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Exact(20)
The given data set D is sorted with respect to the sensitive attribute value SA.
Here, the account balance is considered as sensitive attribute and others are non-sensitive.
The problem with this method is that it depends upon the range of sensitive attribute.
In the Obvious Guess attack, an adversary may easily guess the sensitive attribute, without having to identify the record.
MDSBA presumes a table model with a set of Q-IDs and one sensitive attribute (S), known by a Class.
Formally, let C be a sensitive attribute of a dataset that can be filled with d possible discrete values.
Similar(40)
Sensitive attributes are private and personal information.
Explicit Identifiers (EID), Quasi Identifiers (QID), Sensitive Attributes (SA) and Non-Sensitive Attributes (NSA) are different classifiers of the attributes.
For a partially synthetic data set, these values would usually correspond to all the values of non-sensitive attributes and to non-sensitive values of sensitive attributes.
Consider a table T contains no sensitive attributes (such as the voter list).
Notice that in the provider-side case, sensitive attributes are fetched from the tenant.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com