Abstract:

With the development of the Internet, cyber fraud crime, featuring concealment and diversity, has become a hazard that is hard to investigate and cannot be neglected. However, under the existing situation of cyber fraud crime, there are still scarce of incorporated investigations on cases and analyses aimed at the crowd involved in cases. In this paper, we get to know current platform and process that public security bureau is using for cyber fraud crime, further apply the thinking of data mining to it. Based on the study of clustering algorithm and decision tree algorithm, we put forward an intelligent analysis algorithm module on the basis of K-means algorithm and CHAID algorithm, and preliminary build a database of the crowd involved in cyber fraud cases for data mining. Through the intelligent analysis, we can conclude the characteristics of the victim and the criminal suspect on the one hand, and factors that influencing the money of cyber fraud cases on the other hand. In the future, we can build an intelligent analysis platform and a database for cyber fraud crime investigation, getting deeper into the crime information, and make better use of the analysis results for our investigation. It is of certain significance that using intelligent analysis algorithm to give assistance and guidance to cyber fraud crime investigation as well as prevention and control.

Key words: cyber fraud, cluster, decision tree, K-means, CHAID