Research on Dynamic Early Warning Methods of Internet of Things Based on Big Data Mining

With the development of the economy, Internet technology has been rapidly promoted and popularized. While people enjoy the convenience of using Internet technology, they are also threatened by potential security risks of the Internet. The Internet network security situation is uncertain, so it is very necessary to ensure the normal operation of the network on the basis of perceiving the network security situation. Based on the analysis of the network security situation, a BAYES-based network security situation evaluation model is constructed. First, collect and sort the index data that affect the network security situation, summarize and integrate; secondly, discretize the index data, and perform hierarchical and hierarchical processing; finally, establish a Bayesian network to divide the underlying indicators in the hierarchical and hierarchical process Gradually integrate upward, calculate the probability and modify the Bayesian network until it is integrated into the security situation layer, and then realize the evaluation of the network security situation, and judge the degree and trend of the network security situation.