ksb.csle.didentification.verification.check
Checks the anonymized dataframe satisfies the given l-Diversity constraint.
Checks the anonymized dataframe satisfies the given l-Diversity constraint.
The anonymized dataframe
Boolean return true if satisfying the given l-diversity constraint
The common L-diversity method just checks whether the number of sensitive attributes is greater than given L-constraints.
The common L-diversity method just checks whether the number of sensitive attributes is greater than given L-constraints. Generally, an equivalence class is l-diverse if contains at least 'l' well-represented values for the sensitive attribute. A table is l-diverse if every equivalence is l-diverse
The anonymized dataframe
Double return the l-diversity value
This class is a base class to check whether the anonymized data satisfies the T-closeness constraints.