Flossmann, Anton and Lechner, Sandra (2006) Combining blanking and noise addition as a data disclosure limitation method. In: Privacy in Statistical Databases - CENEX-SDC Project International Conference, PSD 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer-Verlag, ITA, pp. 152-163. ISBN 9783540493303
Full text not available from this repository.Abstract
Statistical disclosure limitation is widely used by data collecting institutions to provide safe individual data. In this paper, we propose to combine two separate disclosure limitation techniques blanking and addition of independent noise in order to protect the original data. The proposed approach yields a decrease in the proba bility of reidentifying/disclosing the individual information, and can be applied to linear as well as nonlinear regression models. We show how to combine the blanking method and the measurement error method, and how to estimate the model by the combination of the Simulation-Extrapolation (SIMEX) approach proposed by [4] and the Inverse Probability Weighting (IPW) approach going back to [8]. We produce Monte-Carlo evidence on how the reduction of data quality can be minimized by this masking procedure.