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The Processing goes far beyond "the app" – Privacy issues of decentralized Digital Contact Tracing using the example of the German Corona-Warn-App

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  • Rehak, Rainer
  • Kuhne, Christian R.

Abstract

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 Data 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 in advance 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 the results of a scientific and methodologically clear DPIA. It shows that even a decentralized architecture involves numerous serious weaknesses and risks, including larger ones still left unaddressed in current implementations. It also found that none of the proposed designs operates on anonymous data or ensures proper anonymisation. It also showed that informed consent would not be a legitimate legal ground for the processing. For all points where data subjects’ rights are still not sufficiently safeguarded, we briefly outline solutions.

Suggested Citation

  • Rehak, Rainer & Kuhne, Christian R., 2022. "The Processing goes far beyond "the app" – Privacy issues of decentralized Digital Contact Tracing using the example of the German Corona-Warn-App," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 16-20.
    • Handle: RePEc:zbw:espost:264865
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    References listed on IDEAS

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    1. Phebo D Wibbens & Wesley Wu-Yi Koo & Anita M McGahan, 2020. "Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-19, December.
    2. Nina Haug & Lukas Geyrhofer & Alessandro Londei & Elma Dervic & Amélie Desvars-Larrive & Vittorio Loreto & Beate Pinior & Stefan Thurner & Peter Klimek, 2020. "Ranking the effectiveness of worldwide COVID-19 government interventions," Nature Human Behaviour, Nature, vol. 4(12), pages 1303-1312, December.
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