A Method for Discovering Abnormal Trading Communities in Financial Networks Based on Information Entropy

Abstract

The invention discloses a financial network unusual transaction community finding method based on information entropy. The method includes the specific steps of firstly, analyzing the process and the mode of an unusual transaction, and extracting features of block transactions and suspicious transactions; secondly, storing transaction amounts and traction frequency information of accounts through an adjacent matrix so as to quantize the features; thirdly, defining the information entropy of nodes; fourthly, conducting community division and finding on the financial network nodes according to the financial network unusual transaction community finding method based on the information entropy; fifthly, evaluating the community finding result. Firstly, accuracy of unusual transaction account identification and unusual transaction communication division which are achieved according to the method is calculated, and then the structure of the unusual transaction community is evaluated through the community evaluation index modularity Q. The community finding method based on the information entropy is applied to the anti-money laundering field for the first time, the money laundering accounts can be identified and tracked by finding the unusual transaction community, and unusual transactions can be prevented by analyzing the relations and the transaction laws between money laundering accounts.

Description

technical field [0001] The invention belongs to the technical field of network financial communities, in particular to a method for discovering abnormal financial network transaction communities based on information entropy. Background technique [0002] Community discovery is currently the most popular and mature technology applied to social network analysis. It mainly refers to the discovery of groups or sub-networks in the network that are closely connected internally but sparsely connected externally, forming multiple sub-communities, and mining these communities. It can discover the hidden connections and laws in the network, predict the behavior of the network, and then propose better and more efficient solutions when analyzing the characteristics of complex networks, retrieving information in complex networks, and solving specific problems in networks. The financial network is a complex network. According to the community structure characteristics of the complex netwo...

AI Technical Summary

Problems solved by technology

[0003] The present invention provides a method for discovering abnormal transaction communities in a financial network based on information entropy, which solves the difficulty in calculating the occurrence probability of abnormal transactions in existing methods, and the accuracy and accuracy of community division and discovery through connections between financial network nodes and probability similarities. low efficiency problem

Images