CN114840727A - Data compliance management method and device - Google Patents

Abstract

The present application provides a data compliance management method, which is characterized by comprising: prefabricating multiple management templates according to different user attributes; The management template is based on the management template, and a business process item is generated through the management template; wherein, the business process item includes a plurality of business nodes, and the business node has preset judgment conditions. When the data input by the user conforms to the preset judgment condition, the processing information corresponding to the data is recorded. In this application, by pre-producing management templates according to relevant regulations, effective risk management can be carried out in the aspect of privacy authorization and the occurrence of violations can be avoided.

Description

A data compliance management method and device

technical field

The present application relates to a data compliance detection technology, in particular to a data compliance management method. The present application also provides a data compliance management device.

Background technique

Data compliance means that in some commercial or social activities, if the user's behavior is not standardized, the data generated by the activity can be fully reflected, so compliance screening can be conducted through data compliance review.

In corporate activities, due to the limitations of laws and regulations and other factors, the personal privacy data required by its business activities requires customer authorization to avoid non-compliant behaviors. Therefore, data compliance analysis is performed to find risk points to solve non-compliant behaviors. Activities are especially important. At present, data compliance auditing is performed manually, which consumes a lot of manpower and material resources, and it is easy to infringe on the privacy of customers' information during the use process, resulting in risks.

SUMMARY OF THE INVENTION

In order to solve the risk problem that may occur during the use of customer information in the prior art, the present application provides a data compliance management method. The present application also provides a data compliance management device.

The present application provides a data compliance management method, which is characterized by comprising:

Pre-made multiple management templates corresponding to each type of user attribute according to different user attributes;

Obtain user information, retrieve the corresponding management template from the template library according to the user attributes in the user information, and generate business process items through the management template, including associating each type of data corresponding to the management template Management item, select a data management item from each category to generate a management template;

The business process item includes a plurality of business nodes, and the business nodes have preset judgment conditions. When the data input by the user meets the preset judgment conditions, processing information corresponding to the data is recorded.

Optionally, retrieving a corresponding management template from the template library according to the user attribute in the user information includes:

Retrieve the pre-trained AI model;

Enter user information in the AI model, and obtain a corresponding management template through the calculation of the AI model.

Optionally, the preset judgment condition includes: a compliance rule, and after the processing information is recorded, the processing information is subject to compliance review through the compliance rule.

Optionally, the compliance rules are set according to multiple determined rules and regulations.

Optionally, the management template is stored in a template library.

The application also provides a data compliance management device, including:

The template module is used to prefabricate multiple management templates corresponding to each type of user attributes according to different user attributes;

A retrieval module, configured to acquire user information, retrieve a corresponding management template from the template library according to the user attribute in the user information, and generate a business process item through the management template, including associating the management template For each type of data management item, select a data management item from each category to generate a management template;

The business process item includes a plurality of business nodes, and the business nodes have preset judgment conditions. When the data input by the user meets the preset judgment conditions, processing information corresponding to the data is recorded.

Optionally, retrieving a corresponding management template from the template library according to the user attribute in the user information includes:

Retrieve the pre-trained AI model;

Enter user information in the AI model, and obtain a corresponding management template through the calculation of the AI model.

Optionally, the preset judgment condition includes: a compliance rule, and after the processing information is recorded, the processing information is subject to compliance review through the compliance rule.

Optionally, the compliance rules are set according to multiple determined rules and regulations.

Optionally, the management template is stored in a template library.

The advantages of the present application relative to the prior art:

The present application provides a data compliance management method, which is characterized by comprising: pre-preparing a plurality of management templates corresponding to each type of user attributes according to different user attributes; acquiring user information, and according to the user attributes in the user information The corresponding management template is retrieved from the template library, and business process items are generated through the management template, including associating each type of data management item corresponding to the management template, and selecting a data management item from each category Generate a management template; wherein, the business process item includes a plurality of business nodes, and the business nodes have preset judgment conditions. When the data input by the user meets the preset judgment conditions, the processing information corresponding to the data is recorded. . In this application, by pre-producing management templates according to relevant regulations, effective risk management can be carried out in terms of privacy authorization, and violations can be avoided.

Description of drawings

FIG. 1 is a flowchart of data compliance management in this application.

FIG. 2 is a flow chart of directly obtaining a management template in this application.

FIG. 3 is a schematic diagram of the data compliance management apparatus in the present application.

Detailed ways

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar promotions without violating the connotation of the present application. Therefore, the present application is not limited by the specific implementation disclosed below.

