Statistical disclosure control is important for the dissemination of statistical outputs. There is an increasing need for greater confidentiality protection during data collection and processing by National Statistical Offices. In particular, various transactions and remote sensing signals are examples of useful but very detailed big data that can be highly sensitive. Moreover, possible conflicts of interest may arise for data suppliers who operate commercially. In this paper, we formulate statistical disclosure control for data collection and processing as an optimisation problem. Even when it is difficult to specify and solve the problem unequivocally, the formulation can still provide the basis for comparing different disclosure control methods. We develop a general compartmented system that adapts and implements non-perturbative methods in the related fields of linking sensitive data and secure computation. We illustrate how the system can be configured to yield variously required tables and microdata sets with sufficiently low disclosure risks.

中文翻译：

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安全的大数据收集和处理：框架、手段和机会

统计披露控制对于统计产出的传播很重要。国家统计局在数据收集和处理过程中越来越需要加强保密保护。特别是，各种交易和遥感信号是有用但非常详细且高度敏感的大数据的示例。此外，商业运营的数据供应商可能会出现利益冲突。在本文中，我们将数据收集和处理的统计披露控制制定为优化问题。即使在难以明确规定和解决问题的情况下，该表述仍然可以为比较不同的披露控制方法提供依据。我们开发了一个通用的分隔系统，该系统在链接敏感数据和安全计算的相关领域适应和实施非微扰方法。我们说明了如何配置系统以生成各种所需的表格和微数据集，同时披露风险足够低。