Data anonymization methods, devices, storage media and electronic equipment
By generating a target bitmap and matching the desensitization rules in the desensitization rule set, the problem of low data desensitization flexibility is solved, and flexible and accurate data desensitization processing is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TRAVELSKY TECHNOLOGY LIMITED
- Filing Date
- 2026-03-12
- Publication Date
- 2026-06-02
Smart Images
Figure CN122133191A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data processing, and more specifically, to a data desensitization method, apparatus, storage medium, and electronic device. Background Technology
[0002] With the rapid development of information technology and its widespread application in various fields (such as civil aviation), the importance of data security has become particularly prominent. Data anonymization technology is one of the key technologies for ensuring data security. Data anonymization is like "locking" sensitive data into a "safe," playing a crucial role in ensuring data security, compliance, and business continuity.
[0003] In related technologies, after identifying sensitive fields from the data to be anonymized, the data is typically anonymized directly based on the anonymization rules corresponding to those sensitive fields. However, this ignores the fact that different anonymization methods may be needed in different scenarios (e.g., different combinations of sensitive fields). In such cases, related technologies may involve adding multiple judgment conditions to the anonymization rules corresponding to each sensitive field, or relying on manual secondary confirmation, resulting in low flexibility in data anonymization.
[0004] There is currently no effective solution to the aforementioned problems in the relevant technologies. Summary of the Invention
[0005] The main objective of this application is to provide a data desensitization method, apparatus, storage medium, and electronic device to solve the problem of low flexibility in data desensitization in related technologies.
[0006] To achieve the above objectives, according to one aspect of this application, a data anonymization method is provided. The method includes: acquiring data to be anonymized; identifying sensitive fields from the data to be anonymized, and determining a target bitmap corresponding to the data to be anonymized based on the sensitive fields, wherein different bits in the target bitmap correspond to different sensitive fields, and the target bitmap represents the sensitive fields contained in the data to be anonymized based on the bit values; determining anonymization rules matching the target bitmap from a set of anonymization rules, and anonymizing the data to be anonymized according to the anonymization rules to obtain anonymized data, wherein the set of anonymization rules includes anonymization rules matching different bitmaps.
[0007] Optionally, the data anonymization method may also include one of the following: calculating the target value based on the target bitmap, mapping the target value to a set of anonymization rules, and determining that the anonymization rule corresponding to the target value is an anonymization rule matching the target bitmap; calculating the target value based on the target bitmap, performing a modulo operation on the target value, mapping the modulo result to a set of anonymization rules, and determining that the anonymization rule corresponding to the modulo result is an anonymization rule matching the target bitmap; or calculating the target value based on the target bitmap, performing a hash operation on the target value, mapping the hash result to a set of anonymization rules, and determining that the anonymization rule corresponding to the hash result is an anonymization rule matching the target bitmap.
[0008] Optionally, the data anonymization method may further include: identifying multiple fields from the data to be anonymized; for each field, determining whether the field is included in a preset set of sensitive fields; and if the field is included in the set of sensitive fields, identifying the field as a sensitive field.
[0009] Optionally, the data anonymization method further includes: determining an initial bitmap based on a preset set of sensitive fields, wherein the number of sensitive fields in the set of sensitive fields is equal to the number of bits in the initial bitmap; and updating the initial bitmap based on the sensitive fields contained in the data to be anonymized to obtain the target bitmap.
[0010] Optionally, the data anonymization method further includes: for each sensitive field in the data to be anonymized, determining the bit corresponding to the sensitive field from the initial bitmap; updating the value of the bit corresponding to the sensitive field to a target value, wherein the target value is used to characterize that the sensitive field exists in the data to be anonymized.
[0011] Optionally, the data desensitization method may also include: for each desensitization sub-rule, determining the sensitive field corresponding to the desensitization sub-rule from the data to be desensitized; and desensitizing the field value of the sensitive field corresponding to the desensitization sub-rule based on the desensitization sub-rule.
[0012] Optionally, the data anonymization method may also include at least one of the following: when a data storage request is detected, identifying the data in the data storage request as data to be anonymized; during the logging process, identifying the data to be logged as data to be anonymized.
[0013] To achieve the above objectives, according to another aspect of this application, a data anonymization apparatus is provided. The apparatus includes: an acquisition module for acquiring data to be anonymized; a first determination module for identifying sensitive fields from the data to be anonymized and determining a target bitmap corresponding to the data to be anonymized based on the sensitive fields, wherein different bits in the target bitmap correspond to different sensitive fields, and the target bitmap characterizes the sensitive fields contained in the data to be anonymized based on the bit values; and a processing module for determining an anonymization rule matching the target bitmap from a set of anonymization rules and anonymizing the data to be anonymized according to the anonymization rules to obtain anonymized data, wherein the set of anonymization rules includes anonymization rules matching different bitmaps.
