A theoretical basis for perturbation methods
Statistics and Computing
Towards value disclosure analysis in modeling general databases
Proceedings of the 2006 ACM symposium on Applied computing
Secure and useful data sharing
Decision Support Systems
Dare to share: Protecting sensitive knowledge with data sanitization
Decision Support Systems
Minimizing Information Loss and Preserving Privacy
Management Science
Maximizing Accuracy of Shared Databases when Concealing Sensitive Patterns
Information Systems Research
Privacy Protection in Data Mining: A Perturbation Approach for Categorical Data
Information Systems Research
A polynomial-time approximation to optimal multivariate microaggregation
Computers & Mathematics with Applications
On-line data protecting via pseudo random binary sequences
CEA'07 Proceedings of the 2007 annual Conference on International Conference on Computer Engineering and Applications
Context-based market basket analysis in a multiple-store environment
Decision Support Systems
Choice and Chance: A Conceptual Model of Paths to Information Security Compromise
Information Systems Research
Why swap when you can shuffle? a comparison of the proximity swap and data shuffle for numeric data
PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
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Organizations are storing large amounts of data in databases for data mining and other types of analysis. Some of this data is considered confidential and has to be protected from disclosure. When access to individual values of confidential numerical data in the database is prevented, disclosure may occur when a snooper uses linear models to predict individual values of confidential attributes using nonconfidential numerical and categorical attributes. Hence, it is important for the database administrator to have the ability to evaluate security for snoopers using linear models. In this study we provide a methodology based on Canonical Correlation Analysis that is both appropriate and adequate for evaluating security. The methodology can also be used to evaluate the security provided by different security mechanisms such as query restrictions and data perturbation. In situations where the level of security is inadequate, the methodology provided in this study can also be used to select appropriate inference control mechanisms. The application of the methodology is illustrated using a simulated database.