The present application provides a data compliance management method, which is characterized by comprising: pre-preparing a plurality of management templates corresponding to each type of user attributes according to different user attributes; acquiring user information, and according to the user attributes in the user information The corresponding management template is retrieved from the template library, and business process items are generated through the management template, including associating each type of data management item corresponding to the management template, and selecting a data management item from each category Generate a management template; wherein, the business process item includes a plurality of business nodes, and the business nodes have preset judgment conditions. When the data input by the user meets the preset judgment conditions, the processing information corresponding to the data is recorded. . In this application, by pre-producing management templates according to relevant regulations, effective risk management can be carried out in terms of privacy authorization, and violations can be avoided.

FIG. 1 is a flowchart of data compliance management in this application.

Referring to Figure 1, S101 prefabricates multiple management templates according to different user attributes;

The user attributes refer to the user's type, business activity mode, etc., such as the user's business items, customer information to be acquired, and the like. A preferred method is to set tags according to the protection items listed in the Personal Information Protection Law, and then use the tags as user attributes after associating the tags with user demand data.

The user mentioned in this application refers to an enterprise or other organization that serves customers, and the user needs to improve and analyze the service by analyzing the information of the customer to better improve the service. The customer refers to the individual served by the user.

The technical solutions described in this application belong to a third party, and in the following description, the third party is collectively referred to as a system party for simplicity.

The system party first establishes a plurality of management templates according to the basic file of data compliance and user attributes, and the basic file may preferably be the "Personal Information Protection Law". The management template can correspond to each type of user attributes as exhaustively as possible, and of course can also be personalized according to the user attributes.

After multiple management templates are established, the management templates will be stored in the template library for subsequent calls. In addition, when the basic file is changed or updated, the management template is also updated accordingly.

Referring to FIG. 1, S102 obtains user information, retrieves a corresponding management template from the template library according to the user attribute in the user information, and generates a business process item through the management template; wherein, the business The process item includes a plurality of service nodes, and the service nodes have preset judgment conditions. When the data input by the user meets the preset judgment conditions, processing information corresponding to the data is recorded.

When the user needs to use it, he first inputs his own mark or information, and the attribute information of the user can be extracted according to the mark or information. A preferred method is that the user inputs his own related information, and the system automatically extracts the attribute information according to the related information. Another preferred method is that the user only needs to input his own mark, the system has already stored the attribute data corresponding to the mark, and directly correspondingly obtains the user's attribute information according to the mark. Another preferred way is to obtain the management template directly according to the user information.

FIG. 2 is a flow chart of directly obtaining a management template in this application.

Referring to Figure 2, S201 retrieves the pre-trained AI model;

The AI model shown is pre-trained. The training method is to first store the AI model in the cloud, download the AI model when the user selects a template, and obtain the user's data information and the finalized template. , perform training, and the user determines the final template, updates the parameters according to the template determined by the user, uploads the parameters of the trained AI model to the cloud to update the AI model in the cloud, and waits and repeats the next training. The AI model described in this application can be continuously optimized.

S202 Input user information in the AI model, and obtain a corresponding management template through the calculation of the AI model.

After the attribute data is acquired, a corresponding management template can be retrieved from the template library according to the attribute data, and then a business process item can be generated according to the management template.

Specifically, the template provides the type and method of data compliance management, and the data management items in the template need to be set by the user. In the present application, the data management item is constructed as a draggable graphical module, and the user only needs to select and drag the module to complete the management template.

In the present application, the data management items are set separately, and each item in the basic file is regarded as a category, and data management items for different users are set, which is characterized by different management items set according to different usage scenarios of users .

After selecting the management template, each type of data management item corresponding to the management template is associated with the template, and then the user selects a data management item from each category, and finally generates a complete version of the management template.

Finally, a business process item is generated according to the data management item of the template, and the business process item has a plurality of business nodes corresponding to each data management item respectively. Specifically, each of the service nodes has preset judgment conditions, and when the data input by the user meets the preset judgment conditions, processing information corresponding to the data is recorded. For example, when a user retrieves a customer's information, a corresponding service node will determine whether the information can be invoked, and if so, run the invocation and record it in the log.

In the present application, the setting of the judgment condition can be performed by a computer program. A preferred method is to first cut the basis for data compliance, that is, various determined laws and regulations, and divide it into multiple compliance modules, such as: identity module, credit module, and privacy module. Specifically, those skilled in the art Personnel can be divided according to the actual situation. After the split is completed, a label is set for each of the models, and the label is extracted according to the customer's data information. Preferably, a plurality of information category tags are preset, and different categories in the user's information are tagged with tags to obtain customer data information with tags.

