Resolving Multi-Party Privacy Conflicts In Social Media - 2016


Items shared through Social Media could affect a lot of than one user's privacy-e.g., photos that depict multiple users, comments that mention multiple users, events in which multiple users are invited, etc. The lack of multi-party privacy management support in current mainstream Social Media infrastructures makes users unable to appropriately management to whom these items are literally shared or not. Computational mechanisms that can merge the privacy preferences of multiple users into a single policy for an item will help solve this downside. However, merging multiple users' privacy preferences is not an simple task, as a result of privacy preferences may conflict, therefore methods to resolve conflicts are required. Moreover, these ways need to contemplate how users' would truly reach an agreement about a resolution to the conflict in order to propose solutions that may be acceptable by all of the users plagued by the item to be shared. Current approaches are either too demanding or solely think about fixed ways in which of aggregating privacy preferences. In this paper, we have a tendency to propose the primary computational mechanism to resolve conflicts for multi-party privacy management in Social Media that's able to adapt to completely different things by modelling the concessions that users make to reach a resolution to the conflicts. We have a tendency to also gift results of a user study in that our proposed mechanism outperformed other existing approaches in terms of how many times every approach matched users' behaviour.

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This privacy policy has been compiled to better serve those who are concerned with how their 'Personally identifiable information' (PII) is being used online. PII, as used in Indian privacy law and information security, is information
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