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User service security comprehensive risk assessment method based on combined weighting

A technology that combines empowerment and comprehensive risk, applied in data processing applications, instruments, character and pattern recognition, etc., can solve the problems of low risk differentiation ability, high overall risk, overlapping credit scores, etc., and achieves an intuitive security risk level evaluation system. , the use of promising effects

Pending Publication Date: 2020-07-03
SHANGHAI GUAN AN INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Specifically, users with high risks in all links have a higher overall risk than users with high risks in only one link
The risk comprehensive score obtained by the existing index statistical method usually cannot separate the evaluation results of risk users and normal users to the greatest extent, resulting in a large amount of overlap in the credit scores of the two, and the ability to distinguish risks is low
In addition, for enterprises with many business scenarios, multiple risk labels can only be obtained by listing user risks in important scenarios, so it is difficult to reflect the distribution of user risk behaviors in the whole process of business

Method used

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  • User service security comprehensive risk assessment method based on combined weighting
  • User service security comprehensive risk assessment method based on combined weighting
  • User service security comprehensive risk assessment method based on combined weighting

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] A method for evaluating the comprehensive risk of user business security based on combined empowerment, the specific steps are as follows:

[0030] Step 1, data processing: perform frequency statistics, proportion calculation, and labeling of the original data to form preliminary indicator variables. The source of the original data is multi-dimensional data extracted from the data warehouse, including business data, risk control log data, and SDK collection. Device data, IP data, etc.;

[0031] Step 2, risk indicator screening: screening risk indicators from the two aspects of differentiation and similarity;

[0032] Step 3, calculating the weight coefficient of single-method weighting: using the subjective weighting method and the objective weighting method to generate weight coefficients respectively;

[0033] Step 4, solving the combined weighting weight of multiple weighting methods, and calculating the comprehensive risk score of each user.

Embodiment 2

[0035] A method for evaluating the comprehensive risk of user business security based on combined empowerment, the specific steps are as follows:

[0036] Step 1, data processing: Perform frequency statistics, proportion calculation and labeling on the original data to form preliminary indicator variables. The numerical data in the original data should be standardized according to the meaning of the indicators. Standardization includes positive standardization, negative Normalization towards normalization and interval type; assuming v ij Indicates the index value of the j-th dimension variable of user i, the training set sample size is n, and the standardized index value is x ij . Indicators that are negatively correlated with user risk can be positively standardized, and the calculation method is as follows: Indicators that are positively correlated with user risk can be negatively standardized, and the calculation method is as follows: When the value of the variable is ...

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Abstract

The invention discloses a user service security comprehensive risk assessment method based on combined empowerment, and aims to solve the problem that the existing user risk behavior is difficult to reflect in the whole process. The method comprises the following specific steps: step 1, data processing: carrying out frequency statistics, proportion calculation and labeling on original data; step 2, risk index screening: risk index screening is carried out from two aspects of discrimination and similarity; 3, calculating the weighting coefficient of a single method; and step 4, solving a combined weighting weight of a plurality of weighting methods, and calculating a comprehensive risk score of each user. According to the invention, an index and model combined weight generation method is provided, the user overall risk scoring method has a risk identification capability, risk customers and non-risk customers can be significantly distinguished through scoring, and a security risk level evaluation system is more intuitive; the method provided by the invention has certain universality in business environments of different industries.

Description

technical field [0001] The invention relates to the field of computer data security, in particular to a method for evaluating comprehensive risk of user business security based on combination empowerment. Background technique [0002] In recent years, technologies such as big data risk control and intelligent risk control have been widely used. With the continuous expansion of the scale of C-end users, the prevention of business risks such as scammers, stolen brushes, and account theft has gradually become an indispensable module in the construction of enterprise security. Effective business security risk protection and anti-fraud measures can not only avoid the waste of corporate marketing costs, but also ensure that corporate marketing strategies can reach real users more accurately, and maintain corporate brand benefits to a certain extent. [0003] In most current big data risk control systems, technologies such as user behavior analysis, abnormal analysis based on equi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/26G06K9/62
CPCG06Q10/0635G06Q50/265G06F18/24323
Inventor 钱沁莹魏国富葛胜利汲丽钟丹阳
Owner SHANGHAI GUAN AN INFORMATION TECH