Sensitive information processing method, device and medium

Abstract

This application relates to the field of blockchain technology, specifically to a method, apparatus, and medium for processing sensitive information. The method includes: obtaining a first suspected sensitive field from test data; if the first suspected sensitive field does not belong to a preset sensitive information table and does not belong to a preset sensitive information exception table, then obtaining a first sensitivity probability of the first suspected sensitive field; if the first sensitivity probability is greater than a first threshold, then obtaining a first desensitization rule for the first suspected sensitive field; and adding the first suspected sensitive field and the first desensitization rule to the preset sensitive information table. Using this application can prevent the leakage of sensitive information corresponding to the desensitization rules, thereby improving data security.

Description

Technical Field

[0001] The present application relates to the field of blockchain technology, and mainly to a sensitive information processing method, device and medium. Background Art

[0002] In daily project development and testing, a large amount of test data is needed. In order to eliminate the differences in data magnitude and data distribution between test data and production data in actual production, production data is used as test data for testing. And in order to avoid the leakage of sensitive information, before the production database is imported into the test database, the sensitive information in the production data (for example, name, ID number, telephone number, email address, etc.) is desensitized. In the prior art, desensitization is performed according to manually configured desensitization rules. However, manual configuration has the problems of untimely and incomplete configuration, which can easily lead to the leakage of sensitive information. Summary of the invention

[0003] The embodiments of the present application provide a sensitive information processing method, device and medium, which can avoid leakage of sensitive information and improve data security.

[0004] In a first aspect, an embodiment of the present application provides a sensitive information processing method, wherein:

[0005] Obtain the first suspected sensitive field in the test data;

[0006] If the first suspected sensitive field does not belong to the preset sensitive information table, and the first suspected sensitive field does not belong to the preset sensitive information exception table, obtaining a first sensitive probability of the first suspected sensitive field;

[0007] If the first sensitivity probability is greater than a first threshold, obtaining a first desensitization rule for the first suspected sensitive field;

[0008] Add the first suspected sensitive field and the first desensitization rule to the preset sensitive information table.

[0009] In a second aspect, an embodiment of the present application provides a sensitive information processing device, wherein:

[0010] A storage unit, used to store a preset sensitive information table and a preset sensitive information exception table;

[0011] a processing unit, configured to obtain a first suspected sensitive field in the test data; if the first suspected sensitive field does not belong to the preset sensitive information table, and the first suspected sensitive field does not belong to the preset sensitive information exception table, obtain a first sensitive probability of the first suspected sensitive field; if the first sensitive probability is greater than a first threshold, obtain a first desensitization rule for the first suspected sensitive field;

[0012] The storage unit is further used to add the first suspected sensitive field and the first desensitization rule to the preset sensitive information table.

[0013] In a third aspect, an embodiment of the present application provides another sensitive information processing device, comprising a processor, a memory, a communication interface, and one or at least one program, wherein the one or at least one program is stored in the memory and configured to be executed by the processor, and the program includes instructions for some or all of the steps described in the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program enables a computer to execute to implement some or all of the steps described in the first aspect.

[0015] Implementing the embodiments of the present application will have the following beneficial effects:

[0016] After adopting the above-mentioned sensitive information processing method, device and medium, if the first suspected sensitive field in the test data does not belong to the preset sensitive information table and does not belong to the preset sensitive information exception table, the sensitivity probability of the first suspected sensitive field is obtained. And when the first sensitive probability is greater than the first threshold, the first desensitization rule of the first suspected sensitive field is obtained. Then, the first suspected sensitive field and the first desensitization rule are added to the preset sensitive information table, which can improve the comprehensiveness of the preset sensitive information table, avoid the leakage of sensitive information corresponding to the desensitization rule, and improve the security of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application 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 application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] in:

[0019] Figure 1 A flowchart of a sensitive information processing method provided in an embodiment of the present application;

[0020] Figure 2 A flowchart of another sensitive information processing method provided in an embodiment of the present application;

[0021] Figure 3 A schematic diagram of a setting page of a management terminal in a test project provided in an embodiment of the present application;

[0022] Figure 4A schematic diagram of a display page of a management terminal provided in an embodiment of the present application;

[0023] Figure 5 A schematic diagram of the logical structure of a sensitive information processing device provided in an embodiment of the present application;

[0024] Figure 6 A schematic diagram of the physical structure of a sensitive information processing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. According to the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0027] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0028] The network architecture used in the embodiments of the present application includes a server and an electronic device. Among them, the electronic device can be a personal computer (PC), a laptop or a smart phone, and can also be an all-in-one machine, a handheld computer, a tablet computer (pad), a smart TV playback terminal, a vehicle-mounted terminal or a portable device, etc. PC-side user terminals, such as all-in-one machines, etc., their operating systems can include but are not limited to Linux systems, Unix systems, Windows series systems (such as Windowsxp, Windows 7, etc.), Mac OS X systems (operating systems for Apple computers), etc. operating systems. Mobile-side user terminals, such as smart phones, etc., their operating systems can include but are not limited to Android systems, IOS (operating systems for Apple phones), Window systems, etc. operating systems.

