Policy-by-example for online social networks

  • Authors:
  • Gorrell P. Cheek;Mohamed Shehab

  • Affiliations:
  • University of North Carolina at Charlotte, Charlotte, NC, USA;University of North Carolina at Charlotte, Charlotte, NC, USA

  • Venue:
  • Proceedings of the 17th ACM symposium on Access Control Models and Technologies
  • Year:
  • 2012

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Abstract

We introduce two approaches for improving privacy policy management in online social networks. First, we introduce a mechanism using proven clustering techniques that assists users in grouping their friends for group based policy management approaches. Second, we introduce a policy management approach that leverages a user's memory and opinion of their friends to set policies for other similar friends. We refer to this new approach as Same-As Policy Management. To demonstrate the effectiveness of our policy management improvements, we implemented a prototype Facebook application and conducted an extensive user study. Leveraging proven clustering techniques, we demonstrated a 23% reduction in friend grouping time. In addition, we demonstrated considerable reductions in policy authoring time using Same-As Policy Management over traditional group based policy management approaches. Finally, we presented user perceptions of both improvements, which are very encouraging.