Abstract
The problem of limiting the disclosure of information gathered on a set of companies or individuals (the “respondents”) is considered, the aim being to provide useful information while preserving confidentiality of sensitive information. The paper proposes a method which explicitly preserves certain information contained in the data. The data are assumed to consist of two sets of information on each “respondent”: public data and specific survey data. It is assumed in this paper that both sets of data are liable to be released for a subset of respondents. However, the public data will be altered in some way to preserve confidentiality whereas the specific survey data is to be disclosed without alteration. The paper proposes a model based approach to this problem by utilizing the information contained in the sufficient statistics obtained from fitting a model to the public data by conditioning on the survey data. Deterministic and stochastic variants of the method are considered.
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Burridge, J. Information preserving statistical obfuscation. Statistics and Computing 13, 321–327 (2003). https://doi.org/10.1023/A:1025658621216
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DOI: https://doi.org/10.1023/A:1025658621216