public class EDDifferentialPrivacy extends ImplicitPrivacyCriterion
Constructor and Description |
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EDDifferentialPrivacy(double epsilon,
double delta,
DataGeneralizationScheme generalization)
Creates a new instance
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EDDifferentialPrivacy(double epsilon,
double delta,
DataGeneralizationScheme generalization,
boolean deterministic)
Creates a new instance which may be configured to produce deterministic output.
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Modifier and Type | Method and Description |
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EDDifferentialPrivacy |
clone()
Clone
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double |
getBeta()
Returns the k parameter of (k,b)-SDGS
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DataSubset |
getDataSubset()
If a privacy model uses a data subset, it must overwrite this method
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double |
getDelta()
Returns the delta parameter of (e,d)-DP
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double |
getEpsilon()
Returns the epsilon parameter of (e,d)-DP
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DataGeneralizationScheme |
getGeneralizationScheme()
Returns the defined generalization scheme
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int |
getK()
Returns the k parameter of (k,b)-SDGS
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int |
getMinimalClassSize()
If a privacy model provides a prosecutor risk threshold, it should override this method to enable optimizations
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int |
getRequirements()
Returns the criterion's requirements.
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void |
initialize(DataManager manager,
ARXConfiguration config)
Creates a random sample based on beta
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boolean |
isAnonymous(Transformation node,
HashGroupifyEntry entry)
Implement this, to enforce the criterion.
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boolean |
isLocalRecodingSupported()
Returns whether the criterion supports local recoding.
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boolean |
isMinimalClassSizeAvailable()
If a privacy model provides a prosecutor risk threshold, it should override this method to enable optimizations
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boolean |
isSubsetAvailable()
If a privacy model uses a data subset, it must overwrite this method
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java.lang.String |
toString()
Returns a string representation.
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clone, getPopulationModel, getRiskThresholdJournalist, getRiskThresholdMarketer, getRiskThresholdProsecutor, getSubset, isMonotonicWithGeneralization, isMonotonicWithSuppression, isSampleBased
public EDDifferentialPrivacy(double epsilon, double delta, DataGeneralizationScheme generalization)
epsilon
- delta
- generalization
- public EDDifferentialPrivacy(double epsilon, double delta, DataGeneralizationScheme generalization, boolean deterministic)
epsilon
- delta
- generalization
- deterministic
- public EDDifferentialPrivacy clone()
PrivacyCriterion
clone
in class PrivacyCriterion
public double getBeta()
public DataSubset getDataSubset()
PrivacyCriterion
getDataSubset
in class PrivacyCriterion
public double getDelta()
public double getEpsilon()
public DataGeneralizationScheme getGeneralizationScheme()
public int getK()
public int getMinimalClassSize()
PrivacyCriterion
getMinimalClassSize
in class PrivacyCriterion
public int getRequirements()
PrivacyCriterion
getRequirements
in class PrivacyCriterion
public void initialize(DataManager manager, ARXConfiguration config)
initialize
in class PrivacyCriterion
manager
- config
- TODOpublic boolean isAnonymous(Transformation node, HashGroupifyEntry entry)
PrivacyCriterion
isAnonymous
in class PrivacyCriterion
node
- TODOpublic boolean isLocalRecodingSupported()
PrivacyCriterion
isLocalRecodingSupported
in class PrivacyCriterion
public boolean isMinimalClassSizeAvailable()
PrivacyCriterion
isMinimalClassSizeAvailable
in class PrivacyCriterion
public boolean isSubsetAvailable()
PrivacyCriterion
isSubsetAvailable
in class PrivacyCriterion
public java.lang.String toString()
PrivacyCriterion
toString
in class PrivacyCriterion