Abstract
The privacy policies of an online social network play an important role in determining user involvement and satisfaction, and in turn site profit and success. In this paper, we develop a game theoretic framework to model the relationship between the set of privacy options offered by a social network site and the sharing decisions of its users within these constraints. We model the site and the users in this scenario as the leader and followers, respectively, in a Stackelberg game. We formally establish the conditions under which this game reaches a Nash equilibrium in pure strategies and provide an approximation algorithm for the site to determine a discrete set of privacy options to maximize payoff. We validate hypotheses in our model on data collected from a mock-social network of users’ privacy preferences both within and outside the context of peer influence, and demonstrate that the qualitative assumptions of our model are well-founded.
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Acknowledgements
Portions of Dr. Rajtmajer’s, Dr. Griffin’s and Dr. Squicciarini’s work were supported by the Army Research Office grant W911NF-13-1-0271. Portions of Dr. Squicciarini’s work were additionally supported by the National Science Foundation grant 1453080.
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Rajtmajer, S., Griffin, C., Squicciarini, A. (2015). Determining a Discrete Set of Site-Constrained Privacy Options for Users in Social Networks Through Stackelberg Games. In: Khouzani, M., Panaousis, E., Theodorakopoulos, G. (eds) Decision and Game Theory for Security. GameSec 2015. Lecture Notes in Computer Science(), vol 9406. Springer, Cham. https://doi.org/10.1007/978-3-319-25594-1_12
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