Privacy in Statistical Databases : CENEX-SDC Project International Conference, PSD 2006, Rome, Italy, December 13-15, 2006, Proceedings / edited by Josep Domingo-Ferrer, Luisa Franconi.

Format:

Book

Contributor:

Domingo-Ferrer, Josep, editor.

Franconi, Luisa, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 4302.

Information Systems and Applications, incl. Internet/Web, and HCI ; 4302

Language:

English

Subjects (All):

Data encryption (Computer science).

Database management.

Mathematical statistics.

Computers and civilization.

Computers.

Law and legislation.

Artificial intelligence.

Cryptology.

Database Management.

Probability and Statistics in Computer Science.

Computers and Society.

Legal Aspects of Computing.

Artificial Intelligence.

Local Subjects:

Cryptology.

Database Management.

Probability and Statistics in Computer Science.

Computers and Society.

Legal Aspects of Computing.

Artificial Intelligence.

Physical Description:

1 online resource (XI, 383 pages).

Edition:

First edition 2006.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.

System Details:

text file PDF

Summary:

Privacy in statistical databases is a discipline whose purpose is to provide - lutions to the con?ict between the increasing social, political and economical demand of accurate information, and the legal and ethical obligation to protect the privacy of the individuals and enterprises to which statistical data refer. - yond law and ethics, there are also practical reasons for statistical agencies and data collectors to invest in this topic: if individual and corporate respondents feel their privacyguaranteed,they arelikelyto providemoreaccurateresponses. There are at least two traditions in statistical database privacy: one stems from o?cial statistics, where the discipline is also known as statistical disclosure control (SDC), and the other originates from computer science and database technology.Bothstartedinthe1970s,butthe1980sandtheearly1990ssawlittle privacy activity on the computer science side. The Internet era has strengthened the interest of both statisticians and computer scientists in this area. Along with the traditional topics of tabular and microdata protection, some research lines have revived and/or appeared, such as privacy in queryable databases and protocols for private data computation.

Contents:

Methods for Tabular Protection

A Method for Preserving Statistical Distributions Subject to Controlled Tabular Adjustment

Automatic Structure Detection in Constraints of Tabular Data

A New Approach to Round Tabular Data

Harmonizing Table Protection: Results of a Study

Utility and Risk in Tabular Protection

Effects of Rounding on the Quality and Confidentiality of Statistical Data

Disclosure Analysis for Two-Way Contingency Tables

Statistical Disclosure Control Methods Through a Risk-Utility Framework

A Generalized Negative Binomial Smoothing Model for Sample Disclosure Risk Estimation

Entry Uniqueness in Margined Tables

Methods for Microdata Protection

Combinations of SDC Methods for Microdata Protection

A Fixed Structure Learning Automaton Micro-aggregation Technique for Secure Statistical Databases

Optimal Multivariate 2-Microaggregation for Microdata Protection: A 2-Approximation

Using the Jackknife Method to Produce Safe Plots of Microdata

Combining Blanking and Noise Addition as a Data Disclosure Limitation Method

Why Swap When You Can Shuffle? A Comparison of the Proximity Swap and Data Shuffle for Numeric Data

Adjusting Survey Weights When Altering Identifying Design Variables Via Synthetic Data

Utility and Risk in Microdata Protection

Risk, Utility and PRAM

Distance Based Re-identification for Time Series, Analysis of Distances

Beyond k-Anonymity: A Decision Theoretic Framework for Assessing Privacy Risk

Using Mahalanobis Distance-Based Record Linkage for Disclosure Risk Assessment

Improving Individual Risk Estimators

Protocols for Private Computation

Single-Database Private Information Retrieval Schemes : Overview, Performance Study, and Usage with Statistical Databases

Privacy-Preserving Data Set Union

"Secure" Log-Linear and Logistic Regression Analysis of Distributed Databases

Case Studies

Measuring the Impact of Data Protection Techniques on Data Utility: Evidence from the Survey of Consumer Finances

Protecting the Confidentiality of Survey Tabular Data by Adding Noise to the Underlying Microdata: Application to the Commodity Flow Survey

Italian Household Expenditure Survey: A Proposal for Data Dissemination

Software

The ARGUS Software in CENEX

Software Development for SDC in R

On Secure e-Health Systems

IPUMS-International High Precision Population Census Microdata Samples: Balancing the Privacy-Quality Tradeoff by Means of Restricted Access Extracts.

Other Format:

Printed edition:

ISBN:

978-3-540-49332-7

9783540493327

Access Restriction:

Restricted for use by site license.