On assessing the disclosure risk of controlled adjustment methods for statistical tabular data
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Cita com:
hdl:2117/17954
Tipus de documentReport de recerca
Data publicació2012-08
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
Minimum distance controlled tabular adjustment is a recent
perturbative approach
for statistical disclosure control in tabular data. Given a
table to be protected, it looks for
the closest safe table, using some particular distance. Con
trolled adjustment is known to
provide high data utility. However, the disclosure risk has
only been partially analyzed
using theoretical results from optimization. This work ext
ends these previous results,
providing both a more detailed theoretical analysis, and an
extensive empirical assess-
ment of the disclosure risk of the method. A set of 25 instance
s from the literature and
four different attacker scenarios are considered, with sever
al random replications for each
scenario, both for
L
1
and
L
2
distances. This amounts to the solution of more than 2000
optimization problems. The analysis of the results shows th
at the approach has low dis-
closure risk when the attacker has no good information on the
bounds of the optimization
problem. On the other hand, when the attacker has good estima
tes of the bounds, and
the only uncertainty is in the objective function (which is a
very strong assumption),
the disclosure risk of controlled adjustment is high and it s
hould be avoided.
CitacióCastro, J. "On assessing the disclosure risk of controlled adjustment methods for statistical tabular data". DR 2012/07 ed. 2012.
Forma partTechnical Report DR 2012/07 UPC-EIO
URL repositori externhttp://www-eio.upc.es/~jcastro/publications/reports/dr2012-07.pdf
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