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Privacy Dynamics: Learning Privacy Norms for Social Software

Calikli, G; Law, M; Bandara, AK; Russo, A; Dickens, LWF; Price, BA; Stuart, A; ... Nuseibeh, B; + view all (2017) Privacy Dynamics: Learning Privacy Norms for Social Software. In: Ghezzi, C and Malek, S, (eds.) 2016 IEEE/ACM 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2016): Proceedings. (pp. pp. 47-56). IEEE Green open access

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Abstract

Privacy violations in online social networks (OSNs) often arise as a result of users sharing information with unintended audiences. One reason for this is that, although OSN capa- bilities for creating and managing social groups can make it easier to be selective about recipients of a given post, they do not provide enough guidance to the users to make informed sharing decisions. In this paper we present Pri- vacy Dynamics, an adaptive architecture that learns privacy norms for dierent audience groups based on users' sharing behaviours. Our architecture is underpinned by a formal model inspired by social identity theory, a social psychology framework for analysing group processes and intergroup re- lations. Our formal model comprises two main concepts, the group membership as a Social Identity (SI) map and privacy norms as a set of con ict rules. In our approach a privacy norm is specied in terms of the information objects that should be prevented fromowing between two con icting social identity groups. We implement our formal model by using inductive logic programming (ILP), which automati- cally learns privacy norms. We evaluate the performance of our learning approach using synthesised data representing the sharing behaviour of social network users.

Type: Proceedings paper
Title: Privacy Dynamics: Learning Privacy Norms for Social Software
Event: SEAMS 2016: IEEE/ACM 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 16-17 May 2016, Austin, Texas, USA
Location: Austin, TX, USA
Dates: 16 May 2016 - 17 May 2016
ISBN-13: 9781450341875
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/SEAMS.2016.013
Publisher version: http://ieeexplore.ieee.org/document/7830546/
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Adaptive privacy, online social networks, inductive logic programming, social identity theory
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities > Dept of Information Studies
URI: https://discovery.ucl.ac.uk/id/eprint/1574577
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