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Towards learning privacy policies

Bandara, A. K.; Russo, A. and Lupu, E. C. (2007). Towards learning privacy policies. In: 8th IEEE International Workshop on Policies for Distributed Systems and Networks (Western Ontario, University of ed.), 13-15 Jun, Bologna, Italy, IEEE Computer Society, p. 274.

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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. Current efforts in privacy management have focussed on notations for privacy policy specification and on user interaction design for privacy management. However, little has been done to support automated analysis and learning of privacy policies. We advocate an approach based on inductive logic programming (ILP) for automatic learning of privacy policies. ILP is preferred over statistical learning techniques because it produces rules (privacy policies) which are comprehensible to the user and amenable to automated analysis.

Item Type: Conference or Workshop Item
ISBN: 0-7695-2767-1, 978-0-7695-2767-3
Extra Information: Workshop paper
Keywords: automatic privacy policy learning; inductive logic programming; privacy management system; privacy policy specification; data privacy; formal specification; inductive logic programming; learning (artificial intelligence)
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 15563
Depositing User: Colin Smith
Date Deposited: 17 Apr 2009 14:01
Last Modified: 07 Dec 2018 09:21
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