Privacy in Statistical Databases: CASC Project Final Conference, PSD 2004, Barcelona, Spain, June 9-11, 2004. Proceedings

Sarah Giessing (auth.), Josep Domingo-Ferrer, Vicenç Torra (eds.)9783540221180, 3540221182

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.

---

Table of contents :
Front Matter….Pages –
Survey on Methods for Tabular Data Protection in ARGUS….Pages 1-13
Data Swapping: Variations on a Theme by Dalenius and Reiss….Pages 14-29
Bounds for Cell Entries in Two-Way Tables Given Conditional Relative Frequencies….Pages 30-43
A New Tool for Applying Controlled Rounding to a Statistical Table in Microsoft Excel….Pages 44-57
Getting the Best Results in Controlled Rounding with the Least Effort….Pages 58-72
Computational Experiments with Minimum-Distance Controlled Perturbation Methods….Pages 73-86
Balancing Quality and Confidentiality for Multivariate Tabular Data….Pages 87-98
Reducing the Set of Tables τ -ARGUS Considers in a Hierarchical Setting….Pages 99-109
Approaches to Identify the Amount of Publishable Information in Business Surveys through Waivers….Pages 110-120
Maximum Utility-Minimum Information Loss Table Server Design for Statistical Disclosure Control of Tabular Data….Pages 121-135
A Fast Network Flows Heuristic for Cell Suppression in Positive Tables….Pages 136-148
On the Security of Noise Addition for Privacy in Statistical Databases….Pages 149-161
Microaggregation for Categorical Variables: A Median Based Approach….Pages 162-174
Evaluating Fuzzy Clustering Algorithms for Microdata Protection….Pages 175-186
To Blank or Not to Blank? A Comparison of the Effects of Disclosure Limitation Methods on Nonlinear Regression Estimates….Pages 187-200
Outlier Protection in Continuous Microdata Masking….Pages 201-215
Re-identification Methods for Masked Microdata….Pages 216-230
Masking and Re-identification Methods for Public-Use Microdata: Overview and Research Problems….Pages 231-246
A Bayesian Hierarchical Model Approach to Risk Estimation in Statistical Disclosure Limitation….Pages 247-261
Individual Risk Estimation in μ -Argus: A Review….Pages 262-272
Analysis of Re-identification Risk Based on Log-Linear Models….Pages 273-281
New Approaches to Confidentiality Protection: Synthetic Data, Remote Access and Research Data Centers….Pages 282-289
Multiply-Imputing Confidential Characteristics and File Links in Longitudinal Linked Data….Pages 290-297
Fast Generation of Accurate Synthetic Microdata….Pages 298-306
Trade-Off between Disclosure Risk and Information Loss Using Multivariate Microaggregation: A Case Study on Business Data….Pages 307-322
The ARGUS Software in the CASC-Project….Pages 323-335
Different Grades of Statistical Disclosure Control Correlated with German Statistics Law….Pages 336-342
Developing Adoptable Disclosure Protection Techniques: Lessons Learned from a U.S. Experience….Pages 343-352
Privacy Preserving and Data Mining in an On-Line Statistical Database of Additive Type….Pages 353-365
Back Matter….Pages –