LAUSR

The existence of botnet puts people in an extremely insecure environment, which has seriously affected the development of Internet of Things (IoT). In order to prevent the formation of a botnet, it is necessary to understand the propagation behaviors and influence factors. As IoT devices become more intelligent, they can gradually generate social characteristics by mimicking human behaviors. However, in the process of coping with the botnet problem, little consideration has been given to the potential social characteristics of IoT. In this article, we build a dynamic botnet propagation model (i.e., IoT-BSI model) to study the influences of two social characteristics (i.e., device’s spread capability and device’s identification ability) on botnet formation. First, in terms of device’s spread capability, this article makes great improvements on the K- shell decomposition algorithm and calculates this characteristic more accurately. Second, this article divides the device’s identification ability into the rational identification ability and the irrational identification ability based on the sociological theory, and the calculation of the former is mainly realized by utilizing the PageRank idea. Third, this article applies the mean-field equation theory to analyze the dynamic characteristics of botnet propagation theoretically. Finally, the comprehensive results show that our model is not merely more consistent with the actual situation but also performs better than four compared models.