Exploratory Study of the Privacy Extension for System Theoretic Process Analysis (STPA-Priv) to Elicit Privacy Risks in eHealth

K. Mindermann, Frederik Riedel, Asim Abdulkhaleq, Christoph Stach, Stefan Wagner
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引用次数: 14

Abstract

Context: System Theoretic Process Analysis for Privacy (STPA-Priv) is a novel privacy risk elicitation method using a top down approach. It has not gotten very much attention but may offer a convenient structured approach and generation of additional artifacts compared to other methods. Aim: The aim of this exploratory study is to find out what benefits the privacy risk elicitation method STPA-Priv has and to explain how the method can be used. Method: Therefore we apply STPA-Priv to a real world health scenario that involves a smart glucose measurement device used by children. Different kinds of data from the smart device including location data should be shared with the parents, physicians, and urban planners. This makes it a sociotechnical system that offers adequate and complex privacy risks to be found. Results: We find out that STPA-Priv is a structured method for privacy analysis and finds complex privacy risks. The method is supported by a tool called XSTAMPP which makes the analysis and its results more profound. Additionally, we learn that an iterative application of the steps might be necessary to find more privacy risks when more information about the system is available later. Conclusions: STPA-Priv helps to identify complex privacy risks that are derived from sociotechnical interactions in a system. It also outputs privacy constraints that are to be enforced by the system to ensure privacy.
基于系统理论过程分析(STPA-Priv)的隐私延伸引出电子医疗隐私风险的探索性研究
背景:隐私系统理论过程分析(STPA-Priv)是一种采用自顶向下方法的新型隐私风险提取方法。它还没有得到很多关注,但与其他方法相比,它可能提供了一种方便的结构化方法和生成额外工件的方法。目的:本探索性研究的目的是找出隐私风险诱导方法STPA-Priv有什么好处,并解释如何使用该方法。方法:因此,我们将STPA-Priv应用于现实世界的健康场景,其中涉及儿童使用的智能葡萄糖测量设备。来自智能设备的不同类型的数据,包括位置数据,应该与父母、医生和城市规划者共享。这使得它成为一个社会技术系统,提供了足够的和复杂的隐私风险。结果:发现stp - priv是一种结构化的隐私分析方法,能够发现复杂的隐私风险。该方法由一个名为XSTAMPP的工具支持,该工具使分析及其结果更加深刻。此外,我们还了解到,当稍后有更多关于系统的信息可用时,这些步骤的迭代应用程序可能是发现更多隐私风险所必需的。结论:STPA-Priv有助于识别源自系统中社会技术交互的复杂隐私风险。它还输出由系统强制执行的隐私约束,以确保隐私。
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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