Abstract
Social media continues to lead imprudent users into over-sharing, exposing them to various privacy threats. Recent research thus focusses on nudging the user into the ‘right’ direction. In this paper, we propose Comparison-based Privacy (CbP), a design paradigm for privacy nudges that overcomes the limitations and challenges of existing approaches. CbP is based on the observation that comparison is a natural human behavior. With CbP, we transfer this observation to decision-making processes in the digital world by enabling the user to compare herself along privacy-relevant metrics to user-selected comparison groups. In doing so, our approach provides a framework for the integration of existing nudges under a self-adaptive, user-centric norm of privacy. Thus, we expect CbP not only to provide technical improvements, but to also increase user acceptance of privacy nudges. We also show how CbP can be implemented and present preliminary results.
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This work has been funded by the Excellence Initiative of the German federal and state governments.
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Ziegeldorf, J.H., Henze, M., Hummen, R., Wehrle, K. (2016). Comparison-Based Privacy: Nudging Privacy in Social Media (Position Paper). In: Garcia-Alfaro, J., Navarro-Arribas, G., Aldini, A., Martinelli, F., Suri, N. (eds) Data Privacy Management, and Security Assurance. DPM QASA 2015 2015. Lecture Notes in Computer Science(), vol 9481. Springer, Cham. https://doi.org/10.1007/978-3-319-29883-2_15
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DOI: https://doi.org/10.1007/978-3-319-29883-2_15
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