/*
* ARX: Powerful Data Anonymization
* Copyright 2012 - 2017 Fabian Prasser, Florian Kohlmayer and contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.deidentifier.arx.criteria;
import org.deidentifier.arx.ARXConfiguration;
import org.deidentifier.arx.ARXCostBenefitConfiguration;
import org.deidentifier.arx.DataSubset;
import org.deidentifier.arx.certificate.elements.ElementData;
import org.deidentifier.arx.framework.check.groupify.HashGroupifyEntry;
import org.deidentifier.arx.framework.lattice.Transformation;
/**
* Privacy model for the "no-attack" variant of the game theoretic approach 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.
*
* @author Fabian Prasser
*/
public class ProfitabilityJournalistNoAttack extends ProfitabilityProsecutorNoAttack {
/** SVUID */
private static final long serialVersionUID = 1073520003237793563L;
/** The data subset */
private final DataSubset subset;
/**
* Creates a new instance
* @param subset
*/
public ProfitabilityJournalistNoAttack(DataSubset subset) {
super();
this.subset = subset;
}
@Override
public PrivacyCriterion clone() {
return new ProfitabilityJournalistNoAttack(this.subset.clone());
}
@Override
public PrivacyCriterion clone(DataSubset subset) {
throw new UnsupportedOperationException("Local recoding is not supported by this model");
}
@Override
public DataSubset getDataSubset() {
return subset;
}
@Override
public int getMinimalClassSize() {
return 0;
}
@Override
public int getRequirements() {
return ARXConfiguration.REQUIREMENT_COUNTER | ARXConfiguration.REQUIREMENT_SECONDARY_COUNTER;
}
@Override
public double getRiskThresholdJournalist() {
return super.getRiskThresholdProsecutor();
}
@Override
public double getRiskThresholdMarketer() {
return super.getRiskThresholdJournalist();
}
@Override
public double getRiskThresholdProsecutor() {
return 0d;
}
@Override
public boolean isAnonymous(Transformation node, HashGroupifyEntry entry) {
return entry.pcount >= super.getK();
}
@Override
public boolean isLocalRecodingSupported() {
return false;
}
@Override
public boolean isMinimalClassSizeAvailable() {
return false;
}
@Override
public boolean isSubsetAvailable() {
return true;
}
@Override
public ElementData render() {
ElementData result = new ElementData("No-attack profitability");
result.addProperty("Attacker model", "Journalist");
ARXCostBenefitConfiguration config = super.getConfiguration();
if (config != null) {
result.addProperty("Threshold", super.getK());
result.addProperty("Adversary cost", config.getAdversaryCost());
result.addProperty("Adversary gain", config.getAdversaryGain());
result.addProperty("Publisher loss", config.getPublisherLoss());
result.addProperty("Publisher benefit", config.getPublisherBenefit());
}
return result;
}
@Override
public String toString() {
return toString("journalist");
}
}