Inference Control in Statistical Databases From Theory to Practice

Inference Control in Statistical Databases From Theory to Practice / edited by Josep Domingo-Ferrer.

Inference control in statistical databases, also known as statistical disclosure limitation or statistical confidentiality, is about finding tradeoffs to the tension between the increasing societal need for accurate statistical data and the legal and ethical obligation to protect privacy of individu...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Domingo-Ferrer, Josep (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2002.
Edition:1st ed. 2002.
Series:Lecture Notes in Computer Science, 2316
Springer eBook Collection.
Subjects:
Computer security.
Data encryption (Computer science).
Mathematical statistics.
Database management.
Computers and civilization.
Artificial intelligence.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Advances in Inference Control in Statistical Databases: An Overview
  • Advances in Inference Control in Statistical Databases: An Overview
  • Tabular Data Protection
  • Cell Suppression: Experience and Theory
  • Bounds on Entries in 3-Dimensional Contingency Tables Subject to Given Marginal Totals
  • Extending Cell Suppression to Protect Tabular Data against Several Attackers
  • Network Flows Heuristics for Complementary Cell Suppression: An Empirical Evaluation and Extensions
  • HiTaS: A Heuristic Approach to Cell Suppression in Hierarchical Tables
  • Microdata Protection
  • Model Based Disclosure Protection
  • Microdata Protection through Noise Addition
  • Sensitive Micro Data Protection Using Latin Hypercube Sampling Technique
  • Integrating File and Record Level Disclosure Risk Assessment
  • Disclosure Risk Assessment in Perturbative Microdata Protection
  • LHS-Based Hybrid Microdata vs Rank Swapping and Microaggregation for Numeric Microdata Protection
  • Post-Masking Optimization of the Tradeoff between Information Loss and Disclosure Risk in Masked Microdata Sets
  • Software and User Case Studies
  • The CASC Project
  • Tools and Strategies to Protect Multiple Tables with the GHQUAR Cell Suppression Engine
  • SDC in the 2000 U.S. Decennial Census
  • Applications of Statistical Disclosure Control at Statistics Netherlands
  • Empirical Evidences on Protecting Population Uniqueness at Idescat.

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