Automating user privacy policy recommendations in social media

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dc.contributor.advisorKayem, Anneen_ZA
dc.contributor.authorAbuelgasim, Ammaren_ZA
dc.date.accessioned2016-07-28T12:23:08Z
dc.date.available2016-07-28T12:23:08Z
dc.date.issued2016en_ZA
dc.description.abstractMost Social Media Platforms (SMPs) implement privacy policies that enable users to protect their sensitive information against privacy violations. However, observations indicate that users find these privacy policies cumbersome and difficult to configure. Consequently, various approaches have been proposed to assist users with privacy policy configuration. These approaches are however, limited to either protecting only profile attributes, or only protecting user-generated content. This is problematic, because both profile attributes and user-generated content can contain sensitive information. Therefore, protecting one without the other, can still result in privacy violations. A further drawback of existing approaches is that most require considerable user input which is time consuming and inefficient in terms of privacy policy configuration. In order to address these problems, we propose an automated privacy policy recommender system. The system relies on the expertise of existing social media users, as well as the user's privacy policy history in order to provide him/her with personalized privacy policy suggestions for both profile attributes, and user-generated content. Results from our prototype implementation indicate that the proposed recommender system provides accurate privacy policy suggestions, with minimum user input.en_ZA
dc.identifier.apacitationAbuelgasim, A. (2016). <i>Automating user privacy policy recommendations in social media</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Computer Science. Retrieved from http://hdl.handle.net/11427/20969en_ZA
dc.identifier.chicagocitationAbuelgasim, Ammar. <i>"Automating user privacy policy recommendations in social media."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Computer Science, 2016. http://hdl.handle.net/11427/20969en_ZA
dc.identifier.citationAbuelgasim, A. 2016. Automating user privacy policy recommendations in social media. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Abuelgasim, Ammar AB - Most Social Media Platforms (SMPs) implement privacy policies that enable users to protect their sensitive information against privacy violations. However, observations indicate that users find these privacy policies cumbersome and difficult to configure. Consequently, various approaches have been proposed to assist users with privacy policy configuration. These approaches are however, limited to either protecting only profile attributes, or only protecting user-generated content. This is problematic, because both profile attributes and user-generated content can contain sensitive information. Therefore, protecting one without the other, can still result in privacy violations. A further drawback of existing approaches is that most require considerable user input which is time consuming and inefficient in terms of privacy policy configuration. In order to address these problems, we propose an automated privacy policy recommender system. The system relies on the expertise of existing social media users, as well as the user's privacy policy history in order to provide him/her with personalized privacy policy suggestions for both profile attributes, and user-generated content. Results from our prototype implementation indicate that the proposed recommender system provides accurate privacy policy suggestions, with minimum user input. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Automating user privacy policy recommendations in social media TI - Automating user privacy policy recommendations in social media UR - http://hdl.handle.net/11427/20969 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20969
dc.identifier.vancouvercitationAbuelgasim A. Automating user privacy policy recommendations in social media. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Computer Science, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20969en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Computer Scienceen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherComputer Scienceen_ZA
dc.titleAutomating user privacy policy recommendations in social mediaen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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