Abstract
In the field of ambient intelligence (AmI) privacy is recognized as one of the key factors regarding the acceptance of systems. However, this topic is mostly neglected or only addressed in a simplified form. Our approach is to understand privacy as a service, i.e., the AmI restricts its own knowledge rather than only hiding it. Through providing related vocabulary and a basic theory of privacy, we introduce a categorization of privacy related functionality and a classification of privacy affordances an AmI can provide. By investigating and evaluating small prototypical systems we propose a measure to compare different systems with respect to the balance between support provided and privacy.
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van de Ven, J., Dylla, F. (2014). Privacy Classification for Ambient Intelligence. In: Aarts, E., et al. Ambient Intelligence. AmI 2014. Lecture Notes in Computer Science(), vol 8850. Springer, Cham. https://doi.org/10.1007/978-3-319-14112-1_26
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DOI: https://doi.org/10.1007/978-3-319-14112-1_26
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