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Fraud behavior analysis system based on neural network model

A neural network model and behavior analysis technology, applied in biological neural network models, neural learning methods, business, etc., can solve the problem of insufficient ability to predict fraud behavior orientation, inability to predict and process network fraud situations, lack of rapid location and identification of fraud sources, etc. problems, achieve rapid and accurate identification, improve traceability and observation capabilities, and improve the effect of early warning processing

Pending Publication Date: 2022-01-11
ZHENGZHOU JINHUI COMP SYST ENG
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Problems solved by technology

[0004] The purpose of the present invention is: in order to solve the problem of insufficient ability to guide and predict fraudulent behaviors, which affects the prevention and treatment of fraudulent behaviors, lacks rapid positioning and identification of fraud sources in a big data environment, and cannot predict and process network fraud situations problem, and proposed a fraud analysis system based on neural network model

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  • Fraud behavior analysis system based on neural network model
  • Fraud behavior analysis system based on neural network model
  • Fraud behavior analysis system based on neural network model

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Embodiment approach

[0038] The implementation method is as follows: the weighted processing of the feature vector can be realized through the neural network model to realize the extraction of the multi-source feature vector of the input layer data, and the fraudulent behavior in the data can be extended and separated through the output layer, and it can be analyzed through the propagation source The module 302 and the fraud feature analysis module 303 realize the retrospective extraction of data propagation features and fraud features, which is conducive to realizing the prediction and warning of fraud before the occurrence of fraud.

[0039] The associated aggregation data set 2 includes a user data acquisition module 202, and the user data acquisition module 202 is used to acquire user signaling data, subscription data, bill data, call behavior data, short message, multimedia message data and Internet behavior data, so The input terminal of the user data acquisition module 202 is connected with ...

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Abstract

The invention discloses a fraudulent behavior analysis system based on a neural network model, and belongs to the technical field of fraudulent behavior analysis. The fraudulent behavior analysis system comprises an association aggregation data set and a data processing center, wherein the input end of the data processing center is connected with the output end of the association aggregation data set; and the data processing center is used for processing and analyzing the data after association aggregation of the data set. According to the invention, through the designed neuron processing unit, a neural network model can be established through a machine learning module to extract and analyze fraud features in big data, and through application of a big data technology, Internet fraud content identification, reverse positioning of a source and linkage analysis of various fraud contents, 24-hour real-time monitoring can be realized all day long. The system has a rapid and accurate recognition capability, and can perform data updating on the neural network model by recording user fraud feature data, thereby improving the adaptive capacity of rapid data transformation in a big data environment.

Description

technical field [0001] The invention belongs to the technical field of fraud analysis, and in particular relates to a fraud analysis system based on a neural network model. Background technique [0002] With the development of science and technology today, network fraud through the Internet is replacing transmission telecom fraud as the main means of fraud. Internet telecom fraud is more difficult to trace than traditional fraud, so front-end analysis of fraudulent behavior is required to meet Preventive treatment of fraudulent activities. [0003] Existing fraud protection systems mostly use tracking behavior analysis after fraud alarms occur, lack certain preventive analysis capabilities, and insufficient ability to guide and predict fraudulent behaviors. The ability to integrate data processing and regulation will affect the prevention and treatment of fraudulent behaviors. The lack of rapid location and identification of the source of fraud in the big data environment, ...

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Application Information

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IPC IPC(8): G06N3/08G06Q30/00G06Q50/30
CPCG06N3/08G06Q30/0185G06Q50/40
Inventor 张晨民王维国张雷孙韧乔利稳
Owner ZHENGZHOU JINHUI COMP SYST ENG