Measuring the Hazard of Malicious Nodes in Information Diffusion over Social Networks

Social networks have become prevalent in our daily life: people learn, discuss, and spread different kinds of information through social networks every day. While bringing a lot of convenience, the prevalence of social networks creates the security challenge. The information released and/or spread by malicious nodes can be wrong, misleading or even virus, which may lead to bad influences and severe consequences. Therefore, understanding the information diffusion process and the hazard impact of malicious nodes' behaviors to the information diffusion is critical. In this paper, we utilize the evolutionary game theory to measure the hazard influence of malicious nodes to the information diffusion over social networks, by investigating the information diffusion dynamics and evolutionary stable strategies. Finally, simulations are conducted to validate the theoretic analysis and illustrate the impact of the malicious nodes.