[0029] The server is similar to a general computer architecture, including a processor, hard disk, memory, system bus, etc., and is used to provide services to electronic devices. The server can run on a single device or on a server cluster consisting of multiple servers, which is not limited here.

[0030] The electronic device in the embodiment of the present application can install and run an application, and the server can be a server corresponding to the application installed in the electronic device, providing application services for the application. Among them, the application can be a project development management platform, or a sensitive information processing platform, etc., or a separately integrated application, or a small program embedded in other applications, obtaining a system on a web page, etc., which are not limited here. The embodiment of the present application does not limit the number of electronic devices and servers, and the server can provide services for multiple electronic devices at the same time. The server can be implemented with an independent server or a server cluster consisting of multiple servers.

[0031] In an embodiment of the present application, a preset sensitive information table and a preset sensitive information exception table may be pre-stored. Among them, the preset sensitive information table, for example, sensitive_info_shield, includes sensitive fields and desensitization rules corresponding to the sensitive fields. The preset sensitive information exception table, for example, test_sensitive_info_exclude, includes non-sensitive fields in suspected sensitive fields. It can be seen that the preset sensitive information table is used to record information that has been identified as sensitive fields in the test database, and the preset sensitive information exception table is used to record information of suspected sensitive fields that have been identified as non-sensitive fields in the test database. In other words, if the preset sensitive information table includes a suspected sensitive field, it can be determined that the suspected sensitive field is a sensitive field. If the preset sensitive information exception table includes a suspected sensitive field, the suspected sensitive field can be excluded as a sensitive field, and the suspected sensitive field is a non-sensitive field. If both the preset sensitive information table and the preset sensitive information exception table do not include the suspected sensitive field, it is neither possible to determine that the suspected sensitive field is a sensitive field nor to exclude that the suspected sensitive field is a sensitive field. It should be noted that the desensitization rules of sensitive fields can be stored separately.

[0032] The preset sensitive information table and the preset sensitive information exception table may also include attribute information such as field column name, field content, table identifier, data identifier, table name, etc. Among them, the field column name is the attribute class name of the field, such as name, ID number, telephone number, etc. The field content is the value corresponding to the field column name, that is, the field column name and field content belong to the attribute-value relationship. The table identifier is used to represent the table, and the table name is the table name of the test data corresponding to the field. The data identifier is the user identifier of the test data.

[0033] In the embodiment of the present application, the above-mentioned preset sensitive information table, preset sensitive information exception table and desensitization rules can be stored in a memory, or stored in a specified location in the network, such as a Uniform Resource Locator (URL), etc. For example, the storage path of the preset sensitive information table is: http: / / XXX.com.cn / sensitive.

[0034] The above-mentioned preset sensitive information table, preset sensitive information exception table and desensitization rules can also be stored in a block created on the blockchain network. Blockchain is a new application model of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database. It is a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. The blockchain can include the underlying blockchain platform, the platform product service layer and the application service layer. It can be seen that by storing data in a distributed manner through the blockchain, while ensuring data security, information sharing between different platforms can be achieved.

[0035] A sensitive information processing method proposed in an embodiment of the present application can be executed by a sensitive information processing device, wherein the device can be implemented by software and / or hardware, can generally be integrated in a server, and can improve the efficiency of demand scheduling.

[0036] Please refer to Figure 1 , Figure 1 This is a flowchart of a sensitive information processing method provided by this application. Taking the application of this aspect on a server as an example, it includes the following steps:

[0037] S101: Obtain a first suspected sensitive field in test data.

[0038] In the embodiment of the present application, the test data may be any data in the test database, or may be newly imported data or newly modified data, etc., which is not limited here. The first suspected sensitive field is a suspected sensitive field in the test data, which may include a field column name, field content, table identifier, data identifier, table name, etc., which is not limited here.

[0039] This application does not limit the method for obtaining the first suspected sensitive field. The test data can be compared with the production data, and the modified fields can be selected for keyword detection. Keywords can be sensitive fields corresponding to names, including customer name, policyholder, insured, user name, Chinese name or English name, etc., sensitive fields corresponding to contact information include telephone, mobile phone, address, email, fax machine, etc., and sensitive fields corresponding to identification information include passport, ID number, driver's license, account number, place of origin, company, stock code, corporate homepage, etc. It should be noted that the above-mentioned sensitive fields can be Chinese characters, English characters, or other languages, etc., which are not limited here.

