Towards learning privacy policies

  • Bandara A
  • Russo A
  • Lupu E
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Abstract

With the proliferation of personal computing devices users are creating a variety of digitized personal information, from personal contact databases and multimedia content to context data such as location, activity and mood. Preventing unintended disclosure of such information is a key motivator for developing privacy management frameworks. It is equally critical that protecting privacy does not prevent users from completing essential tasks. For example, whilst a user does not generally make his location available, he may want to disclose it to the taxi company with which he has booked a journey. It is impractical for the user to always specify his preferences in advance and it is impossible to forecast every possible scenario. Furthermore, conflicts may arise due to apparently conflicting requirements or due to the diversity of situations encountered. Therefore there is a need to be able to learn privacy requirements from the user's behaviour and decisions and to be able to analyse privacy requirements for consistency. Otherwise the overhead of using the privacy management system could cause it to be disabled completely.

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Authors

  • Arosha K. Bandara

  • Alessandra Russo

  • Emil C. Lupu

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