Study on the Hot Spot Analysis of Internet Fraud based on Spatio-temporal and Early Warning Models

Abstract

Internet fraud is an important research topic in the field of cyberspace security. In this paper, on the one hand, the public news text obtained from portal is taken as the data source. The word frequency statistics and regular expression method are used to calculate the monthly growth rate of the time hot spot, and the thermal temporal and spatial models are constructed. On the other hand, we use the double index dictionary method and the K means clustering algorithm to construct the spatio-temporal distribution module and early warning module. What’s more, we build the visual modeling of the above work. The results show that in recent years, China's online fraud cases showed a low growth rate, from outside to inside. Not only this research enriches the analytical methods in related fields, but also can provide some scientific basis for the decision of relevant departments.