Data sharing method and system of industrial internet

Abstract

The invention relates to a data sharing method and system for an industrial internet, and the method comprises the steps: obtaining original data, and dividing the original data according to the confidentiality of the original data; obtaining user information, and obtaining original data of a corresponding confidential degree according to the user information; performing corresponding desensitization processing on the original data with different confidentiality degrees according to the confidentiality degrees of the original data and the user information, wherein the desensitization processing is used for adjusting the display degrees of the original data with different confidentiality degrees; the system is used for executing the method. According to the method, different desensitization processing is carried out on the original data according to the levels of each partner and company internal personnel and the confidentiality degree of the original data, so that the security during data sharing is ensured, and meanwhile, the data can be reasonably shared to the partner.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet data sharing, and in particular to a data sharing method and system for industrial Internet. Background Art

[0002] With the rapid development of new-generation information technologies such as the Internet of Things, cloud computing, big data, and artificial intelligence, industrial manufacturing has begun to move towards digitalization, networking, and intelligence. The data collection, transmission, and processing capabilities of industrial equipment, production lines, and the entire industrial chain have been greatly improved, providing the basic conditions for data sharing.

[0003] In the context of globalization, competition among enterprises has gradually shifted to competition within the ecosystem. Enterprises need to cooperate deeply with other enterprises, scientific research institutions, service agencies, etc. Targeted data sharing has become a key means to enhance supply chain synergy and strengthen innovation capabilities.

[0004] At present, how to provide security protection for intelligence data and how to safely share data with partners are issues that the industry urgently needs to address. Summary of the invention

[0005] In order to solve the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide a data sharing method and system for the industrial Internet to solve the technical problem that the prior art cannot be safely shared with partners.

[0006] The data sharing method of the industrial Internet described in the present invention includes: obtaining original data, and dividing the original data according to the confidentiality level of the original data;

[0007] Obtain user information, and obtain original data of corresponding confidentiality level according to the user information;

[0008] According to the confidentiality level of the original data and user information, the original data with different confidentiality levels are subjected to corresponding desensitization processing, and the desensitization processing is used to adjust the display level of the original data with different confidentiality levels.

[0009] Preferably, the obtaining of the original data includes dividing the original data according to the confidentiality level of the original data: the original data includes personal information, identity information, financial information and business information; the dividing of the original data according to the confidentiality level of the original data includes:

[0010] Calculate the sensitivity score for the original data:

[0011] The sensitivity score is obtained according to the following criteria:

[0012] If the original data contains personal information, 1 point is awarded;

[0013] If the original data contains identity information, 3 points are awarded;

[0014] If the original data contains financial information, 5 points are awarded;

[0015] If the original data contains commercial information, 8 points will be awarded;

[0016] The original data after the sensitivity score is calculated is preprocessed to obtain preprocessed data, wherein the preprocessed data includes the initial sensitivity score of the original data, and the preprocessed data is divided into the following levels according to the confidentiality degree:

[0017] Leadership level: pre-processed data with a sensitivity score of 8 or more;

[0018] Management level: pre-processed data with a sensitivity score between 4 and 7;

[0019] Staff level: pre-processed data with sensitivity scores between 1 and 3 points;

[0020] Temporary worker level: pre-processed data with a sensitivity score less than 1.

[0021] Preferably, the obtaining of user information and obtaining original data of corresponding confidentiality level according to the user information include: the user information includes name, company name and position; the user information is matched with preset roles, the preset roles include company personnel and partner personnel, the company personnel are divided into levels, including: company leadership, company management, company staff and company temporary workers; the partner personnel are divided into levels, including: partner leadership, partner management, partner staff and partner temporary workers;

[0022] If it is determined to be a company employee, the level of the pre-processed data will correspond to the preset role;

[0023] If the user is determined to be a partner, the correlation between the partner to which the user belongs and the company is confirmed based on the user information, and the initial sensitivity score in the preprocessed data is adjusted based on the correlation to obtain adjusted preprocessed data; the adjusted preprocessed data is classified according to the degree of confidentiality and corresponds to the preset role.

