社会网络中观点动力学的安全性分析

该文考虑了社会网络中带有恶意观点注入的观点动力学。首先，基于DeGroot模型提出了恶意攻击者不断向网络中注入恶意观点的动力学模型，并证明了在该模型中所有个体都将收敛到攻击者的恶意观点。其次，研究了在资源受限的情况下攻击者攻击的节点对网络收敛速率的影响，为抵御攻击者的恶意攻击提出了有效的防御机制，进一步获得了个体稳态下的观点差。最后通过数值仿真验证了网络中节点角色与观点收敛速率的关系，并证实了防御机制的有效性。

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.