Search Engine: A Hidden Power for Virus Propagation in Community Networks

Abstract

The propagation methods of viruses are diverse and studying the virus propagation is a hot topic. There appears a new way that the search engine quickly spreads network viruses, and many researches overlook its impact of propagation and few researches set a model to quantifiabely analyze how the search engine spread viruses. Based on community networks, this paper designs a specific model how the search engine spreads viruses. Moreover, this paper quantifiabely calculate the virus propagation velocity and the propagation effect. First, by analyzing the propagation process of viruses under the search engine condition, we design a positive feedback model to analyze how the search engine and the community network influence the propagation process of viruses. Second, we define relationship functions of propagation factors and calculate the rate of infected nodes while establishing mathematical propagation formulas for two situations. One situation is with the search engine, and another is without the search engine. Third, we design the experiment to verify the model analysis. Compared with two situations, we show that viruses have a much quicker propagation velocity, and the growth rate of infected rate is larger under the search engine condition. When the immune vaccine replaces the virus, this paper is also applicable.