Package org.deidentifier.arx.metric.v2

Klasse MetricSDNMEntropyBasedInformationLoss

java.lang.Object

org.deidentifier.arx.metric.Metric<ILSingleDimensional>

org.deidentifier.arx.metric.v2.AbstractMetricSingleDimensional

org.deidentifier.arx.metric.v2.MetricSDNMEntropyBasedInformationLoss

Alle implementierten Schnittstellen:

Serializable

public class MetricSDNMEntropyBasedInformationLoss
extends AbstractMetricSingleDimensional

This class implements a the entropy-based information loss model proposed in:
A Game Theoretic Framework for Analyzing Re-Identification Risk. Zhiyu Wan, Yevgeniy Vorobeychik, Weiyi Xia, Ellen Wright Clayton, Murat Kantarcioglu, Ranjit Ganta, Raymond Heatherly, Bradley A. Malin PLOS|ONE. 2015.

Siehe auch:

• Serialisierte Form

Verschachtelte Klassen - Übersicht

Von Klasse geerbte verschachtelte Klassen/Schnittstellen org.deidentifier.arx.metric.Metric

Metric.AggregateFunction

Konstruktorübersicht

Konstruktoren

Konstruktor	Beschreibung
MetricSDNMEntropyBasedInformationLoss()	Creates a new instance.
MetricSDNMEntropyBasedInformationLoss(double gsFactor)	Creates a new instance.

Methodenübersicht

Modifizierer und Typ	Methode	Beschreibung
ILSingleDimensional	createMaxInformationLoss()	Returns an instance of the maximal value.
ILSingleDimensional	createMinInformationLoss()	Returns an instance of the minimal value.
MetricConfiguration	getConfiguration()	Returns the configuration of this metric.
static double	getEntropyBasedInformationLoss(org.deidentifier.arx.framework.lattice.Transformation<?> transformation, org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry entry, DomainShare[] shares, org.deidentifier.arx.framework.data.DataAggregationInformation aggregation, double maxIL)	Implements the entropy-based IL model.
static double	getMaximalEntropyBasedInformationLoss(DomainShare[] domainShares, org.deidentifier.arx.framework.data.DataAggregationInformation aggregation)	Returns the maximal entropy-based information loss
String	getName()	Returns the name of metric.
boolean	isAbleToHandleMicroaggregation()	Returns whether this metric handles microaggregation
boolean	isGSFactorSupported()	Returns whether a generalization/suppression factor is supported
ElementData	render(ARXConfiguration config)	Renders the privacy model
String	toString()	Returns the name of metric.

Von Klasse geerbte Methoden org.deidentifier.arx.metric.v2.AbstractMetricSingleDimensional

createInformationLoss, createInformationLoss

Von Klasse geerbte Methoden org.deidentifier.arx.metric.Metric

createAECSMetric, createAECSMetric, createAmbiguityMetric, createClassificationMetric, createClassificationMetric, createDiscernabilityMetric, createDiscernabilityMetric, createEntropyBasedInformationLossMetric, createEntropyBasedInformationLossMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createEntropyMetric, createHeightMetric, createHeightMetric, createInstanceOfHighestScore, createInstanceOfLowestScore, createKLDivergenceMetric, createLossMetric, createLossMetric, createLossMetric, createLossMetric, createMetric, createNormalizedEntropyMetric, createNormalizedEntropyMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecisionMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedEntropyMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedLossMetric, createPrecomputedNormalizedEntropyMetric, createPrecomputedNormalizedEntropyMetric, createPublisherPayoutMetric, createPublisherPayoutMetric, createStaticMetric, createStaticMetric, getAggregateFunction, getDescription, getGeneralizationFactor, getGeneralizationSuppressionFactor, getInformationLoss, getInformationLoss, getLowerBound, getLowerBound, getScore, getSuppressionFactor, initialize, isAbleToHandleClusteredMicroaggregation, isIndependent, isMonotonic, isMonotonicWithGeneralization, isMonotonicWithSuppression, isMultiDimensional, isPrecomputed, isScoreFunctionSupported, isWeighted, list

Von Klasse geerbte Methoden java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Konstruktordetails

MetricSDNMEntropyBasedInformationLoss

public MetricSDNMEntropyBasedInformationLoss()

Creates a new instance. Default constructor which treats all transformation methods equally.

MetricSDNMEntropyBasedInformationLoss

public MetricSDNMEntropyBasedInformationLoss(double gsFactor)

Creates a new instance.

Parameter:

gsFactor - A factor [0,1] weighting generalization and suppression. The default value is 0.5, which means that generalization and suppression will be treated equally. A factor of 0 will favor suppression, and a factor of 1 will favor generalization. The values in between can be used for balancing both methods.

Methodendetails

getEntropyBasedInformationLoss

public static double getEntropyBasedInformationLoss(org.deidentifier.arx.framework.lattice.Transformation<?> transformation,
 org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry entry,
 DomainShare[] shares,
 org.deidentifier.arx.framework.data.DataAggregationInformation aggregation,
 double maxIL)

Implements the entropy-based IL model. Ignores record suppression. Returns the loss for exactly one record.

Parameter:

transformation -

entry -

shares -

aggregation -

maxIL -

Gibt zurück:

getMaximalEntropyBasedInformationLoss

public static double getMaximalEntropyBasedInformationLoss(DomainShare[] domainShares,
 org.deidentifier.arx.framework.data.DataAggregationInformation aggregation)

Returns the maximal entropy-based information loss

Parameter:

domainShares - For generalized attributes

aggregation - For microaggregated attributes

Gibt zurück:

createMaxInformationLoss

public ILSingleDimensional createMaxInformationLoss()

Beschreibung aus Klasse kopiert: Metric

Returns an instance of the maximal value.

Setzt außer Kraft:

createMaxInformationLoss in Klasse AbstractMetricSingleDimensional

Gibt zurück:

createMinInformationLoss

public ILSingleDimensional createMinInformationLoss()

Beschreibung aus Klasse kopiert: Metric

Returns an instance of the minimal value.

Setzt außer Kraft:

createMinInformationLoss in Klasse AbstractMetricSingleDimensional

Gibt zurück:

getConfiguration

public MetricConfiguration getConfiguration()

Returns the configuration of this metric.

Setzt außer Kraft:

getConfiguration in Klasse Metric<ILSingleDimensional>

Gibt zurück:

getName

public String getName()

Beschreibung aus Klasse kopiert: Metric

Returns the name of metric.

Setzt außer Kraft:

getName in Klasse Metric<ILSingleDimensional>

Gibt zurück:

isAbleToHandleMicroaggregation

public boolean isAbleToHandleMicroaggregation()

Beschreibung aus Klasse kopiert: Metric

Returns whether this metric handles microaggregation

Setzt außer Kraft:

isAbleToHandleMicroaggregation in Klasse Metric<ILSingleDimensional>

Gibt zurück:

isGSFactorSupported

public boolean isGSFactorSupported()

Beschreibung aus Klasse kopiert: Metric

Returns whether a generalization/suppression factor is supported

Setzt außer Kraft:

isGSFactorSupported in Klasse Metric<ILSingleDimensional>

Gibt zurück:

render

public ElementData render(ARXConfiguration config)

Beschreibung aus Klasse kopiert: Metric

Renders the privacy model

Angegeben von:

render in Klasse Metric<ILSingleDimensional>

Gibt zurück:

toString

public String toString()

Beschreibung aus Klasse kopiert: Metric

Returns the name of metric.

Setzt außer Kraft:

toString in Klasse Metric<ILSingleDimensional>

Gibt zurück: