A data dynamic desensitization method, device, equipment, medium and product

Abstract

The present invention discloses a method, device, equipment, medium and product for dynamic data desensitization, and relates to the technical field of data desensitization. The method is to obtain a sensitive data configuration set and a data classification configuration set and receive at least two columns of data to be desensitized, and then determine the subject identity identification results and sensitive identification results of the current historical data and all the current non-history data based on the above two sets, and then determine the relationship value between the current historical data and each current non-history data based on the above two results, and cumulatively calculate the total value of the current historical data, and finally decide whether to perform data desensitization processing on the current historical data based on the comparison result of the total value and the preset value, so that after the sensitive data and the like are set, the data relationship can be used to adapt to the diversified combination of data to be desensitized and complete dynamic desensitization, avoiding the risk of sensitive information being desensitized and bypassed to cause information security accidents, and simplify the settings to improve the user experience.

Description

Technical Field

[0001] The present invention belongs to the technical field of data desensitization, and specifically relates to a data dynamic desensitization method, device, equipment, medium and product. Background Art

[0002] Data desensitization refers to the deformation of certain sensitive information through desensitization rules to achieve reliable protection of sensitive privacy data, so that the desensitized real data set can be safely used in development, testing and other non-production environments or partial production environments and outsourced environments. Dynamic data desensitization generally desensitizes certain sensitive information of the data source in real time, and is mostly used in production environments.

[0003] At present, although the existing data dynamic desensitization systems have done a lot of work on desensitization technology and rules, and can achieve data desensitization in real time according to the set rules, these systems usually have strict regulations on the data that needs to be desensitized, that is, some data is sensitive data in some scenarios, but not in other scenarios. On the contrary, some data is not set as sensitive data, but it may become sensitive information and be leaked after multiple splicing. In order to comply with the regulations, either all data must be desensitized, or in order to distinguish these application scenarios, very complicated settings must be made, or another data desensitization system must be set up. The above measures will not only increase the complexity of the system, but also cause sensitive information to be desensitized and bypassed, resulting in information security incidents.

[0004] In the face of the above situation, the existing data dynamic desensitization scheme is based on pre-set sensitive data and desensitization rules to perform targeted desensitization on the data to be desensitized returned by the request. However, this scheme obviously has the following problems: (1) There is a lot of sensitive data that needs to be pre-set, which makes the setting very laborious and affects the user experience; (2) Since the setting is fixed and the data to be desensitized returned by the request is different each time, it is impossible to dynamically desensitize the diverse data combinations, which leads to the risk of sensitive information being desensitized and bypassed, causing information security accidents. Therefore, how to dynamically desensitize the diverse data combinations based on the pre-set results is a topic that technicians in this field urgently need to study. Summary of the invention

[0005] The purpose of the present invention is to provide a data dynamic desensitization method, device, computer equipment, computer readable storage product and computer program product to solve the problem that existing data dynamic desensitization schemes are prone to being unable to dynamically desensitize diverse data combinations due to their rigid settings.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, a method for dynamic data desensitization is provided, comprising:

[0008] Obtain a sensitive data configuration set and a data classification configuration set, wherein the sensitive data configuration set includes a plurality of sensitive class data, and the data classification configuration set includes a plurality of subject identity class data for determining a unique identity;

[0009] Receive at least two columns of data to be desensitized;

[0010] The method further comprises the following steps: traversing each column of the at least two columns of the data to be desensitized and not being the last column of the data to be desensitized in order from the front to the back of the at least two columns of the data to be desensitized: determining the subject identity class identification results of the current data in history and all the data not currently in history according to the data classification configuration set, and also determining the sensitive class identification results of the current data in history and all the data not currently in history according to the sensitive data configuration set, and then determining the subject identity class identification results and sensitive class identification results of the current data in history and all the data not currently in history according to the subject identity class identification results and the sensitive class identification results of the current data in history and all the data not currently in history According to the relationship value with each currently untraversed data in all the currently untraversed data, and cumulatively calculating to obtain the total value of the currently in-traversal data, finally, if the total value of the currently in-traversal data is greater than or equal to the preset value, performing data desensitization processing on the currently in-traversal data to obtain the desensitized data corresponding to the currently in-traversal data, otherwise directly using the currently in-traversal data as the desensitized data corresponding to the currently in-traversal data, wherein the currently in-traversal data refers to the data to be desensitized that is currently being traversed, and the currently untraversed data refers to the data to be desensitized that is not currently being traversed;

[0011] The last column of the data to be desensitized in the at least two columns of the data to be desensitized is directly used as the desensitized data corresponding to the last column of the data to be desensitized;

[0012] Output at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized.

[0013] Based on the above invention content, a new scheme for dynamic data desensitization based on the principle that data relationship determines data value is provided, that is, after obtaining a sensitive data configuration set and a data classification configuration set and receiving at least two columns of data to be desensitized, the subject identity identification results and sensitive identification results of the current historical data and all the current non-historical data are first determined based on the aforementioned two sets, and then the relationship value of the current historical data and each current non-historical data is determined based on the aforementioned two results, and the total value of the current historical data is accumulated and calculated. Finally, based on the comparison result of the total value and the preset value, it is decided whether to perform data desensitization on the current historical data. In this way, after the sensitive data and the like are set, the data relationship can be used to adapt to the diverse combinations of data to be desensitized and complete dynamic desensitization, thereby avoiding the risk of information security incidents caused by desensitization bypass of sensitive information, and facilitating practical application and promotion.

[0014] In a possible design, according to the data classification configuration set, determining the subject identity class identification results of the current historical data and all the current unhistory data includes:

[0015] Performing first encoding processing on each subject identity data in the data classification configuration set to obtain a first vector of each subject identity data, and adding all the first vectors to a first vector library;

[0016] Performing the first encoding process on a certain data among the currently recorded data and all the currently unrecorded data to obtain a third vector of the certain data;

[0017] Performing ANN vector retrieval on the first vector library based on the third vector;

[0018] If any first vector having a similarity with the third vector higher than a first preset threshold is retrieved in the first vector library, the subject identity class identification result of the certain data is determined to be that the certain data belongs to the subject identity class; otherwise, the subject identity class identification result of the certain data is determined to be that the certain data does not belong to the subject identity class.

[0019] In a possible design, determining the sensitivity category identification results of the current historical data and all the current non-historical data according to the sensitive data configuration set includes:

[0020] Performing second encoding processing on each sensitive data in the sensitive data configuration set to obtain a second vector of each sensitive data, and adding all the second vectors to a second vector library;

[0021] Perform the second encoding process on any data among the currently calendared data and all the currently uncalculated data to obtain a fourth vector of the any data;

[0022] Performing ANN vector retrieval on the second vector library based on the fourth vector;

[0023] If any second vector having a similarity with the fourth vector higher than a second preset threshold is retrieved in the second vector library, the sensitive class identification result of the any data is determined to be that the any data belongs to the sensitive class; otherwise, the sensitive class identification result of the any data is determined to be that the any data does not belong to the sensitive class.

[0024] In a possible design, determining the relationship value between the current historical data and each of the current non-historical data in all the current non-historical data according to the subject identity identification results and the sensitivity identification results of the current historical data and all the current non-historical data includes:

[0025] For each currently unrecorded data in all currently unrecorded data, the relationship value between the currently recorded data and the corresponding data is determined in the following manner according to the subject identity identification result and the sensitivity identification result of the currently recorded data and the corresponding data:

[0026] If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;

[0027] If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;

[0028] If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;

[0029] If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;

[0030] If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then determine that the relationship value between the current historical data and the corresponding data is one;

[0031] If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth;

[0032] If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth;

[0033] If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth;

[0034] If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;

[0035] If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one sixth;

[0036] If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero;

[0037] If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero;

[0038] If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;

[0039] If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth;

[0040] If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero;

[0041] If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero.

[0042] In one possible design, the method further includes:

[0043] When the total number of columns of the at least two columns of data to be desensitized reaches a third preset threshold and the subject identity class identification results of the at least two columns of data to be desensitized are that all data do not belong to the subject identity class, the at least two columns of data to be desensitized are respectively subjected to the data desensitization process to obtain at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized;

[0044] Alternatively, when the total number of columns of the at least two columns of data to be desensitized reaches a fourth preset threshold and the subject identity class identification results of the at least two columns of data to be desensitized are that all data do not belong to the subject identity class, any column of data to be desensitized in the at least two columns of data to be desensitized is directly used as the desensitized data corresponding to the any column of data to be desensitized, and the data desensitization processing is performed on each other column of data to be desensitized in the at least two columns of data to be desensitized, so as to obtain each column of desensitized data corresponding one by one to each column of other data to be desensitized.

[0045] In one possible design, outputting at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized includes:

[0046] For each column of desensitized data in at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized, the row order in the corresponding data is first disrupted, and then the corresponding data is output.

[0047] In a second aspect, a data dynamic desensitization device is provided, comprising a configuration information acquisition unit, a to-be-desensitized data receiving unit, a first desensitization processing unit, a second desensitization processing unit and a desensitized data output unit;

[0048] The configuration information acquisition unit is used to acquire a sensitive data configuration set and a data classification configuration set, wherein the sensitive data configuration set includes a plurality of sensitive class data, and the data classification configuration set includes a plurality of subject identity class data for determining a unique identity;

[0049] The to-be-desensitized data receiving unit is used to receive at least two columns of to-be-desensitized data;

[0050] The first desensitizing processing unit is respectively communicatively connected to the configuration information acquisition unit and the to-be-desensitized data receiving unit, and is used to sequentially traverse the at least two columns of the to-be-desensitized data that are not the last column of the to-be-desensitized data in the at least two columns of the to-be-desensitized data in order from front to back: determine the subject identity class identification results of the current calendar data and all the currently unscheduled data according to the data classification configuration set, and also determine the sensitive class identification results of the current calendar data and all the currently unscheduled data according to the sensitive data configuration set, and then determine the subject identity class identification results of the current calendar data and all the currently unscheduled data according to the current calendar data and all the currently unscheduled data. The identification result and the sensitive category identification result are used to determine the relationship value between the current in-history data and each currently non-history data in all the currently non-history data, and the total value of the current in-history data is obtained by cumulative calculation. Finally, if the total value of the current in-history data is greater than or equal to the preset value, the current in-history data is desensitized to obtain the desensitized data corresponding to the current in-history data, otherwise the current in-history data is directly used as the desensitized data corresponding to the current in-history data, wherein the current in-history data refers to the data to be desensitized that is currently being traversed, and the currently non-history data refers to the data to be desensitized that is not currently being traversed;

[0051] The second desensitization processing unit is communicatively connected to the to-be-desensitized data receiving unit, and is used to directly use the last column of the to-be-desensitized data in the at least two columns of the to-be-desensitized data as the desensitized processed data corresponding to the last column of the to-be-desensitized data;

[0052] The desensitized data output unit is communicatively connected to the first desensitization processing unit and the second desensitization processing unit, respectively, and is used to output at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized.

[0053] In a third aspect, the present invention provides a computer device comprising a memory, a processor and a transceiver which are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the data dynamic desensitization method as described in the first aspect or any possible design of the first aspect.

[0054] In a fourth aspect, the present invention provides a computer-readable storage product having instructions stored thereon. When the instructions are run on a computer, the data dynamic desensitization method as described in the first aspect or any possible design of the first aspect is executed.

[0055] In a fifth aspect, the present invention provides a computer program product, comprising a computer program or instructions, which, when executed by a computer, implement the data dynamic desensitization method as described in the first aspect or any possible design of the first aspect.

[0056] Beneficial effects of the above scheme:

[0057] (1) The present invention provides a new scheme for dynamic data desensitization based on the principle that data relationship determines data value, that is, after obtaining a sensitive data configuration set and a data classification configuration set and receiving at least two columns of data to be desensitized, the subject identity identification results and sensitive identification results of the current historical data and all currently un-historical data are first determined based on the aforementioned two sets, and then the relationship value between the current historical data and each currently un-historical data is determined based on the aforementioned two results, and the total value of the current historical data is accumulated and calculated. Finally, based on the comparison result of the total value and the preset value, it is decided whether to perform data desensitization processing on the current historical data. In this way, after the sensitive data is set, the data relationship can be used to adapt to the diverse combinations of data to be desensitized and complete dynamic desensitization, thereby avoiding the risk of sensitive information being desensitized and bypassed, causing information security accidents;

[0058] (2) It can also simplify settings, avoiding complex desensitized data settings in different application scenarios, and improving user experience;

[0059] (3) It can also achieve the purpose of appropriately transmitting information without leaking sensitive information. For example, the medical industry needs to know the different symptoms of the same disease in different patients. In this case, although the "disease type" is a sensitive field, if the patient's identity is desensitized and masked, the "symptoms" of the "disease type" can be transmitted without being rigid.

[0060] (4) By disrupting the row order of the returned data, it is also possible to prevent the leakage of sensitive information due to the piecing together of desensitized data, which facilitates practical application and promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0062] Figure 1 A flowchart of the data dynamic desensitization method provided in an embodiment of the present application.

[0063] Figure 2 A schematic diagram of the structure of the data dynamic desensitization device provided in an embodiment of the present application.

[0064] Figure 3 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in combination with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structures of the drawings is only some embodiments of the present invention. For ordinary technicians in this field, other embodiments can be obtained based on these embodiments without creative work. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0066] It should be understood that although the terms first and second, etc. may be used herein to describe various objects, these objects should not be limited by these terms. These terms are only used to distinguish one object from another object. For example, a first object can be referred to as a second object, and similarly, a second object can be referred to as a first object without departing from the scope of the exemplary embodiments of the present invention.

[0067] It should be understood that the term "and / or" that may appear in this document is merely a description of the association relationship between associated objects, indicating that there may be three relationships. For example, A and / or B can indicate three situations: A exists alone, B exists alone, or A and B exist at the same time. For another example, A, B and / or C can indicate the existence of any one of A, B and C or any combination of them. The term " / and" that may appear in this document describes another type of association object relationship, indicating that there may be two relationships. For example, A / and B can indicate two situations: A exists alone or A and B exist at the same time. In addition, the character " / " that may appear in this document generally indicates that the previous and next associated objects are in an "or" relationship.

[0068] Example

[0069] like Figure 1 As shown, the data dynamic desensitization method provided in the first aspect of this embodiment can be, but is not limited to, executed by a computer device with certain computing resources, such as a server or other electronic device that serves as a data desensitization agent. Figure 1 As shown, the data dynamic desensitization method may include but is not limited to the following steps S1 to S5.

[0070] S1. Obtain a sensitive data configuration set and a data classification configuration set, wherein the sensitive data configuration set includes but is not limited to multiple sensitive data, and the data classification configuration set includes but is not limited to multiple subject identity data for determining a unique identity.

[0071] In step S1, the sensitive data configuration set and the data classification configuration set are pre-set results, wherein the sensitive data configuration set can be conventionally pre-set based on existing technical means. This embodiment is based on the theory that the value of data is determined by the relationship between the data itself and other data (i.e., the principle that data relationship determines data value. For example, data such as a mobile phone number or ID card number alone has no value in itself, because this information can be constructed and can't be used for anything, so there is actually no need for confidentiality and desensitization. However, if it is combined with a "name", this is private data, which needs to be desensitized and encrypted. Therefore, whether desensitization is needed actually depends on which data needs to be output), that is, the value of each data is determined by the sum of the relationship values ​​between the data itself and other data that need to be output together: if Indicates the total number of other data that need to be output together with a certain data. Indicates less than or equal to A positive integer, Indicates that the certain data is related to The value of the relationship between the other data, then the value of the data . However, the relationship value of each pair of data is not equal. For example, the relationship value between "height" and "age" is not as good as the relationship value between "height" and "name". Therefore, some relationship values ​​can be ignored due to their small proportion, that is, the following simplification can be done: all data are divided into two categories, subject identity and feature. For example, subject identity data includes data such as "ID number", "telephone number" and / or "QQ number" that can determine the unique identity, while feature data includes sensitive data such as "positive hepatitis B symptoms" and / or "account balance" and belongs to specific targets and / or in specific scenarios. Specifically, the subject identity data in the data classification configuration set can be directly obtained after the sensitive data in the sensitive data configuration set is given the attribute of the subject identity class, or it can be obtained by referring to the sensitive data in the data classification configuration set and pre-setting it conventionally based on existing technical means.

[0072] S2. Receive at least two columns of data to be desensitized.

[0073] In step S2, the at least two columns of data to be desensitized may be, but are not limited to, data returned by a user request, wherein each column of data to be desensitized includes, but is not limited to, a data field and multiple lines of field content, for example, a data field of "student name" and multiple lines of name information. In addition, if the user requests the return of a column of data, no desensitization is required regardless of whether it belongs to the subject identity category and / or sensitive category, that is, the column of data is directly returned to the requesting user (of course, it can also be returned to the requesting user after the order of the rows in the column of data is disrupted).

[0074] S3. Traverse the columns of data to be desensitized in the at least two columns of data to be desensitized and not the last column of data to be desensitized in order from front to back of the at least two columns of data to be desensitized: determine the subject identity class recognition results of the current data in history and all the data not currently in history according to the data classification configuration set, and also determine the sensitive class recognition results of the current data in history and all the data not currently in history according to the sensitive data configuration set, and then determine the subject identity class recognition results and sensitive class recognition results of the current data in history and all the data not currently in history according to the subject identity class recognition results and sensitive class recognition results of the current data in history and all the data not currently in history. The relationship value between the data and each currently untraversed data in all the currently untraversed data is calculated and the total value of the currently in-traversal data is obtained by cumulative calculation. Finally, if the total value of the currently in-traversal data is greater than or equal to the preset value, the currently in-traversal data is desensitized to obtain the desensitized data corresponding to the currently in-traversal data. Otherwise, the currently in-traversal data is directly used as the desensitized data corresponding to the currently in-traversal data, wherein the currently in-traversal data refers to the data to be desensitized that is currently being traversed, and the currently untraversed data refers to the data to be desensitized that has not been traversed.

[0075] In step S3, the order from front to back of the at least two columns of data to be desensitized may be an initial order or an order obtained after random scrambling. For example, if the at least two columns of data to be desensitized contain column A data to be desensitized, column B data to be desensitized and column C data to be desensitized, then the order from front to back of the at least two columns of data to be desensitized may be: column A data to be desensitized, column B data to be desensitized and column C data to be desensitized; or may be: column C data to be desensitized, column B data to be desensitized and column A data to be desensitized; or may be: column B data to be desensitized, column C data to be desensitized and column A data to be desensitized; and so on. For example, if the at least two columns of data to be desensitized are in the following order from front to back: column A data to be desensitized, column B data to be desensitized and column C data to be desensitized, then it is necessary to traverse column A data to be desensitized and column B data to be desensitized in sequence (because the last column of data to be desensitized is column C data to be desensitized): when the current data in the history is column A data to be desensitized, all currently untraversed data will include column B data to be desensitized and column C data to be desensitized; when the current data in the history is column B data to be desensitized, all currently untraversed data will include column C data to be desensitized (because column A data to be desensitized has been traversed at this time).

[0076] In step S3, if the subject identity data in the data classification configuration set is rich enough, the subject identity recognition result of the current historical data or the current non-history data can be directly determined based on the specific situation of whether the current historical data or the current non-history data appears in the data classification configuration set: if it appears in the data classification configuration set, it is determined that the current historical data or the current non-history data belongs to the subject identity class, otherwise it is determined that the current historical data or the current non-history data does not belong to the subject identity class. However, if the subject identity data in the data classification configuration set is limited in number due to simple settings, in order to significantly improve the classification recognition efficiency while ensuring that the classification recognition result has a certain accuracy, it is preferred to determine the subject identity recognition results of the current historical data and all the current non-history data according to the data classification configuration set, including but not limited to the following steps S311 to S314.

[0077] S311. Perform first encoding processing on each subject identity data in the data classification configuration set to obtain a first vector of each subject identity data, and add all the first vectors to a first vector library.

[0078] In the step S311, the specific method of the first encoding process is the existing technology, for example, the existing word vector encoding technology is used to encode the subject identity data into a word vector used as the first vector.

[0079] S312. Perform the first encoding process on a certain data in the current calendar data and all the currently uncalculated data to obtain a third vector of the certain data.

[0080] In step S312, the third vector may also be exemplified as a word vector.

[0081] S313. Perform ANN vector search on the first vector library based on the third vector.

[0082] In step S313, the ANN (Approximate Nearest Neighbor) vector retrieval is an existing technology for processing similarity search in large-scale data sets, which is mainly used to quickly find data items similar to the query object in large data sets; this technology has applications in many fields, including vector databases, retrieval enhancement generation, large-scale information retrieval, recommendation systems, drug discovery, and image search. The core of ANN vector retrieval is to use efficient indexing and search algorithms to approximately find the nearest neighbors in the data set (note that it is not accurate to find the nearest neighbors). This approximate method allows a certain error while ensuring search efficiency, thereby significantly improving the search speed when processing large-scale data sets. In general, ANN vector retrieval technology can significantly improve the efficiency of similarity search in large-scale data sets while ensuring that the retrieval results have a certain degree of accuracy by using efficient indexing and search algorithms, as well as specific graph methods, such as HNSW (Hierarchical Navigable Small World Graph, which is a graph method for vector retrieval. It is based on the idea of ​​skip lists and achieves efficient approximate nearest neighbor search by constructing a navigable small world graph. It organizes data by using a navigable small world graph at each layer to form a hierarchical structure, so that the retrieval process can gradually approach the target vector space from top to bottom, thereby improving the search efficiency. In the process of graph composition, HNSW can ensure the connectivity of the graph by cutting the edges to ensure the smooth progress of the search process). Therefore, by performing ANN vector retrieval on the first vector library based on the third vector, the retrieval result can be obtained accurately and efficiently.

[0083] S314. If any first vector having a similarity with the third vector higher than a first preset threshold is retrieved in the first vector library, the subject identity class identification result of the certain data is determined to be that the certain data belongs to the subject identity class; otherwise, the subject identity class identification result of the certain data is determined to be that the certain data does not belong to the subject identity class.

[0084] In step S314, the similarity may be, but is not limited to, calculated based on cosine similarity (which measures the similarity between two vectors by measuring the cosine value of the angle between them: the cosine value of a 0 degree angle is 1, while the cosine value of any other angle is not greater than 1, and its minimum value is -1, so that the cosine value of the angle between two vectors determines whether the two vectors point roughly in the same direction; when the two vectors have the same direction, the cosine similarity value is 1; when the angle between the two vectors is 90°, the cosine similarity value is 0; and when the two vectors point in completely opposite directions, the cosine similarity value is -1; the aforementioned cosine similarity result is independent of the length of the vector and is only related to the direction of the vector; cosine similarity is usually used in positive space, so the value given is between -1 and 1). Specifically, when the similarity is expressed as a percentage, the first preset threshold value may be, but is not limited to, 60%. In addition, when the subject identity data in the data classification configuration set is directly obtained after the sensitive data in the sensitive data configuration set is assigned the subject identity class attribute, in order to simplify the settings and improve the user experience, preferably, obtaining the data classification configuration set includes but is not limited to the following steps S111 to S114: S111. After at least one sensitive data in the sensitive data configuration set is set to belong to the subject identity class, the at least one sensitive data is added to the data classification configuration set as the subject identity data for determining the unique identity, and each sensitive data in the at least one sensitive data is assigned a unique identity attribute. The first encoding process is performed on each of the candidate data to obtain the fifth vector of each sensitive class data, and all the fifth vectors are added to the third vector library; S112. The first encoding process is also performed on any candidate data to obtain the sixth vector of any candidate data; S113. The ANN vector search is performed on the third vector library based on the sixth vector; S114. If any fifth vector having a similarity with the sixth vector higher than the first preset threshold is retrieved in the third vector library, then any candidate data is also added to the data classification configuration set as subject identity class data for determining a unique identity. The specific technical details of the aforementioned steps S111 to S114 can be conventionally derived with reference to the aforementioned steps S311 to S314, and will not be repeated here; any of the aforementioned candidate data can be other sensitive class data in the sensitive data configuration set and has not yet been assigned a subject identity class, or it can be other data outside the sensitive data configuration set.

[0085] In step S3, if the sensitive data in the sensitive data configuration set is rich enough, the sensitive class identification result of the current historical data or the current non-history data can be directly determined based on the specific situation of whether the current historical data or the current non-history data appears in the sensitive data configuration set: if it appears in the sensitive data configuration set, it is determined that the current historical data or the current non-history data belongs to the sensitive class; otherwise, it is determined that the current historical data or the current non-history data does not belong to the sensitive class. However, if the sensitive data in the sensitive data configuration set is limited in number due to simple settings, in order to significantly improve the classification and identification efficiency while ensuring that the classification and identification results have a certain accuracy, it is preferred to determine the sensitive class identification results of the current historical data and all the current non-history data according to the sensitive data configuration set, including but not limited to the following steps S321 to S324.

[0086] S321. Perform a second encoding process on each sensitive data in the sensitive data configuration set to obtain a second vector of each sensitive data, and add all the second vectors to a second vector library.

[0087] In the step S321, the specific method of the second encoding processing is the existing technology, for example, the existing word vector encoding technology is used to encode the sensitive data into a word vector used as the second vector.

[0088] S322. Perform the second encoding process on any data in the current calendar data and all the currently uncalculated data to obtain a fourth vector of the any data.

[0089] In the step S322, the fourth vector can also be exemplified as a word vector.

[0090] S323. Perform ANN vector search on the second vector library based on the fourth vector.

[0091] S324. If any second vector having a similarity with the fourth vector higher than a second preset threshold is retrieved in the second vector library, the sensitive class identification result of the any data is determined to be that the any data belongs to the sensitive class; otherwise, the sensitive class identification result of the any data is determined to be that the any data does not belong to the sensitive class.

[0092] In the step S324, specifically, when the similarity is expressed as a percentage, the second preset threshold can be, but is not limited to, 60%. In addition, in order to simplify the settings and improve the user experience, preferably, a sensitive data configuration set is obtained, including but not limited to the following steps S101 to S104: S101. After adding at least one data as sensitive data to the sensitive data configuration set, the second encoding process is performed on each data in the at least one data to obtain the seventh vector of each data, and all the seventh vectors are added to the fourth vector library; S102. The second encoding process is also performed on any sensitive unknown data to obtain the eighth vector of any sensitive position data; S103. The ANN vector search is performed on the fourth vector library based on the eighth vector; S104. If any of the seventh vectors having a similarity with the eighth vector higher than the second preset threshold is retrieved in the fourth vector library, any sensitive unknown data is also added as sensitive data to the sensitive data configuration set. The specific technical details of the aforementioned steps S101 to S104 can be conventionally derived with reference to the aforementioned steps S321 to S324, and will not be repeated here.

[0093] In step S3, based on the subject identity identification results and sensitive identification results of the current historical data and all the current non-historical data, the relationship value between the current historical data and each current non-historical data in all the current non-historical data is determined. The specific value needs to be determined in combination with the mapping relationship between each pair of data with different subject identity identification results and sensitive identification results and the relationship value. However, the aforementioned mapping relationship can be specifically set in advance according to the actual desensitization needs: considering that the value of each data relationship is different, that is, the relationship value related to the subject identity data is higher, the relationship value related to the feature data is lower, and the information value of the data belonging to the subject identity and sensitive categories is the highest. Therefore, the relationship value of the data belonging to the subject identity and sensitive categories and the data belonging to the subject identity and sensitive categories, the relationship value of the data belonging to the subject identity and sensitive categories and the data belonging to the subject identity and not belonging to the sensitive category, the relationship value of the data belonging to the subject identity and sensitive categories and the data that does not belong to the subject identity and sensitive category, and the relationship value of the data belonging to the subject identity and sensitive category and the data that does not belong to the subject identity and not belonging to the sensitive category can be pre-set to one (that is, desensitization must be performed); and the relationship value of the data that does not belong to the subject identity and sensitive category and the data that does not belong to the subject identity and sensitive category, and the relationship value of the data that does not belong to the subject identity and sensitive category and the data that does not belong to the subject identity and sensitive category, The relationship value of data belonging to the identity category and not belonging to the sensitive category and the relationship value of data belonging to the non-subject identity category and not belonging to the sensitive category and data belonging to the non-subject identity category and not belonging to the sensitive category are both preset to zero; and the six degrees of relationship theory (first proposed by American social psychologist Stanley Milgram in 1967: in layman's terms, the relationship between you and anyone in the world will not exceed six degrees, that is, you can know any stranger through at most six people, that is, you can find any subject identity category based on the data relationship of no more than six subject identity categories) is applied, and the relationship value of data belonging to the subject identity category and not belonging to the sensitive category and data belonging to the non-subject identity category and not belonging to the sensitive category, the relationship value of data belonging to the subject identity category and not belonging to the sensitive category and data belonging to the non-subject identity category and belonging to the sensitive category, and the relationship value of data belonging to the subject identity category and not belonging to the sensitive category and data belonging to the subject identity category and not belonging to the sensitive category are all preset to one-sixth, as shown in Table 1 below:

[0094] Table 1. Relationship value table under various data pairs

[0095]

[0096] Based on the above Table 1, specifically, according to the subject identity class identification results and sensitive class identification results of the current historical data and all the current non-historical data, the relationship value between the current historical data and each current non-historical data in the current non-historical data is determined, including but not limited to: for each current non-historical data in the current non-historical data, according to the subject identity class identification results and sensitive class identification results of the current historical data and the corresponding data, the relationship value between the current historical data and the corresponding data is determined in the following manner: If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the current If the sensitive class identification result of the previous historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that The relationship value between the current in-history data and the corresponding data is one; if the subject identity class identification result of the current in-history data is that the current in-history data does not belong to the subject identity class, the sensitive class identification result of the current in-history data is that the current in-history data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current in-history data and the corresponding data is one; if the subject identity class identification result of the current in-history data is that the current in-history data does not belong to the subject identity class, the sensitive class identification result of the current in-history data is that the current in-history data If the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the corresponding data If the subject identity class identification result of the data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be six one; if the subject identity class identification result of the current in-history data is that the current in-history data belongs to the subject identity class, the sensitive class identification result of the current in-history data is that the current in-history data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current in-history data and the corresponding data is one; if the subject identity class identification result of the current in-history data is that the current in-history data belongs to the subject identity class, and the sensitive class identification result of the current in-history data is that the current in-history data does not belong to the sensitive class, the corresponding data If the subject identity class identification result of the data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be zero;If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, If the subject identity class identification result is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data belongs to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be zero; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be zero. ;

[0097] In the step S3, based on the above Table 1, since the relationship value between the data belonging to the subject identity class and not belonging to the sensitive class and the data not belonging to the subject identity class and not belonging to the sensitive class, the relationship value between the data not belonging to the subject identity class and belonging to the sensitive class and the data not belonging to the subject identity class and belonging to the sensitive class, the relationship value between the data not belonging to the subject identity class and belonging to the sensitive class and the data not belonging to the subject identity class and not belonging to the sensitive class, and the relationship value between the data not belonging to the subject identity class and not belonging to the sensitive class and the data not belonging to the subject identity class and not belonging to the sensitive class are all zero, the total value of the current historical data can be calculated by accumulating according to the following formula: :

[0098]

[0099] In the formula, Indicates the total number of cases where the currently recorded data and the currently unrecorded data are data belonging to the subject identity class and the sensitive class and data belonging to the subject identity class and the sensitive class, Indicates that the current historical data and the current unhistory data are data belonging to the subject identity class and the sensitive class and data belonging to the subject identity class and the sensitive class. The value of the relationship when Indicates the total number of cases where the currently recorded data and the currently unrecorded data are data belonging to the subject identity class and the sensitive class, and data belonging to the subject identity class and not belonging to the sensitive class, Indicates that the current historical data and the current unhistory data are data belonging to the subject identity class and the sensitive class and data belonging to the subject identity class and not belonging to the sensitive class. The value of the relationship when Indicates the total number of cases where the currently recorded data and the currently unrecorded data are data belonging to the subject identity class and the sensitive class and data not belonging to the subject identity class and the sensitive class, Indicates that the current historical data and the current unhistory data are data belonging to the subject identity class and the sensitive class and data not belonging to the subject identity class and the sensitive class. The relationship value in the situation Indicates the total number of cases where the currently recorded data and the currently unrecorded data are data belonging to the subject identity class and the sensitive class and data not belonging to the subject identity class and not belonging to the sensitive class, Indicates that the current historical data and the current unhistorical data are data belonging to the subject identity class and the sensitive class and data not belonging to the subject identity class and not belonging to the sensitive class. The relationship value in the situation Indicates the total number of cases where the currently recorded data and the currently unrecorded data are data belonging to the subject identity class and not belonging to the sensitive class, and data belonging to the subject identity class and not belonging to the sensitive class, Indicates that the current historical data and the current unhistory data are data belonging to the subject identity class and not belonging to the sensitive class and data belonging to the subject identity class and not belonging to the sensitive class. The relationship value in the situation Indicates the total number of cases where the currently recorded data and the currently unrecorded data are data belonging to the subject identity class and not belonging to the sensitive class, and data not belonging to the subject identity class and belonging to the sensitive class, Indicates that the current historical data and the current unhistory data are data belonging to the subject identity class and not belonging to the sensitive class and data not belonging to the subject identity class and belonging to the sensitive class. The relationship value in the situation Indicates the total number of cases where the currently recorded data and the currently unrecorded data are data belonging to the subject identity class and not belonging to the sensitive class, and data not belonging to the subject identity class and not belonging to the sensitive class, Indicates that the current historical data and the current unhistory data are data belonging to the subject identity class and not belonging to the sensitive class and data not belonging to the subject identity class and not belonging to the sensitive class. In addition, the preset value may be, but is not limited to, one, that is, if the total value of the current historical data is greater than or equal to 1, the data desensitization is performed, otherwise, the data desensitization is not performed.

[0100] In step S3, the specific method of data desensitization can be conventionally implemented using existing technical means. For example, if the numerical value of each row in the current historical data (such as a mobile phone number or an ID card number, etc.) exceeds 8 digits, the last 4 digits are retained and the first digits are represented by '*'.

[0101] S4. The last column of the data to be desensitized in the at least two columns of the data to be desensitized is directly used as the desensitized data corresponding to the last column of the data to be desensitized.

[0102] In step S4, since the previous data before the last column of data to be desensitized have been desensitized respectively, no matter whether the last column of data to be desensitized belongs to the subject identity category and / or sensitive category, it does not need to be desensitized again (that is, it does not affect information security), and can be directly used as desensitized data.

[0103] S5. Output at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized.

[0104] In step S5, if the at least two columns of data to be desensitized are data requested to be returned by the user, the at least two columns of desensitized data are output and returned to the user when returning. In order to prevent the data before desensitization from being restored by piecing together, preferably, at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized are output, including but not limited to the following steps: for each column of desensitized data in the at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized, the row order in the corresponding data is first disrupted, and then the corresponding data is output. In addition, in order to ensure the information security of multiple columns of non-subject identity data, preferably, the method also includes but is not limited to: when the total number of columns of the at least two columns of data to be desensitized reaches the third preset threshold and the subject identity identification result of the at least two columns of data to be desensitized is that all data do not belong to the subject identity class, the at least two columns of data to be desensitized are respectively subjected to the data desensitization processing to obtain at least two columns of desensitized data corresponding to the at least two columns of data to be desensitized; or, when the total number of columns of the at least two columns of data to be desensitized reaches the fourth preset threshold and the subject identity identification result of the at least two columns of data to be desensitized is that all data do not belong to the subject identity class, any column of the data to be desensitized in the at least two columns of data to be desensitized is directly used as the desensitized data corresponding to any column of the data to be desensitized, and the data desensitization processing is performed on each column of the other data to be desensitized in the at least two columns of data to be desensitized, and each column of the desensitized data corresponding to each column of the other data to be desensitized is obtained. The aforementioned third preset threshold and fourth preset threshold can be, but are not limited to, both 6.

[0105] Therefore, based on the data dynamic desensitization method described in the aforementioned steps S1 to S5, a new scheme for dynamic data desensitization based on the principle that data relationship determines data value is provided, that is, after obtaining the sensitive data configuration set and the data classification configuration set and receiving at least two columns of data to be desensitized, the subject identity identification results and sensitive identification results of the current historical data and all the current non-history data are first determined based on the aforementioned two sets, and then the relationship value between the current historical data and each current non-history data is determined based on the aforementioned two results, and the total value of the current historical data is accumulated and calculated. Finally, based on the comparison result of the total value and the preset value, it is decided whether to perform data desensitization processing on the current historical data. In this way, after the sensitive data and the like are set, the data relationship can be used to adapt to the diverse combination of data to be desensitized and complete dynamic desensitization, avoiding the risk of sensitive information being bypassed by desensitization and causing information security accidents. In addition, the settings can be simplified to achieve the purpose of avoiding complex desensitization data settings in different application scenarios, which is conducive to improving user experience and facilitating practical application and promotion.

[0106] like Figure 2As shown, the second aspect of this embodiment provides a virtual device for implementing the data dynamic desensitization method described in the first aspect, including a configuration information acquisition unit, a to-be-desensitized data receiving unit, a first desensitization processing unit, a second desensitization processing unit and a desensitized data output unit;

[0107] The configuration information acquisition unit is used to acquire a sensitive data configuration set and a data classification configuration set, wherein the sensitive data configuration set includes a plurality of sensitive class data, and the data classification configuration set includes a plurality of subject identity class data for determining a unique identity;

[0108] The to-be-desensitized data receiving unit is used to receive at least two columns of to-be-desensitized data;

[0109] The first desensitizing processing unit is respectively communicatively connected to the configuration information acquisition unit and the to-be-desensitized data receiving unit, and is used to sequentially traverse the at least two columns of the to-be-desensitized data that are not the last column of the to-be-desensitized data in the at least two columns of the to-be-desensitized data in order from front to back: determine the subject identity class identification results of the current calendar data and all the currently unscheduled data according to the data classification configuration set, and also determine the sensitive class identification results of the current calendar data and all the currently unscheduled data according to the sensitive data configuration set, and then determine the subject identity class identification results of the current calendar data and all the currently unscheduled data according to the current calendar data and all the currently unscheduled data. The identification result and the sensitive category identification result are used to determine the relationship value between the current in-history data and each currently non-history data in all the currently non-history data, and the total value of the current in-history data is obtained by cumulative calculation. Finally, if the total value of the current in-history data is greater than or equal to the preset value, the current in-history data is desensitized to obtain the desensitized data corresponding to the current in-history data, otherwise the current in-history data is directly used as the desensitized data corresponding to the current in-history data, wherein the current in-history data refers to the data to be desensitized that is currently being traversed, and the currently non-history data refers to the data to be desensitized that is not currently being traversed;

[0110] The second desensitization processing unit is communicatively connected to the to-be-desensitized data receiving unit, and is used to directly use the last column of the to-be-desensitized data in the at least two columns of the to-be-desensitized data as the desensitized processed data corresponding to the last column of the to-be-desensitized data;

[0111] The desensitized data output unit is communicatively connected to the first desensitization processing unit and the second desensitization processing unit, respectively, and is used to output at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized.

[0112] In one possible design, the first desensitizing processing unit is also used to perform the data desensitizing processing on the at least two columns of data to be desensitized respectively when the total number of columns of the at least two columns of data to be desensitized reaches a third preset threshold and the subject identity class identification results of the at least two columns of data to be desensitized are that all data do not belong to the subject identity class, so as to obtain at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized.

[0113] In one possible design, the first desensitizing processing unit is also used to directly use any column of the at least two columns of data to be desensitized as the desensitized data corresponding to any column of the data to be desensitized, and perform the data desensitization processing on each column of other data to be desensitized in the at least two columns of data to be desensitized, when the total number of columns of the at least two columns of data to be desensitized reaches a fourth preset threshold and the subject identity class identification result of the at least two columns of data to be desensitized is that all data do not belong to the subject identity class, to obtain each column of desensitized data corresponding one-to-one to each column of other data to be desensitized.

[0114] The working process, working details and technical effects of the aforementioned device provided in the second aspect of this embodiment can be referred to the data dynamic desensitization method described in the first aspect, and will not be repeated here.

[0115] like Figure 3 As shown, the third aspect of this embodiment provides a computer device for executing the data dynamic desensitization method as described in the first aspect, including a memory, a processor and a transceiver that are sequentially connected in communication, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the data dynamic desensitization method as described in the first aspect. Specifically, the memory may include, but is not limited to, a random access memory (Random-Access Memory, RAM), a read-only memory (Read-Only Memory, ROM), a flash memory (Flash Memory), a first-in-first-out memory (First Input First Output, FIFO) and / or a first-in-last-out memory (First Input Last Output, FILO), etc.; the processor may include, but is not limited to, a microprocessor of the STM32F105 series. In addition, the computer device may also include, but is not limited to, a power module, a display screen and other necessary components.

[0116] The working process, working details and technical effects of the aforementioned computer device provided in the third aspect of this embodiment can be found in the data dynamic desensitization method described in the first aspect, and will not be repeated here.

[0117] The fourth aspect of this embodiment provides a computer-readable storage product that stores instructions containing the data dynamic desensitization method as described in the first aspect, that is, the computer-readable storage product stores instructions, and when the instructions are run on a computer, the data dynamic desensitization method as described in the first aspect is executed. Wherein, the computer-readable storage product refers to a carrier for storing data, which may include but is not limited to computer-readable storage media such as floppy disks, optical disks, hard disks, flash memories, USB flash drives, and / or memory sticks (MemoryStick), and the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.

[0118] The working process, working details and technical effects of the aforementioned computer-readable storage medium provided in the fourth aspect of this embodiment can be referred to the data dynamic desensitization method described in the first aspect, and will not be repeated here.

[0119] The fifth aspect of this embodiment provides a computer program product, including a computer program or an instruction, which, when executed by a computer, implements the data dynamic desensitization method as described in the first aspect. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0120] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data dynamic desensitization method, characterized in that: include: Obtain a sensitive data configuration set and a data classification configuration set, wherein the sensitive data configuration set includes a plurality of sensitive class data, and the data classification configuration set includes a plurality of subject identity class data for determining a unique identity; Receive at least two columns of data to be desensitized; The method further comprises the following steps: traversing each column of the at least two columns of the data to be desensitized and not being the last column of the data to be desensitized in order from the front to the back of the at least two columns of the data to be desensitized: determining the subject identity class identification results of the current data in history and all the data not currently in history according to the data classification configuration set, and also determining the sensitive class identification results of the current data in history and all the data not currently in history according to the sensitive data configuration set, and then determining the subject identity class identification results and sensitive class identification results of the current data in history and all the data not currently in history according to the subject identity class identification results and the sensitive class identification results of the current data in history and all the data not currently in history According to the relationship value with each currently untraversed data in all the currently untraversed data, and cumulatively calculating to obtain the total value of the currently in-traversal data, finally, if the total value of the currently in-traversal data is greater than or equal to the preset value, performing data desensitization processing on the currently in-traversal data to obtain the desensitized data corresponding to the currently in-traversal data, otherwise directly using the currently in-traversal data as the desensitized data corresponding to the currently in-traversal data, wherein the currently in-traversal data refers to the data to be desensitized that is currently being traversed, and the currently untraversed data refers to the data to be desensitized that is not currently being traversed; According to the subject identity class identification results and sensitive class identification results of the current historical data and all the current non-historical data, determine the relationship value between the current historical data and each current non-historical data in the current non-historical data, including: for each current non-historical data in the current non-historical data, according to the subject identity class identification results and sensitive class identification results of the current historical data and the corresponding data, determine the relationship value between the current historical data and the corresponding data in the following manner: if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitive class identification result of the current historical data If the current in-history data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current in-history data and the corresponding data is one; if the subject identity class identification result of the current in-history data is that the current in-history data belongs to the subject identity class, and the sensitivity class identification result of the current in-history data is that the current in-history data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the current in-history data and the corresponding data have a relationship value of one. The relationship value of the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value of the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data does not belong to sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the corresponding data If the subject identity class identification result of the data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be six one; if the subject identity class identification result of the current in-history data is that the current in-history data belongs to the subject identity class, the sensitive class identification result of the current in-history data is that the current in-history data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current in-history data and the corresponding data is one; if the subject identity class identification result of the current in-history data is that the current in-history data belongs to the subject identity class, and the sensitive class identification result of the current in-history data is that the current in-history data does not belong to the sensitive class, the corresponding data If the subject identity class identification result of the data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be zero;If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, If the subject identity class identification result is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data belongs to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero; The last column of the data to be desensitized in the at least two columns of the data to be desensitized is directly used as the desensitized data corresponding to the last column of the data to be desensitized; Output at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized.

2. The data dynamic desensitization method according to claim 1, characterized in that: According to the data classification configuration set, the subject identity recognition results of the current historical data and all the current non-historical data are determined, including: Performing first encoding processing on each subject identity data in the data classification configuration set to obtain a first vector of each subject identity data, and adding all the first vectors to a first vector library; Performing the first encoding process on a certain data among the currently recorded data and all the currently unrecorded data to obtain a third vector of the certain data; Performing ANN vector retrieval on the first vector library based on the third vector; If any first vector having a similarity with the third vector higher than a first preset threshold is retrieved in the first vector library, the subject identity class identification result of the certain data is determined to be that the certain data belongs to the subject identity class; otherwise, the subject identity class identification result of the certain data is determined to be that the certain data does not belong to the subject identity class.

