Abstract
Privacy on online social networks is a concern, specifically in relation to sharing co-owned images. Co-owned images raise a privacy conundrum, in that enforcing privacy policies impacts negatively on performance and usability. In most existing work, this issue is addressed by requiring users from the same or overlapping friendship networks to contribute privacy opinions vis-a-vis posting the co-owned image. This poses two issues: (1) privacy posting decisions cannot be made, resulting in delay; and (2) ineffective user opinion computation necessitates large amounts of image distortion, resulting in low levels of user satisfaction. In this paper, we present a multi-agent system in which an opinion formulation algorithm computes offline user opinions based on user personality and behaviour information. Our results indicate that posting decisions, for images in which all co-owners are offline, take 3.81 s on average.
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Motlagh, F.N., Kayem, A.V.D.M., Meinel, C. (2022). A Multi-agent Model to Support Privacy Preserving Co-owned Image Sharing on Social Media. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-030-99584-3_13
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