Abstract
Microdata protection by adding noise is being discussed for more than 20 years now. Several algorithms were developed that have different characteristics. The simplest algorithm consists of adding white noise to the data. More sophisticated methods use more or less complex transformations of the data and more complex error-matrices to improve the results. This contribution gives an overview over the different algorithms and discusses their properties in terms of analytical validity and level of protection. Therefore some theoretical considerations are shown and an illustrating empirical example is given.
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Brand, R. (2002). Microdata Protection through Noise Addition. In: Domingo-Ferrer, J. (eds) Inference Control in Statistical Databases. Lecture Notes in Computer Science, vol 2316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47804-3_8
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DOI: https://doi.org/10.1007/3-540-47804-3_8
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