DYNAMIC FRAUD INFORMATION CONTROL IN SOCIAL NETWORKS

Abstract

Mobile social networks (MSNs) provide real-time information services to
individuals in social communities through mobile devices. However, due to
their high openness and autonomy, MSNs have been suffering from rampant
rumors, fraudulent activities, and other types of misuses. To mitigate such
threats, it is urgent to control the spread of fraud information. The research
challenge is: how to design control strategies to efficiently utilize limited
resources and meanwhile minimize individuals’ losses caused by fraud
information? To this end, we model the fraud information control issue as an
optimal control problem, in which the control resources consumption for
implementing control strategies and the losses of individuals are jointly taken as
a constraint called total cost, and the minimum total cost becomes the objective
function. Based on the optimal control theory, we devise the optimal dynamic
allocation of control strategies. Besides, a dynamics model for fraud
information diffusion is established by considering the uncertain mental state of
individuals, we investigate the trend f fraud information diffusion and the
stability of the dynamics model. Our simulation study shows that the proposed
optimal control strategies can effectively inhibit the diffusion of fraud information while incurring the smallest total cost. Compared with other control
strategies, the control effect of the proposed optimal control strategies is about
10% higher.