Since SARS-CoV-2 started spreading in Europe in early 2020, there has been a strong call for technical solutions to combat or contain the pandemic, with contact tracing apps at the heart of the debates. The EU's General Daten Protection Regulation (GDPR) requires controllers to carry out a data protection impact assessment (DPIA) where their data processing is likely to result in a high risk to the rights and freedoms (Art. 35 GDPR). A DPIA is a structured risk analysis that identifies and evaluates possible consequences of data processing relevant to fundamental rights and describes the measures envisaged to address these risks or expresses the inability to do so. Based on the Standard Data Protection Model (SDM), we present a scientific DPIA which thoroughly examines three published contact tracing app designs that are considered to be the most "privacy-friendly": PEPP-PT, DP-3T and a concept summarized by Chaos Computer Club member Linus Neumann, all of which process personal health data. The DPIA starts with an analysis of the processing context and some expected use cases. Then, the processing activities are described by defining a realistic processing purpose. This is followed by the legal assessment and threshold analysis. Finally, we analyse the weak points, the risks and determine appropriate protective measures. We show that even decentralized implementations involve numerous serious weaknesses and risks. Legally, consent is unfit as legal ground hence data must be processed based on a law. We also found that measures to realize the rights of data subjects and affected people are not sufficient. Last but not least, we show that anonymization must be understood as a continuous process, which aims at separating the personal reference and is based on a mix of legal, organizational and technical measures. All currently available proposals lack such an explicit separation process.
翻译:自2020年初开始在欧洲推广SARS-COV-2以来,人们强烈呼吁采用技术解决办法来防治或遏制这一流行病,在辩论的核心部分采用联系追踪应用程序。欧盟的《一般日期保护条例》要求控制者进行数据保护影响评估,其数据处理很可能对权利和自由造成高风险(第35条GDPR)。一个DPA是一个结构化的风险分析,查明和评价与基本权利有关的数据处理可能造成的后果,并描述为解决这些风险而设想的措施,或表示无法这样做。根据标准数据保护模式(SDM),我们提出一个科学DPIA,彻底审查出版的三种被认为最“隐私友好”的联系人追踪应用程序设计:PEPP-PT、DP-3T,以及Chaos计算机俱乐部成员Linus Neumann所总结的概念,所有这些都处理个人健康数据。新闻部首先必须分析处理背景和一些预期使用案例。随后,对处理活动进行描述,而不是界定现实的处理目的。我们所描述的是一个不切实际的、不透明的处理目的。我们所遵循的是法律追踪的三个法律追踪的追踪程序,并分析一个非常薄弱的底线。我们所理解了一种了解的底线。我们所了解的是,这是一个以什么标准,这个底底底部,我们所理解的、最后的、我们所理解的、我们所了解的、一个以正确地分析。我们所了解的、以什么是缺乏的、我们所理解的、我们所了解的、我们所了解的、我们所了解的、我们所了解的、我们所了解的、我们所了解的缺点。