On the other hand, the label is correspondingly set in each law, so that each law is set as the law marked by the label, and each law can be set with multiple labels. Next, make a label correspondence table, that is, combine all the labels, and associate each label group after the combination with the corresponding law.

After acquiring the customer's data information, extract a plurality of tags from the data information, generate a query tag group, query the corresponding law from the tag table through the query tag group, extract the law, and The restrictive description of the said statute serves as a judgment condition. Specifically, a data set is established according to the restrictive description, and it is judged whether the steps of the user operating on the customer's data information are in the data set or outside the data set, and then judge whether it is compliant.

Preferably, the preset judgment conditions include: compliance rules, which are used to define whether the information of the displayed customer and whether the processing of the information violates the rules. The compliance rules are set according to the determined one or more rules and regulations.

The compliance rules are described in one or more ways including regular expressions, numerical ranges, and numerical feature matrices.

When a regular expression or a numerical range is used to describe a compliance rule, the regular expression or numerical range needs to be manually predefined according to one or more determined rules and regulations, and stored in the system database.

When using the numerical feature matrix to describe the compliance rule description, calculate the similarity between the user data information and the numerical feature matrix to obtain the compliance similarity value; when the compliance similarity value is greater than the preset similarity threshold, the The above user data information is compliant, otherwise it is not compliant.

The present application also provides a data compliance management device, including: a template module 301 and a retrieval module 302 .

FIG. 3 is a schematic diagram of the data compliance management apparatus in the present application.

Referring to FIG. 3 , the template module 301 is used to pre-create multiple management templates according to different user attributes.

The user attributes refer to the user's type, business activity mode, etc., such as the user's business items, customer information to be acquired, and the like. A preferred method is to set tags according to the protection items listed in the Personal Information Protection Law, and then use the tags as user attributes after associating the tags with user demand data.

The user mentioned in this application refers to an enterprise or other organization that serves customers, and the user needs to improve and analyze the service through the information of the customer to better improve the service. The customer refers to the individual served by the user.

The technical solutions described in this application belong to a third party, and in the following description, the third party is collectively referred to as a system party for simplicity.

The system party first establishes a plurality of management templates according to the basic file of data compliance and user attributes, and the basic file may preferably be the "Personal Information Protection Law". The management template can correspond to each type of user attributes as exhaustively as possible, and of course, can also be personalized according to the user attributes. Here, those skilled in the art can select according to the actual situation, and details are not repeated here.

After multiple management templates are established, the management templates will be stored in the template library for subsequent calls. In addition, when the basic file is changed or updated, the management template is also updated accordingly.

Referring to FIG. 1, the retrieval module 302 is configured to acquire user information, retrieve a corresponding management template from the template library according to the user attribute in the user information, and generate a business process item through the management template ; wherein, the business process item includes a plurality of business nodes, the business nodes have preset judgment conditions, and when the data input by the user meets the preset judgment conditions, the processing information corresponding to the data is recorded.

When the user needs to use it, he first inputs his own mark or information, and the attribute information of the user can be extracted according to the mark or information. A preferred method is that the user inputs his own related information, and the system automatically extracts the attribute information according to the related information. Another preferred method is that the user only needs to input his own mark, the system has already stored the attribute data corresponding to the mark, and directly correspondingly obtains the user's attribute information according to the mark. Another preferred way is to obtain the management template directly according to the user information, including: retrieving a pre-trained AI model; inputting user information into the AI model, and obtaining the corresponding management template through the calculation of the AI model.

The AI model is obtained in the following ways:

Selecting a user information sample and manually marking it according to the user information, marking the management template number corresponding to each piece of data in the user information sample;

Perform data feature extraction on the user information sample, and package it with the corresponding management template number to form a management template sample data set;

splitting the management template sample data set into a management template model training set and a management template model test set;

Adopt a machine learning algorithm to train the management template model by relying on the management template model training set, and use the management template model test set to evaluate the management template model;

Adjust the parameters to continuously train the model until the recall rate and accuracy rate meet the preset thresholds, and output the management template model;

The output management template model is the AI model.

It can be understood that the machine learning algorithms used in the training of the AI model include: logistic regression algorithm, decision tree, genetic algorithm, support vector machine (SVN), K-means algorithm, random forest and naive Bayes algorithm, When different algorithms are used, their program designs are different, but they are all mature technical means, and those skilled in the art can completely implement the algorithm smoothly according to the description of the above-mentioned embodiment, which is not repeated here.

