choose between additive, correlated, correlated2, restr, ROMM, outdect
p
multiplication factor for method ROMM
delta
parameter for method correlated2, details can be found
in the reference below.
Value
An object of class micro with following entities:
xthe original data
xmthe modified (perturbed) data
methodmethod used for perturbation
noiseamount of noise
Details
Method additive adds noise completely at random to each variable
depending on there size and standard deviation. correlated
and method correlated2 adds noise and preserves the covariances as descriped in
R. Brand (2001) or in the reference given below.
Method restr takes the
sample size into account when adding noise.
Method ROMM is an implementation of the algorithm ROMM (Random Orthogonalized
Matrix Masking) (Fienberg, 2004).
Method outdect adds noise only to outliers.
The outliers are idedentified with univariate and robust multivariate procedures
based on a robust mahalanobis distancs calculated by the MCD estimator.
References
Domingo-Ferrer, J. and Sebe, F. and Castella, J.,
On the security of noise addition for privacy in statistical databases,
Lecture Notes in Computer Science, vol. 3050, pp. 149-161, 2004.
ISSN 0302-9743. Vol. Privacy in Statistical Databases,
eds. J. Domingo-Ferrer and V. Torra, Berlin: Springer-Verlag.
http://vneumann.etse.urv.es/publications/sci/lncs3050OntheSec.pdf,
Ting, D. Fienberg, S.E. and Trottini, M. ROMM Methodology for Microdata Release
Joint UNECE/Eurostat work session on statistical data confidentiality, Geneva, Switzerland, 2005,
http://www.niss.org/dgii/TR/wp.11.e(ROMM).pdf
Ting, D., Fienberg, S.E., Trottini, M.
Random orthogonal matrix masking methodology for microdata release,
International Journal of Information and Computer Security, vol. 2, pp. 86-105, 2008.
Templ, M. and Meindl, B.,
Robustification of Microdata Masking Methods and the Comparison
with Existing Methods,
Lecture Notes in Computer Science, Privacy in Statistical Databases,
vol. 5262, pp. 177-189, 2008.
Templ, M.
New Developments in Statistical Disclosure Control and Imputation:
Robust Statistics Applied to Official Statistics, Suedwestdeutscher Verlag fuer Hochschulschriften,
2009, ISBN: 3838108280, 264 pages.
Templ, M. and Meindl, B.:
Practical Applications in Statistical Disclosure Control Using R,
Privacy and Anonymity in Information Management Systems New Techniques for New Practical Problems,
Springer, 31-62, 2010, ISBN: 978-1-84996-237-7.