Inferring privacy policies for social networking services

  • Authors:
  • George Danezis

  • Affiliations:
  • Microsoft Research, Cambridge, United Kingdom

  • Venue:
  • Proceedings of the 2nd ACM workshop on Security and artificial intelligence
  • Year:
  • 2009

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Abstract

Social networking sites have come under criticism for their poor privacy protection track record. Yet, there is an inherent difficulty in deciding which principals should have access to user's information or actions, without requiring them to constantly manage their privacy settings. We propose to extract automatically such privacy settings, based on the policy that information produced within a social context should remain in that social context, both to ensure privacy as well as maximising utility. A machine learning approach is used to extract automatically such social contexts, as well as a tentative evaluation.