Digital privacy is and likely will remain an important issue for end users, and there are many recommendations on how to protect one’s privacy. However, the majority of research focuses on security advice, thereby creating a potential gap in the field. In this work, we present the results of \(n=10\) expert interviews on privacy recommendations given to end users. We collect the recommendations given by experts, as well as their evaluation and prioritisation. In addition, the experts consider for which target user groups the advice is appropriate, distinguishing between different levels of knowledge and experience. The results highlight the importance of basic measures, such as being generally careful when sharing data and posting on social media. Concurrently, they emphasise the value of simple and automatable measures that require minimal or no user interaction, such as ad blockers and automated cookie deletion.

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“Of course, that’s not feasible for everyone” – Compiling and Evaluating Privacy Recommendations in Expert Interviews

  • Maike M. Raphael,
  • Hannah Köster,
  • Lennard Boetcher,
  • Markus Dürmuth

摘要

Digital privacy is and likely will remain an important issue for end users, and there are many recommendations on how to protect one’s privacy. However, the majority of research focuses on security advice, thereby creating a potential gap in the field. In this work, we present the results of \(n=10\) expert interviews on privacy recommendations given to end users. We collect the recommendations given by experts, as well as their evaluation and prioritisation. In addition, the experts consider for which target user groups the advice is appropriate, distinguishing between different levels of knowledge and experience. The results highlight the importance of basic measures, such as being generally careful when sharing data and posting on social media. Concurrently, they emphasise the value of simple and automatable measures that require minimal or no user interaction, such as ad blockers and automated cookie deletion.