3. The data dynamic desensitization method according to claim 1, characterized in that: Determining, according to the sensitive data configuration set, the sensitive category identification results of the currently recorded data and all the currently unrecorded data, including: Performing second encoding processing on each sensitive data in the sensitive data configuration set to obtain a second vector of each sensitive data, and adding all the second vectors to a second vector library; Perform the second encoding process on any data among the currently calendared data and all the currently uncalculated data to obtain a fourth vector of the any data; Performing ANN vector retrieval on the second vector library based on the fourth vector; If any second vector having a similarity with the fourth vector higher than a second preset threshold is retrieved in the second vector library, the sensitive class identification result of the any data is determined to be that the any data belongs to the sensitive class; otherwise, the sensitive class identification result of the any data is determined to be that the any data does not belong to the sensitive class.

4. The data dynamic desensitization method according to claim 1, characterized in that: The method further comprises: When the total number of columns of the at least two columns of data to be desensitized reaches a third preset threshold and the subject identity class identification results of the at least two columns of data to be desensitized are that all data do not belong to the subject identity class, the at least two columns of data to be desensitized are respectively subjected to the data desensitization process to obtain at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized; Alternatively, when the total number of columns of the at least two columns of data to be desensitized reaches a fourth preset threshold and the subject identity class identification results of the at least two columns of data to be desensitized are that all data do not belong to the subject identity class, any column of data to be desensitized in the at least two columns of data to be desensitized is directly used as the desensitized data corresponding to the any column of data to be desensitized, and the data desensitization processing is performed on each other column of data to be desensitized in the at least two columns of data to be desensitized, so as to obtain each column of desensitized data corresponding one by one to each column of other data to be desensitized.

5. The data dynamic desensitization method according to claim 1, characterized in that: Outputting at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized includes: For each column of desensitized data in at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized, the row order in the corresponding data is first disrupted, and then the corresponding data is output.

6. A data dynamic desensitization device, characterized in that: It includes a configuration information acquisition unit, a to-be-desensitized data receiving unit, a first desensitization processing unit, a second desensitization processing unit and a desensitized data output unit; The configuration information acquisition unit is used to acquire a sensitive data configuration set and a data classification configuration set, wherein the sensitive data configuration set includes a plurality of sensitive class data, and the data classification configuration set includes a plurality of subject identity class data for determining a unique identity; The to-be-desensitized data receiving unit is used to receive at least two columns of to-be-desensitized data; The first desensitizing processing unit is respectively communicatively connected to the configuration information acquisition unit and the to-be-desensitized data receiving unit, and is used to sequentially traverse the at least two columns of the to-be-desensitized data that are not the last column of the to-be-desensitized data in the at least two columns of the to-be-desensitized data in order from front to back: determine the subject identity class identification results of the current calendar data and all the currently unscheduled data according to the data classification configuration set, and also determine the sensitive class identification results of the current calendar data and all the currently unscheduled data according to the sensitive data configuration set, and then determine the subject identity class identification results of the current calendar data and all the currently unscheduled data according to the current calendar data and all the currently unscheduled data. The identification result and the sensitive category identification result are used to determine the relationship value between the current in-history data and each currently non-history data in all the currently non-history data, and the total value of the current in-history data is obtained by cumulative calculation. Finally, if the total value of the current in-history data is greater than or equal to the preset value, the current in-history data is desensitized to obtain the desensitized data corresponding to the current in-history data, otherwise the current in-history data is directly used as the desensitized data corresponding to the current in-history data, wherein the current in-history data refers to the data to be desensitized that is currently being traversed, and the currently non-history data refers to the data to be desensitized that is not currently being traversed; According to the subject identity class identification results and sensitive class identification results of the current historical data and all the current non-historical data, determine the relationship value between the current historical data and each current non-historical data in the current non-historical data, including: for each current non-historical data in the current non-historical data, according to the subject identity class identification results and sensitive class identification results of the current historical data and the corresponding data, determine the relationship value between the current historical data and the corresponding data in the following manner: if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitive class identification result of the current historical data If the current in-history data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current in-history data and the corresponding data is one; if the subject identity class identification result of the current in-history data is that the current in-history data belongs to the subject identity class, and the sensitivity class identification result of the current in-history data is that the current in-history data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the current in-history data and the corresponding data have a relationship value of one. The relationship value of the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value of the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data does not belong to sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one;If the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, the corresponding data If the subject identity class identification result of the data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data belongs to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be six one; if the subject identity class identification result of the current in-history data is that the current in-history data belongs to the subject identity class, the sensitive class identification result of the current in-history data is that the current in-history data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current in-history data and the corresponding data is one; if the subject identity class identification result of the current in-history data is that the current in-history data belongs to the subject identity class, and the sensitive class identification result of the current in-history data is that the current in-history data does not belong to the sensitive class, the corresponding data If the subject identity class identification result of the data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitivity class identification result of the current historical data is that the current historical data belongs to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitivity class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then the relationship value between the current historical data and the corresponding data is determined to be zero;If the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data belongs to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data belongs to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one; if the subject identity class identification result of the current historical data is that the current historical data belongs to the subject identity class, the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, If the subject identity class identification result is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is one-sixth; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data belongs to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero; if the subject identity class identification result of the current historical data is that the current historical data does not belong to the subject identity class, and the sensitive class identification result of the current historical data is that the current historical data does not belong to the sensitive class, and the subject identity class identification result of the corresponding data is that the corresponding data does not belong to the subject identity class, and the sensitive class identification result of the corresponding data is that the corresponding data does not belong to the sensitive class, then it is determined that the relationship value between the current historical data and the corresponding data is zero; The second desensitization processing unit is communicatively connected to the to-be-desensitized data receiving unit, and is used to directly use the last column of the to-be-desensitized data in the at least two columns of the to-be-desensitized data as the desensitized processed data corresponding to the last column of the to-be-desensitized data; The desensitized data output unit is communicatively connected to the first desensitization processing unit and the second desensitization processing unit, respectively, and is used to output at least two columns of desensitized data corresponding one-to-one to the at least two columns of data to be desensitized.

7. A computer device, characterized in that: It includes a memory, a processor and a transceiver which are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program to execute the data dynamic desensitization method as described in any one of claims 1 to 5.

8. A computer readable storage product, characterized in that The computer-readable storage product stores instructions, and when the instructions are run on a computer, the data dynamic desensitization method as described in any one of claims 1 to 5 is executed.

9. A computer program product comprising a computer program or instructions, characterized in that When the computer program or the instruction is executed by a computer, the data dynamic desensitization method as described in any one of claims 1 to 5 is implemented.

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