Digital Government:

Project Update - March 2006

Accepted Tentatively for Publication

• Alan F. Karr, William J. Fulp, Xiaodong Lin, Jerome P. Reiter, Francisco Vera, S. Stanley Young (2005). Secure, Privacy-Preserving Analysis of Distributed Databases. Submitted to special issue of Technometrics on information technology.

Revised Paper Accepted for Publication

• Stephen E. Fienberg (2006). "Privacy and Confidentiality in an E-Commerce World: Data Mining, Data Warehousing, Matching, and Disclosure Limitation." To appear in special issue of Statistical Science on E-Commerce.

Appeared in Print

• Daniel Ting, Stephen E. Fienberg, and Mario Trottini (2006). “ROMM Methodology for Microdata Release, ” Proceedings of UNECE/Eurostat Work Session on Statistical Data Confidentiality, Geneva, Switzerland, November 9-11, 2005, in Monographs in Official Statistics, Eurostat, Luxemburg, 89–98.
  
  
• Mario Trottini (2006). “Statistical disclosure limitation in longitudinal linked microdata: Objectives and attributes,” Proceedings of UNECE/Eurostat Work Session on Statistical Data Confidentiality, Geneva, Switzerland, November 9-11, 2005, in Monographs in Official Statistics, Eurostat, Luxemburg, 165-173.
  

At the Institute for Digital Research and Education, UCLA, February 13, 2006

• George T. Duncan: Statistical Confidentiality: Is Synthetic Data the Answer?

At the mid-program workshop of the data confidentiality working group of the SAMSI 2005 program on national defense and homeland security, NCHS, March 13, 2006

• Lawrence H. Cox, NCHS: Mathematical Models for Data Confidentiality Problems
  
  
• Aleksandra B. Slavkovic, Penn State: Algebraic Statistics for Statistical Disclosure Limitation in Contingency Tables
  
  
• Lisa Denogean, SAMSI: A Stochastic Process Approach to the Analysis of Swapping for Categorical Variables
  
  
• Jay J. Kim, NCHS: Effects of Rounding on Data Quality
  
  
• Anna Oganian, NISS: Combinations of SDC Methods for Continuous Microdata
  
  
• Mi-Ja Woo, NISS: New Measures of Data Utility
  
  
• Francisco Vera, NISS and SAMSI: Secure Statistics Software for Horizontally Partitioned Data