[0040] In a possible example, step S101 includes: obtaining multiple sensitive categories according to a preset sensitive information table; constructing multiple keywords according to the multiple sensitive categories; generating a keyword detection script according to the multiple keywords; and obtaining a first suspected sensitive field in the test data according to the keyword detection script.

[0041] Among them, sensitive categories include personal information categories such as name, contact information and identification information. As mentioned above, the preset sensitive information table includes sensitive fields, that is, the sensitive categories involved in the sensitive fields are obtained for the queried sensitive fields, and then keywords are constructed according to the sensitive categories, which can improve the comprehensiveness of the keywords.

[0042] The keyword detection script is a method for detecting sensitive fields based on keywords. This application does not limit the method for generating keyword detection scripts, and it can be obtained through the multiple keywords obtained above and the regular expressions corresponding to the keywords. For example: a mobile phone number is 11 digits, and the first digit is 1; a Chinese ID card number is 18 digits, or 17 digits and the last digit is a capital letter X; an email address includes special characters "@" and ".com", etc. Therefore, a regular expression can be constructed according to the above rules. For example, the regular expression for a mobile phone number can be: 1(3\d|47|5(?!4\d)|7(0|1|[6-8])|8\d)\d{8,8}.

[0043] For example, the keyword detection script includes the query code shown below, which is based on the Structured Query Language (SQL). Among them, sid is the table identifier, owner is the data identifier, table_name is the table name, comment_name is the field column name, and comments is the field content. The table identifier is used to represent the table, and the table name is the table name of the test data corresponding to the field.

[0044] Query code:

[0045] select sid,owner,table_name,column_name,comments from all_col_comments

[0046] where(column_name like'%APP%NAME%'or column_name like'%CLIENT%NAME%'or column_name like'CHINESE%NAME%'or column_name like'%ENGLISH%NAME%'

[0047] or column_name like'%ADDR%'or column_name like'%TEL%'or column_name like'%EML%'

[0048] or comments like'%Customer name%' or comments like'%Address%' or commentslike'%Telephone%' or comments like'%ID number%' or comments like'%Account number%' or comments like'%Company%'

[0049] and(owner not in('SYS','APPMGR','APPQOSSYS','DBMGR','XDB','ORDSYS'))

[0050] and(owner||table_name in(select owner||object_name from All_objects awhere a.last_ddl_time>to_date('2019-10-26','yyyy-mm-dd')))

[0051] According to the above query code, you can search for tables with dates after 2019-10-26 from the all_col_comments table, and the field column names include "APP NAME", "CLIENT NAME", "CHINESE NAME", "ENGLISHNAME", "ADDR", "TEL", "EML" fields, or the field contents include "Customer Name", "Telephone", "Address", "ID Number", "Account Number", "Company" fields, and the data identifier is not one of 'SYS', 'APPMGR', 'APPQOSSYS', 'DBMGR', 'XDB', 'ORDSYS'.

[0052] It can be understood that in the above example, multiple sensitive categories are obtained according to the preset sensitive information table, that is, the sensitive categories involved in the sensitive fields are obtained for the queried sensitive fields, and then keywords are constructed according to the sensitive categories, which can improve the comprehensiveness of the keywords. Then, a keyword detection script is generated according to the multiple keywords, and the first suspected sensitive field in the test data is obtained according to the keyword detection script, which can improve the accuracy of obtaining the suspected sensitive field.

[0053] The present application does not limit the time for obtaining the first suspected sensitive field, which can be after the test database is updated, or it can be a scheduled query, such as 14 hours, 24 hours, etc.

[0054] In a possible example, before step S101, the method further includes: obtaining a sensitivity ratio of a test database corresponding to the test data; determining a first timing duration according to the sensitivity ratio; and executing step S101 when the time of the first timer reaches the first timing duration.

[0055] The test database can be a collection of all test data or a collection of test group data corresponding to the test data, which is not limited here. The sensitivity ratio refers to the ratio of sensitive fields to the test database, which can be the ratio between the number of sensitive fields and the total amount of data in the test database, which is not limited here.

[0056] The first timer is a timing device in the server, used for timing, and when the time reaches the first timing duration, step S101 is executed. The timing is restarted when step S101 is executed, or after all the test data in the test database are detected, which is not limited here.

[0057] The present application may determine the first timing duration according to a mapping relationship between a preset sensitivity ratio and a timing duration, as shown in the following table. When the sensitivity ratio is 0.5, the timing duration is 1 week.

[0058] Sensitive ratio Timing duration (0，0.3] 12 hours (0.3，0.7] 1 week (0.7，1] January

[0059] It can be understood that the greater the sensitivity ratio, the smaller the probability of missing sensitive fields in the test database. In this example, the first timing duration is determined according to the sensitivity ratio of the test database, and when the time of the first timer reaches the first timing duration, step S101 is executed, which can avoid the electronic device from frequently detecting suspected sensitive fields and reduce power consumption.

[0060] Furthermore, in a possible example, a first update frequency of the preset sensitive information table and a second update frequency of the preset sensitive information exception table are obtained; a second timing duration is obtained according to the sensitive ratio; a third timing duration is obtained according to the first update frequency and the second update frequency; and the first timing duration is obtained according to the second timing duration and the third timing duration.

[0061] The first update frequency is used to describe the number of preset sensitive information tables updated within a unit time (e.g., one day, one week, one month, etc.), and the second update frequency is used to describe the number of preset sensitive information exception tables updated within a unit time. It can be seen that the first update frequency and the second update frequency are used to describe the update frequency of the corresponding tables, respectively. The greater the update frequency, the greater the probability of missing sensitive fields in the test database.

[0062] It can be understood that obtaining the second timing duration according to the sensitivity ratio, obtaining the third timing duration according to the first update frequency and the second update frequency, and then obtaining the timing duration according to the second timing duration and the third timing duration can improve the effectiveness of timing monitoring.

[0063] S102: If the first suspected sensitive field does not belong to the preset sensitive information table, and the first suspected sensitive field does not belong to the preset sensitive information exception table, obtaining a first sensitive probability of the first suspected sensitive field.

[0064] In the embodiment of the present application, the sensitivity probability is used to describe the probability value that the first suspected sensitive field is a sensitive field. As mentioned above, if the first suspected sensitive field does not belong to the preset sensitive information table and does not belong to the preset sensitive information exception table, it is neither possible to determine that the suspected sensitive field is a sensitive field nor to exclude that the suspected sensitive field is a sensitive field. Therefore, obtaining the sensitivity probability of the first suspected sensitive field can improve the accuracy of identifying sensitive fields.

[0065] The present application does not limit the method for obtaining sensitive probability. In a possible example, step S102 includes: obtaining, from a production database, production data corresponding to the test data according to the data identifier of the test data; obtaining, from the production data, a first field according to the target field column name of the first suspected sensitive field; obtaining a similarity value between the first field and the first suspected sensitive field; and obtaining a first sensitive probability of the first suspected sensitive field according to the similarity value.

[0066] The data identifier of the test data is unique and non-sensitive, and is used to obtain the generated data corresponding to the test data in the production database, that is, the original data. The target field column name can be a keyword determined as a suspected sensitive field in the process of obtaining the first suspected sensitive field. The similarity value is used for the similarity between the first field and the first suspected sensitive field.

[0067] It can be understood that, according to the data identifier of the test data, the production data corresponding to the test data is first obtained from the production database, and then the first field is obtained from the production data according to the target field column name of the first suspected sensitive field. Then, the similarity value between the first field and the first suspected sensitive field is obtained, and the first sensitive probability of the first suspected sensitive field is obtained according to the similarity value. In other words, the sensitivity probability is obtained according to the difference between the field after desensitization and the field before desensitization, which can improve the accuracy of obtaining the sensitivity probability.

[0068] Further, in a possible example, after obtaining the similarity value between the first field and the first suspected sensitive field, the method also includes: obtaining operation information of the test data; obtaining a second sensitive probability of the first suspected sensitive field based on the operation information; and obtaining a first sensitive probability of the first suspected sensitive field based on the second sensitive probability and the similarity value.

[0069] The operation information may include the name of the operation table, the name of the operation field, the content of the operation field, the operation type (for example, data addition, deletion, modification and query), etc. This application does not limit the method for obtaining the operation information, and the interactive operation instructions of the third-party application can be obtained, and then the interactive operation instructions can be identified to obtain the operation information.

[0070] It can be understood that the operation information is a kind of dynamic interactive information. Based on the similarity values ​​between the fields after desensitization and the fields before desensitization, the accuracy of identifying sensitive information can be improved by verifying the dynamic interactive information.

[0071] S103: If the first sensitive probability is greater than a first threshold, obtaining a first desensitization rule for the first suspected sensitive field.

[0072] In the embodiment of the present application, the first threshold is not limited and can be 50%. In a possible example, the method further includes: obtaining the first threshold according to the sensitive ratio. It can be understood that the sensitive ratio is used to describe the proportion of sensitive fields in the test database, and dynamically setting the first threshold according to the sensitive ratio can improve the accuracy of identifying sensitive information.

[0073] In the embodiment of the present application, the first desensitization rule is a rule for converting the first field into the first suspected sensitive field. The first desensitization rule can be determined according to the field column name of the sensitive field, or can be obtained by comparing the source data of the production data and then reversely calculating, which is not limited here.

[0074] In a possible example, step S103 includes: obtaining a second desensitization rule corresponding to the production data from the preset sensitive information table according to the data identifier; desensitizing the first field according to the second desensitization rule to obtain a second field; and obtaining a first desensitization rule for the first suspected sensitive field according to the second field and the first suspected sensitive field.

[0075] The second desensitization rule may be a preset desensitization rule corresponding to the production data, or a desensitization rule of a data table corresponding to the production data. The second field is a field obtained by desensitizing the first field according to the second desensitization rule.

[0076] It can be understood that in this example, the first field is first desensitized according to the previously agreed second desensitization rule to obtain the second field, and then the second field and the first suspected sensitive field are analyzed to obtain the first desensitization rule, which can further improve the accuracy of obtaining the desensitization rule.

[0077] S104: Add the first suspected sensitive field and the first desensitization rule to the preset sensitive information table.

[0078] As mentioned above, the preset sensitive information table includes sensitive fields and desensitization rules for sensitive fields. When the first sensitive probability is greater than the first threshold, it indicates that the first suspected sensitive field is a sensitive field. Therefore, adding the first suspected sensitive field and the first desensitization rule to the preset sensitive information table can improve the comprehensiveness of the preset sensitive information table, avoid leakage of sensitive information corresponding to the desensitization rule, and improve data security.

[0079] exist Figure 1 In the method shown, if the first suspected sensitive field in the test data does not belong to the preset sensitive information table and does not belong to the preset sensitive information exception table, the sensitivity probability of the first suspected sensitive field is obtained. And when the first sensitive probability is greater than the first threshold, the first desensitization rule of the first suspected sensitive field is obtained. Then, the first suspected sensitive field and the first desensitization rule are added to the preset sensitive information table, which can improve the comprehensiveness of the preset sensitive information table, avoid the leakage of sensitive information corresponding to the desensitization rule, and improve the security of the data.

[0080] In a possible example, after step S102, if the first sensitive probability is less than or equal to the first threshold, the first suspected sensitive field is added to the preset sensitive information exception table.

[0081] It can be understood that when the first sensitive probability is less than or equal to the first threshold, it means that the probability that the first suspected sensitive field is a sensitive field is small, and the first suspected sensitive field can be determined to be a non-sensitive field. Then, the first suspected sensitive field is added to the preset sensitive information exception table, which can improve the comprehensiveness of the preset sensitive information exception table. When the first suspected sensitive field is identified next time, it can be directly determined as a non-sensitive field, which can improve the recognition efficiency.

[0082] Please refer to Figure 2 , Figure 2 This is a flowchart of another sensitive information processing method provided by the present application. Taking the application of this aspect on a server as an example, it includes the following steps:

[0083] S201: Obtain a first suspected sensitive field in the test data.

[0084] S202: If the first suspected sensitive field does not belong to the preset sensitive information table, and the first suspected sensitive field does not belong to the preset sensitive information exception table, obtaining a first sensitive probability of the first suspected sensitive field.

[0085] Among them, step S201 and step S202 can refer to the description of step S101 and step S102, and will not be repeated here.

[0086] S203: If the first sensitive probability is less than or equal to a first threshold, sending attribute information of the first suspected sensitive field to a management terminal corresponding to the test data.

[0087] In the embodiment of the present application, the management terminal is a display device corresponding to the pre-bound contact information of the manager. For example, if the contact information is email, the management terminal is an electronic device for the manager to log in to the email application (or applet, public account, etc.).

[0088] The attribute information of the first suspected sensitive field may include the field's table identifier, data identifier, table name, field column name, and field content, and may also include sensitivity probability, etc., which is not limited here.

[0089] The manager can correspond to the test items. Figure 3 As shown in the figure, the setting page of the test project includes the project name, contact email, email template and content type. The project name is "[Sensitive Information Check] Sensitive Information Check of ABC Test Library", which means sensitive information check of ABC test library. The contact email is the email of the administrator. Figure 3 The email template is a template for sending emails to managers, and the content type is the language in which the email template is written. Figure 3In the example, the Hyper Text Markup Language (HTML) is used to set the mail format. In this way, the attribute information of the first suspected sensitive field can be sent to the management terminal through the contact information of the administrator (xxx@xxx.com.cn), and the attribute information is sent in the form of a mail template.

[0090] like Figure 4 As shown, the display page of the management terminal includes the administrator's avatar and contact email address (i.e., recipient), receiving time (2020.07.25 (Saturday) 14:30), project name ([Sensitive Information Check] ABC Test Library Sensitive Information Check) and attribute information of the first suspected sensitive field. Among them, the attribute information is presented in the form of a table. The table includes the table identifier, data identifier, table name, field column name and field content of the field. In this way, when the administrator views the email, he obtains the attribute information of the first suspected sensitive field, thereby determining whether the first suspected sensitive field is a sensitive field.

[0091] S204: If a confirmation instruction regarding the attribute information is received from the management terminal, a first desensitization rule for the first suspected sensitive field is obtained.

[0092] In the embodiment of the present application, the confirmation instruction is used to indicate that the first suspected sensitive field is a sensitive field. The first desensitization rule can refer to the description of step S103, which will not be repeated here.

[0093] S205: Add the first suspected sensitive field and the first desensitization rule to the preset sensitive information table.

[0094] exist Figure 2 In the method shown, if the first suspected sensitive field in the test data does not belong to the preset sensitive information table and does not belong to the preset sensitive information exception table, the sensitivity probability of the first suspected sensitive field is obtained. And when the first sensitive probability is less than or equal to the first threshold, the attribute information of the first suspected sensitive field is sent to the management terminal corresponding to the test data. Upon receiving the confirmation instruction for the attribute information from the management terminal, it is determined that the first suspected sensitive field is a sensitive field. Then, the first desensitization rule for the first suspected sensitive field is obtained, and the first suspected sensitive field and the first desensitization rule are added to the preset sensitive information table, which can improve the comprehensiveness of the preset sensitive information table, avoid the leakage of sensitive information corresponding to the desensitization rule, and improve the security of the data.

[0095] In a possible example, after step S203, if a denial instruction from the management terminal regarding the attribute information is received, the first suspected sensitive field is added to the preset sensitive information exception table.

[0096] In the embodiment of the present application, the denial instruction is used to indicate that the first suspected sensitive field is a non-sensitive field. It can be understood that when the denial instruction sent by the management terminal is received, the first suspected sensitive field can be determined to be a non-sensitive field. Then, the first suspected sensitive field is added to the preset sensitive information exception table, which can improve the comprehensiveness of the preset sensitive information exception table. When the first suspected sensitive field is identified next time, it can be directly determined as a non-sensitive field, which can improve the recognition efficiency.

[0097] In a possible example, if the first suspected sensitive field does not belong to a preset sensitive information table, and the first suspected sensitive field does not belong to a preset sensitive information exception table, attribute information of the first suspected sensitive field is sent to a management terminal corresponding to the test data.

[0098] It can be understood that when the preset sensitive information table and the preset sensitive information exception table cannot determine whether a suspected sensitive field is a sensitive field or a non-sensitive field, introducing manual judgment can avoid misidentification caused by automated processing and improve the accuracy of determining sensitive information.

[0099] The method of the embodiment of the present application is described in detail above, and the device of the embodiment of the present application is provided below.

[0100] and Figure 1 and Figure 2 The embodiment shown is consistent with that shown in FIG. Figure 5 , Figure 5 is a schematic diagram of the structure of a sensitive information processing device proposed in this application, such as Figure 5 As shown, the above-mentioned sensitive information processing device 500 includes:

[0101] The storage unit 503 is used to store a preset sensitive information table and a preset sensitive information exception table;

[0102] The processing unit 501 is used to obtain a first suspected sensitive field in the test data; if the first suspected sensitive field does not belong to the preset sensitive information table, and the first suspected sensitive field does not belong to the preset sensitive information exception table, obtain a first sensitive probability of the first suspected sensitive field; if the first sensitive probability is greater than a first threshold, obtain a first desensitization rule for the first suspected sensitive field;

[0103] The storage unit 503 is further used to add the first suspected sensitive field and the first desensitization rule to the preset sensitive information table.

[0104] In a possible example, the processing unit 501 is specifically used to obtain, from a production database, production data corresponding to the test data according to the data identifier of the test data; obtain, from the production data, a first field according to a target field column name of the first suspected sensitive field; obtain a similarity value between the first field and the first suspected sensitive field; and obtain a first sensitive probability of the first suspected sensitive field according to the similarity value.

[0105] In a possible example, after obtaining the similarity value between the first field and the first suspected sensitive field, the processing unit 501 is further used to obtain operation information of the test data; obtain the second sensitive probability of the first suspected sensitive field according to the operation information; and obtain the first sensitive probability of the first suspected sensitive field according to the second sensitive probability and the similarity value.

[0106] In a possible example, the processing unit 501 is specifically used to obtain, from the preset sensitive information table, according to the data identifier, a second desensitization rule corresponding to the production data; according to the second desensitization rule, desensitize the first field to obtain a second field; and according to the second field and the first suspected sensitive field, obtain a first desensitization rule for the first suspected sensitive field.

[0107] In a possible example, the processing unit 501 is specifically used to obtain multiple sensitive categories according to the preset sensitive information table; construct multiple keywords according to the multiple sensitive categories; generate a keyword detection script according to the multiple keywords; and obtain the first suspected sensitive field in the test data according to the keyword detection script.

