Package | Description |
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org.deidentifier.arx.criteria |
This package implements different variants of class-based privacy criteria,
such as k-anonymity, l-diversity, t-closeness and d-presence.
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Modifier and Type | Class and Description |
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class |
DPresence
The d-presence criterion
Published in:
Nergiz M, Atzori M, Clifton C.
|
class |
EDDifferentialPrivacy
(e,d)-Differential Privacy implemented with (k,b)-SDGS as proposed in:
Ninghui Li, Wahbeh H.
|
class |
Inclusion
This is a special criterion that does not enforce any privacy guarantees
but allows to define a data subset.
|
class |
KAnonymity
The k-anonymity criterion
Published in:
Sweeney L.
|
class |
KMap
This class implements the k-map privacy model as proposed by Latanya Sweeney.
As an alternative to explicitly providing data about the underlying population, cell sizes can be can be estimated with the D3 (Poisson) and D4 (zero-truncated Poisson) estimators proposed in: K. |
class |
ProfitabilityJournalist
Privacy model for the game theoretic approach proposed in:
A Game Theoretic Framework for Analyzing Re-Identification Risk.
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class |
ProfitabilityJournalistNoAttack
Privacy model for the "no-attack" variant of the game theoretic approach proposed in:
A Game Theoretic Framework for Analyzing Re-Identification Risk.
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class |
ProfitabilityProsecutor
Privacy model for the game theoretic approach proposed in:
A Game Theoretic Framework for Analyzing Re-Identification Risk.
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class |
ProfitabilityProsecutorNoAttack
Privacy model for the "no-attack" variant of the game theoretic approach proposed in:
A Game Theoretic Framework for Analyzing Re-Identification Risk.
|