A modified random perturbation method for database security
ACM Transactions on Database Systems (TODS)
Practical Data-Oriented Microaggregation for Statistical Disclosure Control
IEEE Transactions on Knowledge and Data Engineering
Microdata Protection through Noise Addition
Inference Control in Statistical Databases, From Theory to Practice
Random-data perturbation techniques and privacy-preserving data mining
Knowledge and Information Systems
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Statistical agencies release microdata to researchers after applying statistical disclosure control (SDC) methods. Noise addition is a perturbative SDC method which is carried out by adding independent random noise to a continuous variable or by misclassifying values of a categorical variable according to a probability mechanism. Because these errors are purposely introduced into the data by the statistical agency, the perturbation parameters are known and can be used by researchers to adjust statistical inference through measurement error models. However, statistical agencies rarely release perturbation parameters and therefore modifications to SDC methods are proposed that a priori ensure valid inferences on perturbed datasets.