[0108] In a possible example, after obtaining the first sensitive probability of the first suspected sensitive field, the sensitive information processing apparatus 500 further includes a communication unit 502, configured to send attribute information of the first suspected sensitive field to a management terminal corresponding to the test data if the sensitive probability is less than or equal to the first threshold;

[0109] The processing unit 501 is also used to execute the step of obtaining the first desensitization rule for the first suspected sensitive field if the communication unit 502 receives a confirmation instruction from the management terminal regarding the attribute information; or, if the communication unit 502 receives a denial instruction from the management terminal regarding the attribute information, add the first suspected sensitive field to the preset sensitive information exception table.

[0110] In a possible example, before obtaining the desensitization rule for the first suspected sensitive field, the processing unit 501 is also used to obtain the sensitivity ratio of the test database corresponding to the test data; obtain the timing duration according to the sensitivity ratio; and when the time of the first timer reaches the first timing duration, execute the step of obtaining the desensitization rule for the first suspected sensitive field.

[0111] The detailed execution process of each unit in the sensitive information processing device 500 can be found in the execution steps in the aforementioned method embodiment, which will not be repeated here.

[0112] and Figure 2 For details, please refer to Figure 6 , Figure 6 1 is a schematic diagram of the structure of another sensitive information processing device provided in an embodiment of the present application, wherein the sensitive information processing device is an electronic device or a server corresponding to a demand document processing application. Figure 6 As shown, the sensitive information processing device 600 includes a processor 610 , a memory 620 , a communication interface 630 , and one or at least one program 640 . Figure 5 The related functions implemented by the communication unit 502 shown can be implemented through the communication interface 630. Figure 5 The related functions implemented by the storage unit 503 shown can be implemented by the memory 620. Figure 5 The related functions implemented by the processing unit 501 shown can be implemented by the processor 610.

[0113] The one or at least one program 640 is stored in the memory 620 and is configured to be executed by the processor 610. The program 640 includes instructions for executing the following steps:

[0114] Obtain the first suspected sensitive field in the test data;

[0115] If the first suspected sensitive field does not belong to the preset sensitive information table, and the first suspected sensitive field does not belong to the preset sensitive information exception table, obtaining a first sensitive probability of the first suspected sensitive field;

[0116] If the first sensitivity probability is greater than a first threshold, obtaining a first desensitization rule for the first suspected sensitive field;

[0117] Add the first suspected sensitive field and the first desensitization rule to the preset sensitive information table.

[0118] In a possible example, in terms of obtaining the first sensitive probability of the first suspected sensitive field, the program 640 is specifically used to execute instructions for the following steps:

[0119] Acquire, from a production database, production data corresponding to the test data according to the data identifier of the test data;

[0120] Acquire a first field from the production data according to a target field column name of the first suspected sensitive field;

[0121] Obtaining a similarity value between the first field and the first suspected sensitive field;

[0122] A first sensitive probability of the first suspected sensitive field is obtained according to the similarity value.

[0123] In a possible example, after obtaining the similarity value between the first field and the first suspected sensitive field, the program 640 is further used to execute instructions for the following steps:

[0124] Acquiring operation information of the test data;

[0125] Acquire a second sensitive probability of the first suspected sensitive field according to the operation information;

[0126] A first sensitive probability of the first suspected sensitive field is obtained according to the second sensitive probability and the similarity value.

[0127] In a possible example, in terms of obtaining the first desensitization rule for the first suspected sensitive field, the program 640 is specifically used to execute instructions for the following steps:

[0128] From the preset sensitive information table, according to the data identifier, obtaining a second desensitization rule corresponding to the production data;

[0129] Perform desensitization processing on the first field according to the second desensitization rule to obtain a second field;

[0130] According to the second field and the first suspected sensitive field, a first desensitization rule of the first suspected sensitive field is obtained.

[0131] In a possible example, in the aspect of obtaining the first suspected sensitive field in the test data, the program 640 is specifically used to execute the following steps:

[0132] Acquire multiple sensitive categories according to the preset sensitive information table;

[0133] constructing a plurality of keywords according to the plurality of sensitive categories;

[0134] generating a keyword detection script according to the multiple keywords;

[0135] According to the keyword detection script, a first suspected sensitive field in the test data is obtained.

[0136] In a possible example, after obtaining the first sensitive probability of the first suspected sensitive field, the program 640 is further used to execute instructions for the following steps:

[0137] If the sensitivity probability is less than or equal to the first threshold, sending the attribute information of the first suspected sensitive field to the management terminal corresponding to the test data;

[0138] If a confirmation instruction for the attribute information is received from the management terminal, the step of obtaining the first desensitization rule for the first suspected sensitive field is executed; or,

[0139] If a denial instruction from the management terminal regarding the attribute information is received, the first suspected sensitive field is added to the preset sensitive information exception table.

