A construction method and construction system of a customer information leakage risk assessment system

Abstract

This application discloses a construction method and construction system of a customer information leakage risk assessment system, wherein, the construction method of the customer information leakage risk assessment system is based on a radial basis function neural network to construct a customer information leakage risk assessment system, and for radial basis The acquisition of training samples of the function neural network and the determination of the kernel function give specific standards. The radial basis function neural network obtained through this method does not require technical personnel when evaluating the risk of customer information leakage on the application page of the customer information system. Participation avoids the interference of the evaluation results caused by the subjective experience of technicians, and can achieve the same output when the input remains unchanged, providing a unified scoring standard for the evaluation of the risk of customer information leakage in the customer information system. It has accuracy, stability and universal applicability; and the evaluation efficiency of the radial basis function neural network obtained by this method is better than manual evaluation, and has higher evaluation efficiency.

Description

technical field [0001] This application relates to the technical field of machine learning, and more specifically, relates to a construction method and construction system of a customer information leakage risk assessment system. Background technique [0002] Customer information system refers to a system that contains a large amount of customer information used in various industries. Generally, a customer information system contains multiple application pages for displaying customer information, and also stores a large amount of customer information. Once these customer information Leakage may cause unpredictable economic losses and adverse social impacts on customers and enterprises. [0003] Research on the assessment of customer information leakage risk in customer information systems is still in its infancy. The existing assessment of customer information leakage risk in customer information systems basically uses the method of technical personnel relying on subjective ...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the above-mentioned technical problems, the present invention provides a construction method and construction system of a customer information leakage risk assessment system to solve the deficiency in the prior art of relying on the subjective experience of technicians to judge the customer information leakage risk of the customer information system. Issues with unified scoring standards and low evaluation efficiency

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