Identifying inference attacks against healthcare data repositories
Identifying inference attacks against healthcare data repositories
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发表时间：
2013-03
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通讯作者：
Jaideep Vaidya;Basit Shafiq;Xiaoqian Jiang;L. Ohno-Machado
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作者：
Jaideep Vaidya;Basit Shafiq;Xiaoqian Jiang;L. Ohno-Machado
医疗保健数据存储库在推动医学研究进步方面发挥着重要作用。寻找新的发现途径需要有足够的数据和相关分析。然而，确保存储数据的隐私和安全至关重要。在本文中，我们确定了一种针对用于保护敏感信息的基于朴素抑制的方法的危险推理攻击。我们的攻击基于医疗保健成本和利用项目提供的查询系统，尽管它通常适用于提供查询功能的任何医疗数据库。我们还讨论了该问题的潜在解决方案。
Health care data repositories play an important role in driving progress in medical research. Finding new pathways to discovery requires having adequate data and relevant analysis. However, it is critical to ensure the privacy and security of the stored data. In this paper, we identify a dangerous inference attack against naive suppression based approaches that are used to protect sensitive information. We base our attack on the querying system provided by the Healthcare Cost and Utilization Project, though it applies in general to any medical database providing a query capability. We also discuss potential solutions to this problem.