The smallest amount the date can be adjusted, relative to the original date.Use negative numbers to shift the date into the past.
Example: If the date part is set to "Day" and the minimum shift is set to
-5, this ensures the date will not be shifted earlier than 5 days prior to the original date.A positive number shifts the date forward.
Example: If the minimum shift is
5, the date will not shift earlier than 5 days after the original date.
Maximum positive noise: The largest amount by which the date can be adjusted from the original value.Use positive numbers to shift the date into the future.
Example: If the date part is set to "Day" and the maximum shift is set to
5, the date will not be shifted later than 5 days after the original date.
Noise type: The unit of time (Additive, Multiplicative, Absolute) that will define the granularity of the shift.Additive: If the data has a value of x, we will add random noise within the range -10% to +10% of x's absolute value.
Multiplicative: Multiply the value by a random factor within the range -5 to 5.
Absolute: Add direct random noise to the value within the range from -5 to 5.
The selected unit will be applied to both the minimum and maximum shift fields
Consistent mapping: Numeric Noise supports consistent mapping.
Example
If you configure:
The results will be:
Random Character Swap
The Random Character Swap function replaces individual characters in categorical values while preserving the structure of punctuation, spaces, and symbols. Characters are swapped within their respective categories (letters with letters, digits with digits), ensuring that the field's overall format remains usable, or in other words, the original data type and structure of each field (letters, numbers, symbols) are preserved. Note that it preserves non-alphabetic characters (e.g., punctuation, spaces).
Parameters
Consistent mapping: Random Character Swap supports consistent mapping.
Example
If you configure:
The results will be:
Last updated
Was this helpful?
