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Erschienen in:
Revisiting Interval Protection, a.k.a. Partial Cell Suppression, for Tabular Data Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Computational Issues in the Design of Transition Probabilities and Disclosure Risk Estimation for Additive Noise

verfasst von : Sarah Giessing

Erschienen in: Privacy in Statistical Databases

Verlag: Springer International Publishing

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Abstract

The Australian Bureau of Statistics has developed an additive noise method for automatically and consistently confidentialising tables of counts ‘on the fly’. Statistical properties of the perturbation are defined by a matrix of transition probabilities. The present paper looks at mathematical and computational aspects of an approach mentioned in the literature for how to design those probabilities. In the second part, the paper proposes computation of feasibility intervals as a technique to compare the effects of different variants for post-tabular perturbative protection methods on disclosure risk and provides experimental results.

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Fußnoten
1
At its first meeting in April 2016 the European Working Group on Methodology identified “confidentiality on-the-fly” as an item to be given some priority (c.f. [4]).
 
2
As index j may take a value of zero (when a cell value is changed to zero), in the following we start counting matrix and vector indices at 0, enumerating rows and columns of the L × L matrix by 0, 1, 2, …, L−1. The number of rows and columns L, which we assume w.l.g. to be the same, differs for different set ups.
 
3
See [9] for a simple illustrative instance (i.e. the case: i = 1, D = 3), where (7) has a unique solution, if V is at least 2 and infeasible otherwise (when (6) is considered as well).
 
4
For example, in the symmetric case, with D = 5: p i(i−5) = p i(i+5) ≅ 0.0006 without the additional constraints, ≅0.009 with constraint on the diagonal element, and ≅0.01 with additional constraint on the off-diagonal elements.
 
5
Notably, the ABS Census TableBuilder product is additive in this sense, because of a subsequent algorithm implemented in the product that restores additivity to the table.
 
6
In the literature [3, 15] there is some discussion as to which extent it could be expected that solutions obtained by the shuttle algorithm coincide with the solutions that would be obtained solving the respective linear programming problems. For some (admittedly: few) test tables we have actually compared the results and found no differences.
 
7
Exact bounds were obtained for only 17 of the 31 structural types, for altogether 44 cell/equation cases. Apart from two structural types with disclosure risk indicators of 0.25 % and 0.1 % for original count sizes 3–10, indicators were at most 0.05 %. For rounding base 10, exact bounds were obtained for 20 cell/equation cases, all in the same structural type and only concerning cells with original counts >10.
 
8
In our present code the second equality constraint (g 2 (p i ) = 0, i.e. the constraint expressing the requirement that perturbations shall have a fixed variance of V) is handled as inequality constraint, defining V as an upper bound, as in most practical instances the variance of the maximum entropy solution anyway assumes the value of this parameter.
 
9
Add one element (x[j] − x[j+1]) to the vector constr for each index j pointing to the right hand side of the distribution. Extend matrix grad by an additional column vector: The vector entries referring to indices j and j+1 should be 1 and (-1), resp. All other entries are 0.
 
10
In our implementation we have defined local_opts as the following list: “algorithm” = “NLOPT_LD_SLSQP”, “xtol_rel” = 1.0e−7, “maxeval” = 100000, and “local_opts” = local_opts, where local_opts is another list: (“algorithm” = “NLOPT_LD_MMA”,“xtol_rel” = 1.0e−7)
 
Literatur
1.
2.
Buzzigoli, L., Giusti, A.: An algorithm to calculate the lower and upperbounds of the elements of an array given its marginals. In: Statistical Data Protection (SDP 1998) Proceedings, Eurostat, Luxembourg, pp. 131–147 (1998)
3.
Buzzigoli, L., Giusti, A.: Disclosure control on multi-way tables by means of the shuttle algorithm: extensions and experiences. In: Bethlehem, J.G., van derHejden, P.G.M. (eds.) Computational Statistics 2000, COMPSTAT Proceedings in Computational Statistics 200. Physica-Verlag, Heidelberg
4.
EUROSTAT, Methodology for Statistics Unit B1: Minutes of the Working Group on Methodology, 7 April 2016
5.
Fischetti, M., Salazar-González, J.J.: Models and algorithms for optimizing cell suppression problem in tabular data with linear constraints. J. Am. Stat. Assoc. 95, 916–928 (2000)CrossRef
6.
Fraser, B., Wooton, J.: A proposed method for confidentialising tabular output to protect against differencing. In: Monographs of Official Statistics, Work session on Statistical Data Confidentiality, Eurostat-Office for Official Publications of the European Communities, Luxembourg, pp. 299–302 (2006)
7.
Giessing, S.: Anonymisierung von Fallzahltabellen durch Rundung. In: Paper presented at the Sitzung des Arbeitskreises für Fragen der mathematischen Methodik am 17.06.1991 in Wiesbaden (in German), Statistisches Bundesamt
8.
Giessing, S.: Report on issues in the design of transition probabilities and disclosure risk estimation for additive noise. Statistisches Bundesamt (Unpublished manuscript)
9.
Giessing, S., Höhne, J.: Eliminating small cells from census counts tables: some considerations on transition probabilities. In: Domingo-Ferrer, J., Magkos, E. (eds.) PSD 2010. LNCS, vol. 6344, pp. 52–65. Springer, Heidelberg (2010)CrossRef
10.
Hundepool, A., Domingo-Ferrer, J., Franconi, L., Giessing, S., Schulte Nordholt, E., Spicer, K., de Wolf, P.P.: Statistical Disclosure Control. Wiley, Chichester
11.
12.
Kraft, D.: A software package for sequential quadratic programming, Technical Report DFVLR-FB 88-28, Institut für Dynamik der Flugsysteme, Oberpfaffenhofen, July 1988
13.
Kraft, D.: Algorithm 733: TOMP–Fortran modules for optimal control calculations. ACM Trans. Math. Softw. 20(3), 262–281 (1994)CrossRefMATH
14.
Marley, J.K., Leaver, V.L.: A method for confidentialising user-defined tables: statistical properties and a risk-utility analysis. In: Proceedings of 58th World Statistical Congress, pp. 1072–1081 (2011)
15.
Roehrig, S.F.: Auditing disclosure in multi-way tables with cell suppression: simplex and shuttle solutions. In: Paper Presented at: Joint Statistical Meeting 1999, Baltimore, 5–12 August 1999
16.
Metadaten
Titel
Computational Issues in the Design of Transition Probabilities and Disclosure Risk Estimation for Additive Noise
verfasst von
Sarah Giessing
Copyright-Jahr
2016
Buch
Privacy in Statistical Databases

Print ISBN: 978-3-319-45380-4

Electronic ISBN: 978-3-319-45381-1

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-45381-1_18

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