云基础设施中的访问控制和数据分离度量

Bernd Jäger, Reiner Kraft, Sebastian Luhn, Ann Selzer, Ulrich Waldmann
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引用次数: 2

摘要

云环境中自动控制和分析的隐私级别可能有助于减轻或至少减少潜在客户的隐私担忧,特别是如果客户自己可以在常规数据处理期间检查是否符合所需的隐私级别。然而,对于每个预期的控制,首先必须仔细确定一组适当的数据源,然后必须将结果与有用的度量结合起来,以便测量结果近似于特定的隐私目标。本文提出了适当的数据源和一种部分自动化的方法来收集测量数据,用于控制云基础设施服务(IaaS)客户端的单独数据处理和访问控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Access Control and Data Separation Metrics in Cloud Infrastructures
An automatically controlled and analyzed privacy level in cloud environments would probably help to allay or at least reduce privacy concerns of prospective clients, in particular if the clients themselves can check the compliance with a required privacy level during regular data processing. However, for each intended control firstly an appropriate set of data sources has to be determined carefully, then the results have to be combined to useful metrics, so that the measurements results approximate specific privacy objectives. This paper proposes appropriate data sources and a partly automatic approach to collect measurement data for controls of separate data processing and access control for clients of cloud infrastructure services (IaaS).
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