Privacy preserving health data processing

Anders Andersen, K. Y. Yigzaw, Randi Karlsen
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引用次数: 18

Abstract

The usage of electronic health data from different sources for statistical analysis requires a toolset where the legal, security and privacy concerns have been taken into consideration. The health data are typically located at different general practices and hospitals. The data analysis consists of local processing at these locations, and the locations become nodes in a computing graph. To support the legal, security and privacy concerns, the proposed toolset for statistical analysis of health data uses a combination of secure multi-party computation (SMC) algorithms, symmetric and public key encryption, and public key infrastructure (PKI) with certificates and a certificate authority (CA). The proposed toolset should cover a wide range of data analysis with different data distributions. To achieve this, large set of possible SMC algorithms and computing graphs have to be supported.
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保护隐私的健康数据处理
使用来自不同来源的电子卫生数据进行统计分析需要一套考虑到法律、安全和隐私问题的工具集。健康数据通常位于不同的全科诊所和医院。数据分析由这些位置的本地处理组成,这些位置成为计算图中的节点。为了支持法律、安全和隐私方面的考虑,建议的健康数据统计分析工具集结合使用了安全多方计算(SMC)算法、对称和公钥加密以及带有证书和证书颁发机构(CA)的公钥基础设施(PKI)。建议的工具集应涵盖不同数据分布的广泛数据分析。为了实现这一点,必须支持大量可能的SMC算法和计算图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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