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This paper focuses on the security and robustness of smart campuses by studying a virus propagation model. Establishing a model that reflects the epidemiological transmission mechanism is a primary method for studying disease outbreaks and control. However, the relationship between microscopic and macrodynamic evolution in networks has long remained an unsolved problem. The existing virus transmission models, which ignore differences between individuals, cannot objectively reflect the spread of infectious diseases. In this paper, a differential model of virus propagation is established for a smart campus network by considering the differences among individuals, and a method to extend the individual evolution process to the evolution process of the entire network is proposed. First, the functional process of a virus infection in individuals is reflected by the evolution model of a single node. Then, we extend the individual evolution to the whole network to reflect the scale of virus transmission and propagation among individuals in a smart campus network. The proposed model more objectively reflects viral infections and could serve to enhance the security and robustness of smart campuses.

Research on a Dynamic Virus Propagation Model to Improve Smart Campus Security