Statistical Disclosure Risk: Separating Potential and Harm
Statistical Disclosure Risk: Separating Potential and Harm
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DOI：
10.1111/j.1751-5823.2012.00194.x
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发表时间：
2012-12-01
影响因子：
2
通讯作者：
Skinner, Chris
中科院分区：
文献类型：
--
作者：
Skinner, Chris
统计机构热衷于想方设法在保护机密性的同时提供研究数据访问权限。尽管统计披露风险评估方法现已在统计科学文献中得到很好的确立，但机构将这些方法整合到其实践的一般科学基础中仍然很困难。本文旨在回顾和澄清统计科学在机构决策中披露风险评估的概念基础中的作用。披露风险分为披露潜力（衡量实现真实披露的能力的指标）和披露损害。有人认为统计科学最适合评估前者。提出了该评估的框架。本文认为，只要在泄露潜力的定义中适当考虑潜在入侵者攻击的性质，入侵者的决策和行为就可以与该框架分开。
Statistical agencies are keen to devise ways to provide research access to data while protecting confidentiality. Although methods of statistical disclosure risk assessment are now well established in the statistical science literature, the integration of these methods by agencies into a general scientific basis for their practice still proves difficult. This paper seeks to review and clarify the role of statistical science in the conceptual foundations of disclosure risk assessment in an agency's decision making. Disclosure risk is broken down into disclosure potential, a measure of the ability to achieve true disclosure, and disclosure harm. It is argued that statistical science is most suited to assessing the former. A framework for this assessment is presented. The paper argues that the intruder's decision making and behaviour may be separated from this framework, provided appropriate account is taken of the nature of potential intruder attacks in the definition of disclosure potential.