Disclosure Risk Assessment in Perturbative Microdata Protection

Authors:
William E. Yancey;William E. Winkler;Robert H. Creecy
Affiliations:
-;-;-
Venue:
Inference Control in Statistical Databases, From Theory to Practice
Year:
2002

Citing 1
Cited 24

A modified random perturbation method for database security

ACM Transactions on Database Systems (TODS)

Model Based Disclosure Protection

Inference Control in Statistical Databases, From Theory to Practice
Transforming data to satisfy privacy constraints

Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient multivariate data-oriented microaggregation

The VLDB Journal — The International Journal on Very Large Data Bases
Rethinking rank swapping to decrease disclosure risk

Data & Knowledge Engineering
A polynomial-time approximation to optimal multivariate microaggregation

Computers & Mathematics with Applications
Attribute selection in multivariate microaggregation

PAIS '08 Proceedings of the 2008 international workshop on Privacy and anonymity in information society
On the disclosure risk of multivariate microaggregation

Data & Knowledge Engineering
Towards the evaluation of time series protection methods

Information Sciences: an International Journal
A new framework to automate constrained microaggregation

Proceedings of the ACM first international workshop on Privacy and anonymity for very large databases
Achieving microaggregation for secure statistical databases using fixed-structure partitioning-based learning automata

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On utilizing association and interaction concepts for enhancing microaggregation in secure statistical databases

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Beyond k-Anonymity: A Decision Theoretic Framework for Assessing Privacy Risk

Transactions on Data Privacy
On the use of economic price theory to find the optimum levels of privacy and information utility in non-perturbative microdata anonymisation

Data & Knowledge Engineering
ONN the use of neural networks for data privacy

SOFSEM'08 Proceedings of the 34th conference on Current trends in theory and practice of computer science
Hybrid microdata using microaggregation

Information Sciences: an International Journal
A survey on statistical disclosure control and micro-aggregation techniques for secure statistical databases

Software—Practice & Experience - Focus on Selected PhD Literature Reviews in the Practical Aspects of Software Technology
An entropy approach to disclosure risk assessment: Lessons from real applications and simulated domains

Decision Support Systems
Statistical disclosure control methods through a risk-utility framework

PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
Combinations of SDC methods for microdata protection

PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
Optimal multivariate 2-microaggregation for microdata protection: a 2-approximation

PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
Using mahalanobis distance-based record linkage for disclosure risk assessment

PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
Improving record linkage with supervised learning for disclosure risk assessment

Information Fusion
Clustering-based categorical data protection

PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
Multivariate microaggregation by iterative optimization

Applied Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes methods for data perturbation that include rank swapping and additive noise. It also describes enhanced methods of re-identification using probabilistic record linkage. The empirical comparisons use variants of the framework for measuring information loss and re-identification risk that were introduced by Domingo-Ferrer and Mateo-Sanz.