Package | Description |
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org.deidentifier.arx |
This package provides the public API for the ARX anonymization framework.
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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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org.deidentifier.arx.gui.model |
Class and Description |
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PrivacyCriterion
An abstract base class for privacy criteria.
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SampleBasedCriterion
An abstract base class for sample-based privacy criteria.
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Class and Description |
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AverageReidentificationRisk
This criterion ensures that an estimate for the average re-identification risk falls
below a given threshold.
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BasicBLikeness
Basic-beta-Likeness:
Jianneng Cao, Panagiotis Karras: Publishing Microdata with a Robust Privacy Guarantee VLDB 2012. |
DDisclosurePrivacy
Delta-disclosure privacy as proposed in:
Justin Brickell and Vitaly Shmatikov: The Cost of Privacy: Destruction of Data-mining Utility in Anonymized Data Publishing Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2008 |
DistinctLDiversity
The distinct l-diversity privacy criterion.
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DPresence
The d-presence criterion
Published in:
Nergiz M, Atzori M, Clifton C.
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EDDifferentialPrivacy
(e,d)-Differential Privacy implemented with SafePub as proposed in:
Bild R, Kuhn KA, Prasser F.
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EnhancedBLikeness
Enhanced-beta-Likeness:
Jianneng Cao, Panagiotis Karras: Publishing Microdata with a Robust Privacy Guarantee VLDB 2012. |
EntropyLDiversity
The entropy l-diversity privacy model.
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EntropyLDiversity.EntropyEstimator
Enumerator of entropy estimators for the entropy-l-diversity privacy model.
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EqualDistanceTCloseness
The t-closeness criterion with equal-distance EMD.
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ExplicitPrivacyCriterion
A privacy criterion that is explicitly bound to a sensitive attribute.
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HierarchicalDistanceTCloseness
The t-closeness criterion with hierarchical-distance EMD.
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ImplicitPrivacyCriterion
A privacy criterion that is implicitly bound to the quasi-identifiers.
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KAnonymity
The k-anonymity criterion
Published in:
Sweeney L.
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KMap
This class implements the k-map privacy model as proposed by Latanya Sweeney.
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KMap.CellSizeEstimator
Estimators for cell sizes in the population.
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LDiversity
An abstract base class for l-diversity criteria
Published in:
Machanavajjhala A, Kifer D, Gehrke J.
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OrderedDistanceTCloseness
The t-closeness criterion for ordered attributes.
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PopulationUniqueness
This criterion ensures that the population uniqueness falls below a given threshold.
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PrivacyCriterion
An abstract base class for privacy criteria.
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ProfitabilityJournalist
Privacy model for the game theoretic approach proposed in:
A Game Theoretic Framework for Analyzing Re-Identification Risk.
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ProfitabilityProsecutor
Privacy model for the game theoretic approach proposed in:
A Game Theoretic Framework for Analyzing Re-Identification Risk.
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ProfitabilityProsecutorNoAttack
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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RecursiveCLDiversity
The recursive-(c,l)-diversity criterion.
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RiskBasedCriterion
Abstract class for criteria that ensure that a certain risk measure is lower than or equal to a given threshold
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SampleBasedCriterion
An abstract base class for sample-based privacy criteria.
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SampleUniqueness
This criterion ensures that the sample uniqueness falls below a given threshold.
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TCloseness
An abstract base class for t-closeness criteria as proposed in:
Li N, Li T, Venkatasubramanian S.
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Class and Description |
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KMap.CellSizeEstimator
Estimators for cell sizes in the population.
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PrivacyCriterion
An abstract base class for privacy criteria.
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