Privacy protection: a community-structured evolutionary game approach

Users of social networks can be connected with each other by different communities according to professions, living locations and personal interests. As each user on the social network platforms stores and shows a large amount of personal data, the privacy protection raises as a major concern. This paper establishes a game theoretic framework to model users' interactions to influence users' strategies to take the privacy protection or not. To model the relationship of user communities, we introduce the community-structured evolutionary dynamics. Users' interactions can only happen among those who have at least one common community. Then we analyze the dynamics of users' privacy protection behavior based on the proposed community structured evolutionary game theoretic framework. Results show that social network managers need to provide appropriate security service b and payment mechanism c to ensure that cost performance b/c is larger than the critical cost performance, which can promote the spread of the privacy security behavior over the network. Moreover, results can help to design appropriate structure of the social network and control the convergence speed that all users take the privacy protection.