[0024] Preferably, the step of confirming the relevance between the partner to which the user belongs and the company according to the user information, and adjusting the initial sensitivity score in the pre-processed data according to the relevance includes:

[0025] The correlation is calculated by the following formula:

[0026] Degree of association = w1×number of partners / number of cooperative projects + w2×number of cooperative resources / number of cooperative achievements + w3×success rate of cooperative projects;

[0027] The w1, w2 and w3 are weights of the corresponding indicators, w1+w2+w3=1, and the value range of the correlation degree is (0, 1];

[0028] After obtaining the correlation, the initial sensitivity score in the preprocessed data is adjusted according to the correlation according to the following formula:

[0029] Adjusted sensitivity score = initial sensitivity score / correlation score.

[0030] Preferably, the desensitizing of original data of different confidentiality levels according to the confidentiality level of the original data and user information includes:

[0031] Determine the user information. If the user information is for internal personnel, desensitize the pre-processed data according to the preset role level and the corresponding confidentiality level in the following manner:

[0032] For pre-processed data with a confidentiality level lower than that corresponding to the preset role level, no desensitization will be performed;

[0033] For pre-processed data with a confidentiality level equal to the preset role level, a light desensitization process is performed;

[0034] For pre-processed data with a confidentiality level higher than that corresponding to the preset role level, moderate desensitization is performed;

[0035] If the user information is of an external person, the pre-processed data will be desensitized as follows based on the preset role level, the corresponding confidentiality level of the pre-processed data, and the relevance between the partner company to which the external person belongs and the company:

[0036] Partners with a correlation degree ∈(0, 0.5] are defined as low-correlation partners, and partners with a correlation degree ∈(0.5, 1] ​​are defined as high-correlation partners;

[0037] For partners with low correlation, the pre-processed data with a confidentiality level lower than the preset role level will be lightly desensitized;

[0038] The pre-processed data with the confidentiality level corresponding to the preset role level shall be subjected to moderate desensitization processing;

[0039] Pre-processed data with a confidentiality level higher than the preset role level will be highly desensitized;

[0040] For highly relevant partners, pre-processed data with a confidentiality level lower than that corresponding to the preset role level will not be desensitized;

[0041] The pre-processed data with a confidentiality level equal to the preset role level is lightly desensitized;

[0042] Pre-processed data with a confidentiality level higher than that corresponding to the preset role level will be subjected to moderate desensitization.

[0043] The present invention also provides a data sharing system for industrial Internet, comprising a data classification module, a user classification module, a data processing module and a data desensitization module;

[0044] The data classification module is used to capture the required original data in real time or periodically, and classify the original data according to the confidentiality level;

[0045] The user classification module is used to obtain user information and correspond to preset roles according to the user information;

[0046] The data processing module is used to process the original data and the user information;

[0047] The data desensitization module is used to perform corresponding desensitization processing on original data of different confidentiality levels according to the confidentiality level of the original data and user information.

[0048] The data sharing method of the industrial Internet described in the present invention has the advantages of:

[0049] By performing different desensitization processes on the original data based on the level of each partner and internal company personnel and the confidentiality of the original data, we ensure the security of data sharing and at the same time ensure that the data can be shared with partners reasonably. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of an industrial Internet data sharing method described in the present invention. DETAILED DESCRIPTION

[0051] like Figure 1 As shown, the data sharing method of an industrial Internet described in the present invention includes:

[0052] Acquire original data, and divide the original data according to the confidentiality level of the original data;

[0053] Obtain user information, and obtain original data of corresponding confidentiality level according to the user information;

[0054] According to the confidentiality level of the original data and user information, the original data with different confidentiality levels are subjected to corresponding desensitization processing, and the desensitization processing is used to adjust the display level of the original data with different confidentiality levels.

[0055] Further, original data is obtained, and the original data is divided according to the confidentiality level of the original data: the original data includes personal information, identity information, financial information and business information; the division of the original data according to the confidentiality level of the original data includes:

[0056] Calculate the sensitivity score for the original data:

[0057] The sensitivity score is obtained according to the following criteria:

[0058] If the original data contains personal information, 1 point is awarded;

[0059] If the original data contains identity information, 3 points are awarded;

[0060] If the original data contains financial information, 5 points are awarded;

[0061] If the original data contains commercial information, 8 points will be awarded;

[0062] The original data after the sensitivity score is calculated is preprocessed to obtain preprocessed data, wherein the preprocessed data includes the initial sensitivity score of the original data, and the preprocessed data is divided into the following levels according to the confidentiality degree:

[0063] Leadership level: pre-processed data with a sensitivity score of 8 or more;

[0064] Management level: pre-processed data with a sensitivity score between 4 and 7;

[0065] Staff level: pre-processed data with sensitivity scores between 1 and 3 points;

[0066] Temporary worker level: pre-processed data with a sensitivity score less than 1.

