Abstract
We present an approach to reduce the complexity of adjusting privacy preferences for multiple online social networks. To achieve this, we quantify the effect on privacy for choices that users make, and simplify configuration by introducing privacy configuration as a service. We present an algorithm that effectively measures privacy and adjusts privacy settings across social networks. The aim is to configure privacy with one click.
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CITATION STYLE
Hehnle, P., Keilbach, P., Lee, H. J., Lejn, S., Steidinger, D., Weinbrenner, M., & Langweg, H. (2017). One click privacy for online social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10489 LNCS, pp. 435–442). Springer Verlag. https://doi.org/10.1007/978-3-319-66284-8_37
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