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This paper presents ongoing research focused on improving the utility of dataprotected by Global Differential Privacy(DP) in the scenario of summarystatistics. Our approach is based on predictions on how an analyst will usestatistics released under DP protection, so that a developer can optimise datautility on further usage of the data in the privacy budget allocation. Thisnovel approach can potentially improve the utility of data without compromisingprivacy constraints. We also propose a metric that can be used by the developerto optimise the budget allocation process.

A proposal to increase data utility on Global Differential Privacy data based on data use predictions