Further Results on the Security of Partitioned Dynamic Statistical Databases
- Mary McLeish
- ACM Trans. Database Syst.
Inferences are of major concern for database managers, particularly in statistical data bases. This problem became apparent when it was discovered that a number of requests on a given set of data could lead to the determination of otherwise hid den data. The search for methods to protect databases from inferences led first to "tracker" type methods (or restrictive methods), and then to data perturbation methods. The intensive use of multidimensional statistical methods on databases (linear regre ssion, principal components analysis) has resulted in another important source of inferences that are difficult to detect in data bases. The objective of this paper is to present a solution for protecting data bases against inferences using data analysis methods, specifically discriminant analysis. The solution is based on the discriminanting power of each attribute in the protected data base.