Abstract
It is now generally accepted that the measurement of statistical disclosure risk should be carried out with reference to the data environment into which a proposed dataset is to be released. This is normally considered through the development of intrusion or attack scenarios. Elliot and Dale’s (1999) scheme set out a general set of principles for a scenario analysis, the output of which was a set of key variables. In this paper we outline an empirically based method, Data Environment Analysis which operationalises these ideas and a prototype tool the Key Variable Mapping System which has been designed to produce lists of key variables, with much more precise specification than was previously possible.
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© 2010 Springer-Verlag Berlin Heidelberg
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Elliot, M., Lomax, S., Mackey, E., Purdam, K. (2010). Data Environment Analysis and the Key Variable Mapping System. In: Domingo-Ferrer, J., Magkos, E. (eds) Privacy in Statistical Databases. PSD 2010. Lecture Notes in Computer Science, vol 6344. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15838-4_13
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DOI: https://doi.org/10.1007/978-3-642-15838-4_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15837-7
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