Detection method and detection system for fraud access to business to business (B2B) platform based on data mining

Abstract

The invention discloses a detection method and a detection system for fraud access to a business to business (B2B) platform based on data mining. The detection method includes dividing the information of clients into static information and dynamic information, detecting the static information by means of a data mining method of an association analysis, detecting the dynamic information by means of a data mining method of a logistic regression classification model, comprehensively calculating warning values obtained from two data mining methods, grading the clients whose warning values exceed the threshold value, judging the access clients who are graded into a specific grade to be fraud visitors, and listing the fraud visitors into a blacklist information base of fraud clients. The detection system comprises a client information processor, a fraud analysis processor and a front-end display processor. According to the detection method and the detection system for the fraud access to the B2B platform based on the data mining, by means of characteristics of the B2B e-commerce platform, on the basis of multi-dimensional data of client information data, client accessing behaviors and the like, the detection method and the detection system detect behaviors of the fraud access to the B2B e-commerce platform by introducing the data mining technology to model, and the problem that the fraud accesses are difficult to detect caused by the fact that transaction behaviors can't be monitored in the industry is solved.

Description

technical field [0001] The present invention mainly relates to the field of business-to-business (Business To Business, B2B) e-commerce, in particular to a method and system for detecting fraudulent access to a B2B platform based on data mining. Background technique [0002] With the development of the market economy, market fraud has become an important problem that most industries must face, especially in the banking, insurance, securities, telecommunications, manufacturing, and e-commerce industries. Therefore, in these several industry fields, attempts have been made to model fraud problems and have achieved certain results. [0003] In the field of insurance industry, insurance fraud occurs frequently. The main literatures published in this area include: "Analysis of Insurance Fraud Game Model Based on Reinsurer's Sharing of Claim Expenses" published in "Operational Research and Management" in 2006. This article uses exaggerated risk Taking the loss claim fraud problem...

AI Technical Summary

Problems solved by technology

However, this fraud detection method has the disadvantage that the detection range is small and the detection effect is unstable.

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