Security Analysis of Opinion Dynamics in Social Networks

This paper concerns the opinion evolution dynamics with malicious opinion injection in social networks. In the study, a modified DeGroot model is proposed by considering a real-time opinion injection from an intruder, and it is proved that the opinions of all the individuals converge to the opinion of the intruder. A set of ‘key’ individuals influenced by the intruder is then found such that the convergence speed on the malicious opinion is maximized. Further, a defense mechanism for each individual is proposed and the steady-state opinion gap of the individuals is obtained. Mumerical examples show the relation of the node role and the opinion convergence speed, and verify the effectiveness of the defense mechanism.