Streisand Games on Complex Social Networks

This paper deals with the study of adversarial social contagion processes as a two-player game on finite complex networks. In our formulation, a censor affects the information diffusion dynamics on finite complex social networks, modeled as a controlled Markov chain, to minimize the number of infected (information aware) individuals. A stopper chooses when to terminate the information relayed to the network. This makes it a two-player dynamic game between the censor and the stopper, and is named as the Streisand game. We show that the game has a well-defined upper value, achieved by pure minimax strategies under the feedback information structure, and establish that it is an increasing function of the state. We provide a game-value iteration algorithm to compute the upper value and the minimax strategies.