[0067] Further, obtaining user information, and obtaining original data of corresponding confidentiality level according to the user information includes: the user information includes name, company name and position; matching the user information with preset roles, the preset roles include company personnel and partner personnel, the company personnel are divided into levels, including: company leadership, company management, company staff and company temporary workers; the partner personnel are divided into levels, including: partner leadership, partner management, partner staff and partner temporary workers;

[0068] If it is determined to be a company employee, the level of the pre-processed data will correspond to the preset role;

[0069] If the user is determined to be a partner, the correlation between the partner to which the user belongs and the company is confirmed based on the user information, and the initial sensitivity score in the preprocessed data is adjusted based on the correlation to obtain adjusted preprocessed data; the adjusted preprocessed data is classified according to the degree of confidentiality and corresponds to the preset role.

[0070] For example, you can choose to design a permission model based on the RBAC model. First, conduct a demand analysis and permission model design, analyze system functions, user roles and their responsibilities, clarify operations that require permission control, and create roles based on business needs: administrators, ordinary users, partners, etc. Then divide the permission granularity, determine the permission level, including functional permissions, data permissions, and set detailed permission units, including CRUD operations of create, read, update, and delete; at the same time, design a role permission matrix to clarify which permissions each role should have, and form a mapping relationship between roles and permissions, and then build an RBAC architecture. Users are assigned one or more roles in the system, and a set of permissions is assigned to each role. According to the roles the user has, the corresponding permissions are dynamically loaded for them, and then the access control list ACL is designed to specify which roles are allowed or prohibited to access each data object, as well as the operations that can be performed. When a user requests access to a data object, the system will search the ACL list based on the role it has to determine whether the user has the corresponding access rights.

[0071] Further, confirming the relevance between the partner to which the user belongs and the company according to the user information, and adjusting the initial sensitivity score in the pre-processed data according to the relevance includes:

[0072] The correlation is calculated by the following formula:

[0073] Degree of association = w1×number of partners / number of cooperative projects + w2×number of cooperative resources / number of cooperative achievements + w3×success rate of cooperative projects;

[0074] The w1, w2 and w3 are weights of the corresponding indicators, w1+w2+w3=1, and the value range of the correlation degree is (0, 1];

[0075] After obtaining the correlation, the initial sensitivity score in the preprocessed data is adjusted according to the correlation according to the following formula:

[0076] Adjusted sensitivity score = initial sensitivity score / correlation score.

[0077] Exemplarily, taking w1=0.3, w2=0.3, w3=0.4 as an example, assuming that the score information of a certain preprocessed data contains one financial information and two personal information, that is, the initial score of the data is 7 points, for the company's personnel, the preprocessed data belongs to the preprocessed data of the management level, and correspondingly, the company's personnel who are above the management level can see the preprocessed data; for the personnel of Company B, the number of partners between Company B and the company is 20, the number of cooperative projects is 50, the number of cooperative resources is 35, the number of cooperative results is 60, and the success rate of cooperative projects is 70%. The calculation shows that the correlation between Company B and the company = 0.3*20 / 50+0.3*35 / 60+0.4*70% = 0.575; According to the above formula, the adjusted sensitivity score = 7 / 0.575≈12, that is, for the personnel of Company B, only the leadership level of Company B can see the preprocessed data, and the other levels will perform corresponding desensitization when browsing the preprocessed data.

