Privacy Model

If you are interrested in the theory behind each privacy models, you can read about it here: https://arx.deidentifier.org/overview/privacy-criteria/

class pyarxaas.privacy_models.KAnonymity(k)

Configuration class for K-Anonymity

Parameters:k – Value of K to anonymize the dataset. K must have a value of 2 or higher to take effect.

class pyarxaas.privacy_models.LDiversityDistinct(l, column_name)

Configuration class for Distinct L-Diversity

Parameters:

• l – Value of L to anonymize the dataset based on a column or dataset field that has a sensitive attribute. L must have a value of 2 or higher to take effect.
• column_name – Column or dataset field that has a sensitive attribute type.

class pyarxaas.privacy_models.LDiversityGrassbergerEntropy(l, column_name)

Configuration class for Grassberger Entropy L-Diversity

Parameters:

• l – Value of L to anonymize the dataset based on a column or dataset field that has a sensitive attribute. L must have a value of 2 or higher to take effect.
• column_name – Column or dataset field that has a sensitive attribute type.

class pyarxaas.privacy_models.LDiversityRecursive(l, c, column_name)

Configuration class for Recursive L-Diversity

Parameters:

• l – Value of L to anonymize the dataset based on a column or dataset field that has a sensitive attribute. L must have a value of 2 or higher to take effect.
• c – Value of C to anonymize the dataset based on a column or dataset field that has a sensitive attribute. c must have a value of 0.00001 or higher to take effect.
• column_name – Column or dataset field that has a sensitive attribute type.

class pyarxaas.privacy_models.LDiversityShannonEntropy(l, column_name)

Configuration class for Shannon Entropy L-Diversity

Parameters:

• l – Value of L to anonymize the dataset based on a column or dataset field that has a sensitive attribute. L must have a value of 2 or higher to take effect.
• column_name – Column or dataset field that has a sensitive attribute type.

class pyarxaas.privacy_models.PrivacyModel

Documentation of the privacy models implemented in the ARXaaS service and the definition of the parameters each privacy model takes.

class pyarxaas.privacy_models.TClosenessEqualDistance(t, column_name)

Configuration class for Equal Distance T-Closeness

Parameters:

• t – Value of T to anonymize the dataset based on a column or dataset field that has a sensitive attribute. T must have a value between 0.000001 to 1.0
• column_name – Column or dataset field that has a sensitive attribute type.

class pyarxaas.privacy_models.TClosenessOrderedDistance(t, column_name)

Configuration class for Ordered Distance T-Closeness

Parameters:

• t – Value of T to anonymize the dataset based on a column or dataset field that has a sensitive attribute. T must have a value between 0.000001 to 1.0
• column_name – Column or dataset field that has a sensitive attribute type.