Privacy in Statistical Databases

1. Front Matter

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2. Foundations of Tabular Protection

   1. Survey on Methods for Tabular Data Protection in ARGUS

      • Sarah Giessing

      Pages 1-13

   2. Data Swapping: Variations on a Theme by Dalenius and Reiss

      • Stephen E. Fienberg, Julie McIntyre

      Pages 14-29

   3. Bounds for Cell Entries in Two-Way Tables Given Conditional Relative Frequencies

      • Aleksandra B. Slavkovic, Stephen E. Fienberg

      Pages 30-43

3. Methods for Tabular Protection

   1. A New Tool for Applying Controlled Rounding to a Statistical Table in Microsoft Excel

      • Juan-José Salazar-González, Markus Schoch

      Pages 44-57

   2. Getting the Best Results in Controlled Rounding with the Least Effort

      • Juan-José Salazar-González, Philip Lowthian, Caroline Young, Giovanni Merola, Stephen Bond, David Brown

      Pages 58-72

   3. Computational Experiments with Minimum-Distance Controlled Perturbation Methods

      • Jordi Castro

      Pages 73-86

   4. Balancing Quality and Confidentiality for Multivariate Tabular Data

      • Lawrence H. Cox, James P. Kelly, Rahul Patil

      Pages 87-98

   5. Reducing the Set of Tables τ -ARGUS Considers in a Hierarchical Setting

      • Peter-Paul de Wolf, Anneke Loeve

      Pages 99-109

   6. Approaches to Identify the Amount of Publishable Information in Business Surveys through Waivers

      • Jean-Sébastien Provençal, Hélène Bérard, Jean-Marc Fillion, Jean-Louis Tambay

      Pages 110-120

   7. Maximum Utility-Minimum Information Loss Table Server Design for Statistical Disclosure Control of Tabular Data

      • Ramesh A. Dandekar

      Pages 121-135

   8. A Fast Network Flows Heuristic for Cell Suppression in Positive Tables

      • Jordi Castro

      Pages 136-148

4. Masking for Microdata Protection

   1. On the Security of Noise Addition for Privacy in Statistical Databases

      • Josep Domingo-Ferrer, Francesc Sebé, Jordi Castellà-Roca

      Pages 149-161

   2. Microaggregation for Categorical Variables: A Median Based Approach

      • Vicenç Torra

      Pages 162-174

   3. Evaluating Fuzzy Clustering Algorithms for Microdata Protection

      • Vicenç Torra, Sadaaki Miyamoto

      Pages 175-186

   4. To Blank or Not to Blank? A Comparison of the Effects of Disclosure Limitation Methods on Nonlinear Regression Estimates

      • Sandra Lechner, Winfried Pohlmeier

      Pages 187-200

   5. Outlier Protection in Continuous Microdata Masking

      • Josep Maria Mateo-Sanz, Francesc Sebé, Josep Domingo-Ferrer

      Pages 201-215

5. Risk in Microdata Protection

   1. Re-identification Methods for Masked Microdata

      • William E. Winkler

      Pages 216-230

   2. Masking and Re-identification Methods for Public-Use Microdata: Overview and Research Problems

      • William E. Winkler

      Pages 231-246

   3. A Bayesian Hierarchical Model Approach to Risk Estimation in Statistical Disclosure Limitation

      • Silvia Polettini, Julian Stander

      Pages 247-261

Privacy in statistical databases is about ?nding tradeo?s to the tension between the increasing societal and economical demand for accurate information and the legal and ethical obligation to protect the privacy of individuals and enterprises, which are the source of the statistical data. Statistical agencies cannot expect to collect accurate information from individual or corporate respondents unless these feel the privacy of their responses is guaranteed; also, recent surveys of Web users show that a majority of these are unwilling to provide data to a Web site unless they know that privacy protection measures are in place. “Privacy in Statistical Databases2004” (PSD2004) was the ?nal conference of the CASC project (“Computational Aspects of Statistical Con?dentiality”, IST-2000-25069). PSD2004 is in the style of the following conferences: “Stat- tical Data Protection”, held in Lisbon in 1998 and with proceedings published by the O?ce of O?cial Publications of the EC, and also the AMRADS project SDC Workshop, held in Luxemburg in 2001 and with proceedings published by Springer-Verlag, as LNCS Vol. 2316. The Program Committee accepted 29 papers out of 44 submissions from 15 di?erentcountriesonfourcontinents.Eachsubmittedpaperreceivedatleasttwo reviews. These proceedings contain the revised versions of the accepted papers. These papers cover the foundations and methods of tabular data protection, masking methods for the protection of individual data (microdata), synthetic data generation, disclosure risk analysis, and software/case studies.

• anonymity
• bayesian model
• clustering
• data analysis
• data masking
• data mining
• data security
• database
• inference control
• privacy
• statistical confidentiality
• statistical databases
• statistical disclosure control
• tabular protection

• Department of Computer Engineering and Mathematics, Universitat Rovira i Virgili, UNESCO Chair in Data Privacy, Tarragona

  Josep Domingo-Ferrer

• IIIA, Artificial Intelligence Research Institute CSIC, Spanish National Research Council, Bellaterra, Spain

  Vicenç Torra

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