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Transparency of Privacy Risks Using PIA Visualizations

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HCI for Cybersecurity, Privacy and Trust (HCII 2023)

Abstract

Privacy enhancing technologies allow the minimization of risks to online data. However, the transparency of the minimization process is not so clear to all types of end users. Privacy Impact Assessments (PIAs) is a standardized tool that identifies and assesses privacy risks associated with the use of a system. In this work, we used the results of the PIA conducted in our use case to visualize privacy risks to end users in the form of User Interface (UI) mock ups. We tested and evaluated the UI mock-ups via walkthroughs to investigate users’ interests by observing their clicking behavior, followed by four focus group workshops. There were 13 participants (two expert groups and two lay user groups) in total. Results reveal general interests in the transparency provided by showing the risks reductions. Generally, although participants appreciate the concept of having detailed information provided about risk reductions and the type of risks, the visualization and usability of the PIA UIs require future development. Specifically, it should be tailored to the target group’s mental models and background knowledge.

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Notes

  1. 1.

    https://www.papaya-project.eu/.

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Acknowledgment

We would like to acknowledge the PAPAYA (H2020 the European Commission, Grant Agreement No. 786767) and the TRUEdig (Swedish Knowledge Foundation) projects for funding this work. We extend our thanks to the project members for contributing with their valuable inputs throughout the projects. We further thank Tobias Pulls and Jonathan Magnusson for their technical input of the PAPAYA tool, John Sören Pettersson for his input to the user studies, and Elin Nilsson for her help in implementing the mock ups in adobe and transcribing results.

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Correspondence to Ala Sarah Alaqra .

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Alaqra, A.S., Fischer-Hübner, S., Karegar, F. (2023). Transparency of Privacy Risks Using PIA Visualizations. In: Moallem, A. (eds) HCI for Cybersecurity, Privacy and Trust. HCII 2023. Lecture Notes in Computer Science, vol 14045. Springer, Cham. https://doi.org/10.1007/978-3-031-35822-7_1

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  • DOI: https://doi.org/10.1007/978-3-031-35822-7_1

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