org.deidentifier.arx.examples.Example49.java Source code

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Here is the source code for org.deidentifier.arx.examples.Example49.java

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/*
 * ARX: Powerful Data Anonymization
 * Copyright 2012 - 2018 Fabian Prasser 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.examples;

import java.io.File;
import java.io.FilenameFilter;
import java.io.IOException;
import java.nio.charset.StandardCharsets;
import java.util.regex.Matcher;
import java.util.regex.Pattern;

import org.apache.mahout.math.Arrays;
import org.deidentifier.arx.ARXAnonymizer;
import org.deidentifier.arx.ARXConfiguration;
import org.deidentifier.arx.ARXCostBenefitConfiguration;
import org.deidentifier.arx.ARXLattice.ARXNode;
import org.deidentifier.arx.ARXResult;
import org.deidentifier.arx.AttributeType.Hierarchy;
import org.deidentifier.arx.Data;
import org.deidentifier.arx.DataHandle;
import org.deidentifier.arx.criteria.ProfitabilityProsecutorNoAttack;
import org.deidentifier.arx.io.CSVHierarchyInput;
import org.deidentifier.arx.metric.Metric;
import org.deidentifier.arx.metric.v2.MetricSDNMPublisherPayout;
import org.deidentifier.arx.metric.v2.QualityMetadata;

/**
 * Examples of using the no-attack variant of the game-theoretic approach for 
 * performing a monetary cost/benefit analysis using prosecutor risk.
 *
 * @author Fabian Prasser
 */
public class Example49 extends Example {

    /**
     * Loads a dataset from disk
     * @param dataset
     * @return
     * @throws IOException
     */
    public static Data createData(final String dataset) throws IOException {

        Data data = Data.create("data/" + dataset + ".csv", StandardCharsets.UTF_8, ';');

        // Read generalization hierarchies
        FilenameFilter hierarchyFilter = new FilenameFilter() {
            @Override
            public boolean accept(File dir, String name) {
                if (name.matches(dataset + "_hierarchy_(.)+.csv")) {
                    return true;
                } else {
                    return false;
                }
            }
        };

        // Create definition
        File testDir = new File("data/");
        File[] genHierFiles = testDir.listFiles(hierarchyFilter);
        Pattern pattern = Pattern.compile("_hierarchy_(.*?).csv");
        for (File file : genHierFiles) {
            Matcher matcher = pattern.matcher(file.getName());
            if (matcher.find()) {
                CSVHierarchyInput hier = new CSVHierarchyInput(file, StandardCharsets.UTF_8, ';');
                String attributeName = matcher.group(1);
                data.getDefinition().setAttributeType(attributeName, Hierarchy.create(hier.getHierarchy()));
            }
        }

        return data;
    }

    /**
     * Entry point.
     *
     * @param args the arguments
     * @throws IOException
     */
    public static void main(String[] args) throws IOException {

        // Load the dataset
        Data data = createData("adult");

        // Config from PLOS|ONE paper
        solve(data, ARXCostBenefitConfiguration.create().setAdversaryCost(4d).setAdversaryGain(300d)
                .setPublisherLoss(300d).setPublisherBenefit(1200d));

        // Fewer costs
        solve(data, ARXCostBenefitConfiguration.create().setAdversaryCost(2d).setAdversaryGain(600d)
                .setPublisherLoss(300d).setPublisherBenefit(1200d));

        // More costs, more gain
        solve(data, ARXCostBenefitConfiguration.create().setAdversaryCost(1d).setAdversaryGain(1200d)
                .setPublisherLoss(300d).setPublisherBenefit(1200d));

    }

    /**
     * Solve the privacy problem
     * @param data
     * @param config
     * @throws IOException
     */
    private static void solve(Data data, ARXCostBenefitConfiguration config) throws IOException {

        // Release
        data.getHandle().release();

        // Configure
        ARXConfiguration arxconfig = ARXConfiguration.create();
        arxconfig.setCostBenefitConfiguration(config);

        // Create model for measuring publisher's benefit
        MetricSDNMPublisherPayout maximizePublisherPayout = Metric.createPublisherPayoutMetric(false);

        // Create privacy model for the game-theoretic approach
        ProfitabilityProsecutorNoAttack profitability = new ProfitabilityProsecutorNoAttack();

        // Configure ARX
        arxconfig.setSuppressionLimit(1d);
        arxconfig.setQualityModel(maximizePublisherPayout);
        arxconfig.addPrivacyModel(profitability);

        // Anonymize
        ARXAnonymizer anonymizer = new ARXAnonymizer();
        ARXResult result = anonymizer.anonymize(data, arxconfig);
        ARXNode node = result.getGlobalOptimum();
        DataHandle handle = result.getOutput(node, false).getView();

        // Print stuff
        System.out.println("Data: " + data.getHandle().getView().getNumRows() + " records with "
                + data.getDefinition().getQuasiIdentifyingAttributes().size() + " quasi-identifiers");
        System.out.println(" - Configuration: " + config.toString());
        System.out.println(" - Policies available: " + result.getLattice().getSize());
        System.out.println(" - Solution: " + Arrays.toString(node.getTransformation()));
        System.out.println("   * Optimal: " + result.getProcessStatistics().getStep(0).isOptimal());
        System.out.println("   * Time needed: " + result.getTime() + "[ms]");
        for (QualityMetadata<?> metadata : node.getLowestScore().getMetadata()) {
            System.out.println("   * " + metadata.getParameter() + ": " + metadata.getValue());
        }
        System.out.println("   * Suppressed records: "
                + handle.getStatistics().getEquivalenceClassStatistics().getNumberOfOutlyingTuples());

    }
}