Synonyms
Additive noise
Definition
Noise addition is a masking method for statistical disclosure control of numerical microdata that consists of adding random noise to original microdata.
Key Points
The noise addition algorithms in the literature are:
- 1.
Masking by uncorrelated noise addition. The vector of observations xj for the jth attribute of the original dataset Xj is replaced by a vector
$$ {z}_j={x}_j+{\upepsilon}_j $$where ɛj is a vector of normally distributed errors drawn from a random variable \( {\varepsilon}_j\sim N\left(0,{\sigma}_{\varepsilon_j}^2\right) \), such that Cov(εt, εl) = 0 for all t ≠ l. This does not preserve variances nor correlations.
- 2.
Masking by correlated noise addition. Correlated noise addition also preserves means and additionally allows preservation of correlation coefficients. The difference with the previous method is that the covariance matrix of the errors is now proportional to the covariance matrix of the original data, i.e., ε ∼ N(0, Σε),...
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Kim JJ. A method for limiting disclosure in microdata based on random noise and transformation. In: Proceedings of the Section on Survey Research Methods; 1986. p. 303–8.
Sullivan GR. The use of added error to avoid disclosure in microdata releases. PhD thesis, Iowa State University; 1989.
Brand R. Microdata protection through noise addition. In: Domingo-Ferrer J, editor. Inference control in statistical databases. LNCS, vol. 2316. Berlin: Springer; 2002. p. 97–116.
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Domingo-Ferrer, J. (2018). Noise Addition. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1495
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DOI: https://doi.org/10.1007/978-1-4614-8265-9_1495
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