After the attribute data is acquired, a corresponding management template can be retrieved from the template library according to the attribute data, and then a business process item can be generated according to the management template.

Specifically, the template provides the type and method of data compliance management, and the data management items in the template need to be set by the user. In the present application, the data management item is constructed as a draggable graphical module, and the user only needs to select and drag the module to complete the management template.

In the present application, the data management items are set separately, and data management items for different users are set according to each item in the basic file as a category, which is characterized by different management items set according to different usage scenarios of users.

After selecting the management template, each type of data management item corresponding to the management template will be associated according to the template, and then the user will create a data management item from each category, and finally generate a complete version of the management template.

Finally, a business process item is generated according to the data management item of the template, and the business process item has a plurality of business nodes corresponding to each data management item respectively. Specifically, each of the service nodes has preset judgment conditions, and when the data input by the user meets the preset judgment conditions, processing information corresponding to the data is recorded. For example, when a user retrieves a customer's information, a corresponding service node will determine whether the information can be invoked, and if so, run the invocation and record it in the log.

In the present application, the setting of the judgment condition can be performed by a computer program. A preferred method is to first cut the basis for data compliance, that is, various determined laws and regulations, and divide it into multiple compliance modules, such as: identity module, credit module, and privacy module. Specifically, those skilled in the art Personnel can be divided according to the actual situation. After the split is completed, a label is set for each of the models, and the label is extracted according to the customer's data information. Preferably, a plurality of information category tags are preset, and different categories in the user's information are tagged with tags to obtain customer data information with tags.

On the other hand, the labels are correspondingly set in each law, so that each clockwork is set as the law marked by the label, and each law can be set with multiple labels. Next, make a label correspondence table, that is, combine all the labels, and associate each label group after the combination with the corresponding law.

After acquiring the customer's data information, extract a plurality of tags from the data information, generate a query tag group, query the corresponding law from the tag table through the query tag group, extract the law, and The restrictive description of the said statute serves as a judgment condition. Specifically, a data set is established according to the restrictive description, and it is judged whether the steps of the user operating on the customer's data information are in the data set or outside the data set, and then judge whether it is compliant.

Preferably, the preset judgment conditions include: compliance rules, which are used to define whether the information of the displayed customer and whether the processing of the information violates the rules. The compliance rules are set according to the determined one or more rules and regulations.

Claims (10)

1. A data compliance management method, comprising: Pre-made multiple management templates corresponding to each type of user attributes according to different user attributes; Obtain user information, retrieve the corresponding management template from the template library according to the user attributes in the user information, and generate business process items through the management template, including associating each type of data corresponding to the management template Management item, select a data management item from each category to generate a management template; The business process item includes a plurality of business nodes, and the business nodes have preset judgment conditions. When the data input by the user meets the preset judgment conditions, processing information corresponding to the data is recorded. 2 . The data compliance management method according to claim 1 , wherein the retrieving the corresponding management template from the template library according to the user attribute in the user information comprises: 2 . Retrieve the pre-trained AI model; Enter user information in the AI model, and obtain a corresponding management template through the calculation of the AI model. 3 . The data compliance management method according to claim 1 , wherein the preset judgment conditions comprise: compliance rules. 4 . 4 . The data compliance management method according to claim 3 , wherein the compliance rules are set according to one or more determined rules and regulations. 5 . 5. The data compliance management method according to claim 1, wherein the management template is stored in a template library. 6. A data compliance management device, comprising: The template module is used for prefabricating multiple management templates corresponding to each type of user attributes according to different user attributes; a retrieval module, configured to acquire user information, retrieve a corresponding management template from the template library according to the user attribute in the user information, and generate a business process item through the management template, including associating the management template For each type of data management item, select a data management item from each category to generate a management template; The business process item includes a plurality of business nodes, and the business nodes have preset judgment conditions. When the data input by the user meets the preset judgment conditions, processing information corresponding to the data is recorded. 7 . The data compliance management device according to claim 6 , wherein the retrieving a corresponding management template from the template library according to the user attribute in the user information comprises: 8 . Retrieve the pre-trained AI model; Enter user information in the AI model, and obtain a corresponding management template through the calculation of the AI model. 8 . The data compliance management device according to claim 6 , wherein the preset judgment conditions comprise: compliance rules. 9 . 9 . The data compliance management device according to claim 3 , wherein the compliance rules are set according to one or more determined rules and regulations. 10 . 10. The data compliance management apparatus according to claim 1, wherein the management template is stored in a template library.

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