Package org.deidentifier.arx.criteria

Klasse EntropyLDiversity

java.lang.Object

org.deidentifier.arx.criteria.PrivacyCriterion

org.deidentifier.arx.criteria.ExplicitPrivacyCriterion

org.deidentifier.arx.criteria.LDiversity

org.deidentifier.arx.criteria.EntropyLDiversity

Alle implementierten Schnittstellen:

Serializable

public class EntropyLDiversity
extends LDiversity

The entropy l-diversity privacy model.

Siehe auch:

• Serialisierte Form

Verschachtelte Klassen - Übersicht

Verschachtelte Klassen

Modifizierer und Typ	Klasse	Beschreibung
static enum	EntropyLDiversity.EntropyEstimator	Enumerator of entropy estimators for the entropy-l-diversity privacy model.

Feldübersicht

Von Klasse geerbte Felder org.deidentifier.arx.criteria.LDiversity

l, minSize

Von Klasse geerbte Felder org.deidentifier.arx.criteria.ExplicitPrivacyCriterion

attribute, index

Konstruktorübersicht

Konstruktoren

Konstruktor	Beschreibung
EntropyLDiversity(String attribute, double l)	Creates a new instance of the entropy l-diversity model as proposed in: Machanavajjhala A, Kifer D, Gehrke J. l-diversity: Privacy beyond k-anonymity. Transactions on Knowledge Discovery from Data (TKDD). 2007;1(1):3.
EntropyLDiversity(String attribute, double l, EntropyLDiversity.EntropyEstimator estimator)	Creates a new instance of the entropy-l-diversity privacy model, specifying the entropy estimator be to used.

Methodenübersicht

Modifizierer und Typ	Methode	Beschreibung
EntropyLDiversity	clone()	Clone
EntropyLDiversity.EntropyEstimator	getEstimator()	Returns the entropy estimator used by this instance
boolean	isAnonymous(org.deidentifier.arx.framework.lattice.Transformation<?> node, org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry entry)	Implement this, to enforce the criterion.
boolean	isLocalRecodingSupported()	Returns whether the criterion supports local recoding.
ElementData	render()	Renders the privacy model
String	toString()	Returns a string representation.

Von Klasse geerbte Methoden org.deidentifier.arx.criteria.LDiversity

getL, getMinimalClassSize, getRequirements, getRiskThresholdJournalist, getRiskThresholdMarketer, getRiskThresholdProsecutor, isMinimalClassSizeAvailable

Von Klasse geerbte Methoden org.deidentifier.arx.criteria.ExplicitPrivacyCriterion

getAttribute, initialize

Von Klasse geerbte Methoden org.deidentifier.arx.criteria.PrivacyCriterion

clone, getDataSubset, getPopulationModel, getSubset, isHeuristicSearchSupported, isHeuristicSearchWithTimeLimitSupported, isMonotonicWithGeneralization, isMonotonicWithSuppression, isOptimalSearchSupported, isSampleBased, isSubsetAvailable

Von Klasse geerbte Methoden java.lang.Object

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

Konstruktordetails

EntropyLDiversity

public EntropyLDiversity(String attribute,
 double l)

Creates a new instance of the entropy l-diversity model as proposed in:
Machanavajjhala A, Kifer D, Gehrke J. l-diversity: Privacy beyond k-anonymity.
Transactions on Knowledge Discovery from Data (TKDD). 2007;1(1):3.

Parameter:

attribute -

l -

EntropyLDiversity

public EntropyLDiversity(String attribute,
 double l,
 EntropyLDiversity.EntropyEstimator estimator)

Creates a new instance of the entropy-l-diversity privacy model, specifying the entropy estimator be to used. Two estimators are available:

• SHANNON for the usual naive Shannon estimator: this amounts to the original entropy-l-diversity definition by Machanavajjhala.
• GRASSBERGER for the corrected Grassberger estimator as proposed in: P Grassberger. Entropy Estimates from Insufficient Samplings. https://arxiv.org/abs/physics/0307138v2
  This estimator generally accepts more sets as being entropy-l-diverse than the naive Shannon estimator, thus increases data utility. It also guarantees a more consistent meaning of the security parameter l between different data sets. For details take a look at: S Stammler, S Katzenbeisser, K Hamacher. Correcting Finite Sampling Issues in Entropy l-diversity. Privacy in Statistical Databases 2016. LNCS Vol. 9867 pp 135-146

Parameter:

attribute - The sensitive attribute

l - Security parameter

estimator - Entropy estimator (SHANNON or GRASSBERGER)

Methodendetails

clone

public EntropyLDiversity clone()

Beschreibung aus Klasse kopiert: PrivacyCriterion

Clone

Angegeben von:

clone in Klasse PrivacyCriterion

getEstimator

public EntropyLDiversity.EntropyEstimator getEstimator()

Returns the entropy estimator used by this instance

Gibt zurück:

isAnonymous

public boolean isAnonymous(org.deidentifier.arx.framework.lattice.Transformation<?> node,
 org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry entry)

Beschreibung aus Klasse kopiert: PrivacyCriterion

Implement this, to enforce the criterion.

Angegeben von:

isAnonymous in Klasse PrivacyCriterion

Parameter:

node - TODO

entry -

Gibt zurück:

isLocalRecodingSupported

public boolean isLocalRecodingSupported()

Beschreibung aus Klasse kopiert: PrivacyCriterion

Returns whether the criterion supports local recoding.

Angegeben von:

isLocalRecodingSupported in Klasse PrivacyCriterion

Gibt zurück:

render

public ElementData render()

Beschreibung aus Klasse kopiert: PrivacyCriterion

Renders the privacy model

Angegeben von:

render in Klasse PrivacyCriterion

Gibt zurück:

toString

public String toString()

Beschreibung aus Klasse kopiert: PrivacyCriterion

Returns a string representation.

Angegeben von:

toString in Klasse PrivacyCriterion

Gibt zurück: