Abstract

This paper is concerned with the problem of balancing the competing objectives of allowing statistical analysis of confidential data while maintaining standards of privacy and confidentiality. Remote analysis servers have been proposed as a way to address this problem by delivering results of statistical analyses without giving the analyst any direct access to data. Several national statistical agencies operate successful remote analysis servers, see for example [1,12].Remote analysis servers are not free from disclosure risk, and current implementations address this risk by “confidentialising” the underlying data and/or by denying some queries. In this paper we explore the alternative solution of “confidentialising” the output of a server so that no confidential information is revealed or can be inferred.In this paper we first review relevant results on remote analysis servers, and provide an explicit list of measures for confidentialising the output from a single regression query to a remote server, as suggested by Sparks et al. [22,23]. We give details of a fully worked example, and compare the confidentialised output from the query to a remote server with the output from a traditional statistical package.KeywordsRemote access facilitiesremote serveranalysis servermodel serverconfidentiality

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