Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
Privacy in e-commerce: examining user scenarios and privacy preferences
Proceedings of the 1st ACM conference on Electronic commerce
Practical Data-Oriented Microaggregation for Statistical Disclosure Control
IEEE Transactions on Knowledge and Data Engineering
Disclosure Risk Assessment in Perturbative Microdata Protection
Inference Control in Statistical Databases, From Theory to Practice
Information preserving statistical obfuscation
Statistics and Computing
Probabilistic Information Loss Measures in Confidentiality Protection of Continuous Microdata
Data Mining and Knowledge Discovery
A Framework for Evaluating Privacy Preserving Data Mining Algorithms*
Data Mining and Knowledge Discovery
An epistemic framework for privacy protection in database linking
Data & Knowledge Engineering
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
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
Constrained Microaggregation: Adding Constraints for Data Editing
Transactions on Data Privacy
A new framework to automate constrained microaggregation
Proceedings of the ACM first international workshop on Privacy and anonymity for very large databases
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
Preventing range disclosure in k-anonymised data
Expert Systems with Applications: An International Journal
Using classification methods to evaluate attribute disclosure risk
MDAI'10 Proceedings of the 7th international conference on Modeling decisions for artificial intelligence
Towards knowledge intensive data privacy
DPM'10/SETOP'10 Proceedings of the 5th international Workshop on data privacy management, and 3rd international conference on Autonomous spontaneous security
Edit constraints on microaggregation and additive noise
PSDML'10 Proceedings of the international ECML/PKDD conference on Privacy and security issues in data mining and machine learning
Distributed privacy-preserving methods for statistical disclosure control
DPM'09/SETOP'09 Proceedings of the 4th international workshop, and Second international conference on Data Privacy Management and Autonomous Spontaneous Security
Kd-trees and the real disclosure risks of large statistical databases
Information Fusion
An evolutionary optimization approach for categorical data protection
Proceedings of the 2012 Joint EDBT/ICDT Workshops
Clustering-based categorical data protection
PSD'12 Proceedings of the 2012 international conference on Privacy in Statistical Databases
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Nowadays, the need for privacy motivates the use of methods that allow to protect a microdata file both minimizing the disclosure risk and preserving the data utility. A very popular microdata protection method is rank swapping. Record linkage is the standard mechanism used to measure the disclosure risk of a microdata protection method. In this paper we present a new record linkage method, specific for rank swapping, which obtains more links than standard ones. The consequence is that rank swapping has a higher disclosure risk than believed up to now. Motivated by this, we present two new variants of the rank swapping method, which make the new record linkage technique unsuitable. Therefore, the real disclosure risk of these new methods is lower than the standard rank swapping.