Anonymization

concept · part of Responsible AI

Techniques like data masking, pseudonymization, and differential privacy applied to PII before training.

Inside Anonymization (4)

Data masking — A technique that alters data to hide original content while preserving usability for testing or development.
k-anonymity — An anonymization technique that ensures each individual's data cannot be distinguished from at least k-1 others.
l-diversity — An anonymization technique that ensures sensitive attributes have at least l distinct values within each equivalence class.
t-closeness — An anonymization technique that ensures the distribution of a sensitive attribute in any equivalence class is close to its global distribution.

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