[0140] In a possible example, before obtaining the desensitization rule of the first suspected sensitive field, the program 640 is further used to execute instructions of the following steps:

[0141] Obtaining a sensitivity ratio of a test database corresponding to the test data;

[0142] Obtaining a timing duration according to the sensitivity ratio;

[0143] When the time of the first timer reaches the first timing duration, the step of obtaining the desensitization rule of the first suspected sensitive field is executed.

[0144] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program, which enables a computer to execute part or all of the steps of any method recorded in the method embodiment, and the computer includes an electronic device and a server.

[0145] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program can be operated to cause a computer to execute to implement some or all steps of any method recorded in the method embodiment. The computer program product can be a software first installation package, and the computer includes an electronic device and a server.

[0146] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modes involved are not necessarily required by the present application.

[0147] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0148] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as at least one unit or component can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0149] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on at least one network unit. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0150] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software program mode.

[0151] If the integrated unit is implemented in the form of a software program model and sold or used as an independent product, it can be stored in a computer-readable memory. According to this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, magnetic disk or optical disk, etc., and other media that can store program codes.

[0152] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing the relevant hardware through a program, and the program may be stored in a computer-readable memory, which may include a flash drive, ROM, RAM, a magnetic disk or an optical disk, etc.

[0153] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A sensitive information processing method, characterized in that: include: Obtain the first suspected sensitive field in the test data; If the first suspected sensitive field does not belong to the preset sensitive information table, and the first suspected sensitive field does not belong to the preset sensitive information exception table, obtaining a first sensitive probability of the first suspected sensitive field; If the first sensitivity probability is greater than a first threshold, obtaining a first desensitization rule for the first suspected sensitive field; Adding the first suspected sensitive field and the first desensitization rule to the preset sensitive information table; The obtaining of the first sensitive probability of the first suspected sensitive field includes: Acquire, from a production database, production data corresponding to the test data according to the data identifier of the test data; Acquire a first field from the production data according to a target field column name of the first suspected sensitive field; Obtaining a similarity value between the first field and the first suspected sensitive field; Obtaining a first sensitive probability of the first suspected sensitive field according to the similarity value; The obtaining a first desensitization rule for the first suspected sensitive field includes: From the preset sensitive information table, according to the data identifier, obtaining a second desensitization rule corresponding to the production data; Perform desensitization processing on the first field according to the second desensitization rule to obtain a second field; According to the second field and the first suspected sensitive field, a first desensitization rule of the first suspected sensitive field is obtained.

2. The method according to claim 1, characterized in that After obtaining the similarity value between the first field and the first suspected sensitive field, the method further includes: Acquiring operation information of the test data; Acquire a second sensitive probability of the first suspected sensitive field according to the operation information; A first sensitive probability of the first suspected sensitive field is obtained according to the second sensitive probability and the similarity value.

3. The method according to claim 1 or 2, characterized in that: The obtaining of the first suspected sensitive field in the test data includes: Acquire multiple sensitive categories according to the preset sensitive information table; constructing a plurality of keywords according to the plurality of sensitive categories; generating a keyword detection script according to the multiple keywords; According to the keyword detection script, a first suspected sensitive field in the test data is obtained.

4. The method according to claim 1 or 2, characterized in that: After obtaining the first sensitive probability of the first suspected sensitive field, the method further includes: If the first sensitive probability is less than or equal to the first threshold, sending the attribute information of the first suspected sensitive field to the management terminal corresponding to the test data; If a confirmation instruction for the attribute information is received from the management terminal, the step of obtaining the first desensitization rule for the first suspected sensitive field is executed; or, If a denial instruction from the management terminal regarding the attribute information is received, the first suspected sensitive field is added to the preset sensitive information exception table.

5. The method according to claim 1 or 2, characterized in that: Before obtaining the first desensitization rule for the first suspected sensitive field, the method further includes: Obtaining a sensitivity ratio of a test database corresponding to the test data; Determine a first timing duration according to the sensitivity ratio; When the time of the first timer reaches the first timing duration, the step of obtaining the first desensitization rule of the first suspected sensitive field is executed.

6. A sensitive information processing device, characterized in that: The method comprises means for executing the method according to any one of claims 1 to 5.

7. A sensitive information processing device, characterized in that: The method comprises a processor, a memory, a communication interface and one or at least one program, wherein the one or at least one program is stored in the memory and configured to be executed by the processor, and the program comprises instructions for executing the steps in any one of the methods of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which enables a computer to execute to implement the method according to any one of claims 1 to 5.

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