[0078] Furthermore, desensitizing the original data of different confidentiality levels according to the confidentiality level of the original data and user information includes:

[0079] Determine the user information. If the user information is for internal personnel, desensitize the pre-processed data according to the preset role level and the corresponding confidentiality level in the following manner:

[0080] For pre-processed data with a confidentiality level lower than that corresponding to the preset role level, no desensitization will be performed;

[0081] For pre-processed data with a confidentiality level equal to the preset role level, a light desensitization process is performed;

[0082] For pre-processed data with a confidentiality level higher than that corresponding to the preset role level, moderate desensitization is performed;

[0083] If the user information is of an external person, the pre-processed data will be desensitized as follows based on the preset role level, the corresponding confidentiality level of the pre-processed data, and the relevance between the partner company to which the external person belongs and the company:

[0084] Partners with a correlation degree ∈(0, 0.5] are defined as low-correlation partners, and partners with a correlation degree ∈(0.5, 1] ​​are defined as high-correlation partners;

[0085] For partners with low correlation, the pre-processed data with a confidentiality level lower than the preset role level will be lightly desensitized;

[0086] The pre-processed data with the confidentiality level corresponding to the preset role level shall be subjected to moderate desensitization processing;

[0087] Pre-processed data with a confidentiality level higher than the preset role level will be highly desensitized;

[0088] For highly relevant partners, pre-processed data with a confidentiality level lower than that corresponding to the preset role level will not be desensitized;

[0089] The pre-processed data with a confidentiality level equal to the preset role level is lightly desensitized;

[0090] Pre-processed data with a confidentiality level higher than that corresponding to the preset role level will be subjected to moderate desensitization.

[0091] Specifically, mild desensitization involves only minimal modification of sensitive data to ensure the security of data in non-production environments; moderate desensitization may include partial character masking, data summary or hashing; and high desensitization means completely removing or replacing all sensitive information. In severe desensitization, data may be encrypted or completely converted to a non-identifiable format.

[0092] For example, for personal information, mild desensitization means retaining only part of the visible information and replacing the rest with *; moderate desensitization means using code to replace; high desensitization means using statistical methods to generate simulated data that is similar to the original data distribution but does not have individual orientation, adding random noise to protect individual data, while retaining the overall statistical characteristics as much as possible;

[0093] Other types of information can also be desensitized by imitating the above situation;

[0094] For example, for financial data or statistical indicators, mild masking means converting them into intervals, and the income range is displayed as "XY yuan" instead of the specific amount; for geographic location, mild masking means being accurate to the city level rather than the specific latitude and longitude or street address; for dates, mild masking means only displaying the year or the year and month, not the specific date, etc.

[0095] Because the sensitivity scores of various data have been converted for partner users when judging user information, even at the partner leadership level, this method will grade the adjusted scores according to the above-mentioned confidentiality levels when displaying pre-processed data, that is, it can increase the thresholds of some more sensitive data that does not need to be provided to partners, thereby ensuring that lower-level personnel among partners cannot obtain more information, ensuring the security of the company's data while the data can be reasonably shared with partners.

[0096] The present invention also provides a data sharing system for industrial Internet, comprising a data classification module, a user classification module, a data processing module and a data desensitization module;

[0097] The data classification module is used to capture the required original data in real time or periodically, and classify the original data according to the confidentiality level;

[0098] The user classification module is used to obtain user information and correspond to preset roles according to the user information;

[0099] The data processing module is used to process the original data and the user information;

[0100] The data desensitization module is used to perform corresponding desensitization processing on original data of different confidentiality levels according to the confidentiality level of the original data and user information.

[0101] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present invention and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present invention.

[0102] For those skilled in the art, various other corresponding changes and deformations can be made according to the technical solutions and concepts described above, and all of these changes and deformations should fall within the protection scope of the claims of the present invention.

Claims

1. A data sharing method for industrial Internet, characterized in that: include: Acquire original data, and divide the original data according to the confidentiality level of the original data; Obtain user information, and obtain original data of corresponding confidentiality level according to the user information; According to the confidentiality level of the original data and user information, the original data with different confidentiality levels are subjected to corresponding desensitization processing, and the desensitization processing is used to adjust the display level of the original data with different confidentiality levels.

2. The data sharing method of the industrial Internet according to claim 1 is characterized in that: The obtaining of the original data, and dividing the original data according to the confidentiality level of the original data: the original data includes personal information, identity information, financial information and commercial information; the dividing of the original data according to the confidentiality level of the original data includes: Calculate the sensitivity score for the original data: The sensitivity score is obtained according to the following criteria: If the original data contains personal information, 1 point is awarded; If the original data contains identity information, 3 points are awarded; If the original data contains financial information, 5 points are awarded; If the original data contains commercial information, 8 points will be awarded; The original data after the sensitivity score is calculated is preprocessed to obtain preprocessed data, wherein the preprocessed data includes the initial sensitivity score of the original data, and the preprocessed data is divided into the following levels according to the confidentiality degree: Leadership level: pre-processed data with a sensitivity score of 8 or more; Management level: pre-processed data with a sensitivity score between 4 and 7; Staff level: pre-processed data with a sensitivity score between 1 and 3 points; Temporary worker level: pre-processed data with a sensitivity score less than 1.

3. The data sharing method of the industrial Internet according to claim 2 is characterized in that: The obtaining of user information and obtaining original data of corresponding confidentiality level according to the user information include: the user information includes name, company name and position; the user information is matched with preset roles, the preset roles include company personnel and partner personnel, the company personnel are divided into levels, including: company leadership, company management, company staff and company temporary workers; the partner personnel are divided into levels, including: partner leadership, partner management, partner staff and partner temporary workers; If it is determined to be a company employee, the level of the pre-processed data will correspond to the preset role; If it is determined that the user is a partner, the correlation between the partner to which the user belongs and the company is confirmed based on the user information, and the initial sensitivity score in the pre-processed data is adjusted based on the correlation to obtain adjusted pre-processed data; the adjusted pre-processed data is classified according to the degree of confidentiality and corresponds to the preset role.

4. The data sharing method of the industrial Internet according to claim 3 is characterized in that: The step of confirming the correlation between the partner to which the user belongs and the company according to the user information, and adjusting the initial sensitivity score in the pre-processed data according to the correlation includes: The correlation is calculated by the following formula: Degree of association = w1×number of partners / number of cooperative projects + w2×number of cooperative resources / number of cooperative achievements + w3×success rate of cooperative projects; The w1, w2 and w3 are weights of the corresponding indicators, w1+w2+w3=1, and the value range of the correlation degree is (0, 1]; After obtaining the correlation, the initial sensitivity score in the preprocessed data is adjusted according to the correlation according to the following formula: Adjusted sensitivity score = initial sensitivity score / correlation score.

5. The data sharing method of the industrial Internet according to claim 4 is characterized in that: The desensitizing of the original data with different confidentiality levels according to the confidentiality level of the original data and the user information includes: Determine the user information. If the user information is for internal personnel, desensitize the pre-processed data according to the preset role level and the corresponding confidentiality level in the following manner: For pre-processed data with a confidentiality level lower than that corresponding to the preset role level, no desensitization will be performed; For pre-processed data with a confidentiality level equal to the preset role level, a light desensitization process is performed; For pre-processed data with a confidentiality level higher than that corresponding to the preset role level, moderate desensitization is performed; If the user information is of an external person, the pre-processed data will be desensitized as follows based on the preset role level, the corresponding confidentiality level of the pre-processed data, and the relevance between the partner company to which the external person belongs and the company: Partners with a correlation degree ∈(0, 0.5] are defined as low-correlation partners, and partners with a correlation degree ∈(0.5, 1] ​​are defined as high-correlation partners; For partners with low correlation, the pre-processed data with a confidentiality level lower than the preset role level will be lightly desensitized; The pre-processed data with the confidentiality level corresponding to the preset role level shall be subjected to moderate desensitization processing; Pre-processed data with a confidentiality level higher than the preset role level will be highly desensitized; For highly relevant partners, pre-processed data with a confidentiality level lower than that corresponding to the preset role level will not be desensitized; The pre-processed data with a confidentiality level equal to the preset role level is lightly desensitized; Pre-processed data with a confidentiality level higher than that corresponding to the preset role level will be subjected to moderate desensitization.

6. An industrial Internet data sharing system, characterized in that: It includes data classification module, user classification module, data processing module and data desensitization module; The data classification module is used to capture the required original data in real time or periodically, and classify the original data according to the confidentiality level; The user classification module is used to obtain user information and correspond to preset roles according to the user information; The data processing module is used to process the original data and the user information; The data desensitization module is used to perform corresponding desensitization processing on original data of different confidentiality levels according to the confidentiality level of the original data and user information.

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