[0014] Optionally, the processing module further includes one of the following: a first determining submodule, used to calculate the target value based on the target bitmap, map the target value to the desensitization rule set, and determine that the desensitization rule corresponding to the target value is a desensitization rule matching the target bitmap; a second determining submodule, used to calculate the target value based on the target bitmap, perform a modulo operation on the target value, map the modulo result to the desensitization rule set, and determine that the desensitization rule corresponding to the modulo result is a desensitization rule matching the target bitmap; a third determining submodule, used to calculate the target value based on the target bitmap, perform a hash operation on the target value, map the hash result to the desensitization rule set, and determine that the desensitization rule corresponding to the hash result is a desensitization rule matching the target bitmap.
[0015] Optionally, the first determining module further includes: an identification submodule, used to identify multiple fields from the data to be de-identified; a judgment submodule, used to determine whether a preset set of sensitive fields includes each field; and a fourth determining submodule, used to determine the field as a sensitive field if it is included in the set of sensitive fields.
[0016] Optionally, the first determining module further includes: a fifth determining submodule, used to determine an initial bitmap based on a preset set of sensitive fields, wherein the number of sensitive fields in the set of sensitive fields is equal to the number of bits in the initial bitmap; and an updating submodule, used to update the initial bitmap based on the sensitive fields contained in the data to be de-identified, to obtain a target bitmap.
[0017] Optionally, the update submodule further includes: a determination unit, used to determine the bit corresponding to each sensitive field in the data to be de-identified from the initial bitmap; and an update unit, used to update the value of the bit corresponding to the sensitive field to a target value, wherein the target value is used to characterize that the sensitive field exists in the data to be de-identified.
[0018] Optionally, the processing module further includes: a sixth determining submodule, used to determine the sensitive field corresponding to the desensitization subrule from the data to be desensitized for each desensitization subrule; and a processing submodule, used to perform desensitization processing on the field value of the sensitive field corresponding to the desensitization subrule based on the desensitization subrule.
[0019] Optionally, the data desensitization device further includes at least one of the following: a second determining module, used to determine the data in the data storage request as data to be desensitized when a data storage request is detected; and a third determining module, used to determine the data to be recorded in the log as data to be desensitized during the log recording process.
[0020] To achieve the above objectives, according to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the above-described data desensitization method.
[0021] To achieve the above objectives, according to another aspect of this application, an electronic device is provided, the electronic device including a memory storing an executable program; and a processor for running the program, wherein the program executes the above-described data desensitization method during runtime.
[0022] To achieve the above objectives, according to another aspect of this application, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the data desensitization method described above.
[0023] In this embodiment, by identifying sensitive fields from the data to be anonymized and determining the target bitmap corresponding to the data based on these sensitive fields, the combination of sensitive fields involved in the data to be anonymized is accurately represented using a bitmap. By matching anonymization rules in the anonymization rule set based on the target bitmap, corresponding anonymization measures can be taken according to different scenarios and needs. That is, different anonymization methods can be adopted for different combinations of sensitive fields that may appear in the data to be anonymized, thereby improving the flexibility and accuracy of data anonymization.
[0024] Therefore, the method provided in this application achieves the goal of using different desensitization methods for different combinations of sensitive fields involved in the data to be desensitized, realizes the technical effect of improving the flexibility of data desensitization, and solves the technical problem of low flexibility of data desensitization in related technologies. Attached Figure Description
[0025] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:
[0026] Figure 1 This is a hardware structure block diagram of a computer terminal provided according to an embodiment of this application;
[0027] Figure 2 This is a flowchart of a data desensitization method provided according to an embodiment of this application;
[0028] Figure 3 This is a schematic diagram of the desensitization process provided according to an embodiment of this application;
[0029] Figure 4 This is a schematic diagram illustrating the determination of a target bitmap according to an embodiment of this application;
[0030] Figure 5 This is a schematic diagram of a data desensitization method provided according to an embodiment of this application;
[0031] Figure 6 This is a schematic diagram of a data desensitization device provided according to an embodiment of this application;
[0032] Figure 7 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation
[0033] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.
[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0035] It should be noted that the information collected in this application (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) are information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of this data all comply with relevant laws, regulations, and standards, and necessary measures have been taken to ensure compliance with public order and good morals. Corresponding access points are provided for users to choose whether to authorize or refuse. For example, interfaces are established between this system and relevant users or organizations, providing users with corresponding access points to choose whether to agree to or refuse automated decision-making results; if the user chooses to refuse, the process proceeds to the expert decision-making stage.
[0036] Example 1
[0037] According to an embodiment of this application, an embodiment of a data desensitization method is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.
[0038] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware structure block diagram of a computer terminal (or mobile device) for implementing a data anonymization method is shown. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor (MCU) or a field-programmable gate array (FPGA), etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output (I / O) interface, a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.
[0039] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).
[0040] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the data desensitization method in this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the aforementioned data desensitization method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
[0041] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.
[0042] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).
[0043] Under the aforementioned operating environment, this application provides the following: Figure 2 The data anonymization method shown. Figure 2 This is a flowchart of the data desensitization method according to Embodiment 1 of this application.
[0044] Step S201: Obtain the data to be de-identified.
[0045] Optionally, electronic devices, application systems, servers, or other similar devices can be used as the executing entity of this application. In this embodiment, the target processing system is used as the executing entity to perform the above-described data desensitization method.
[0046] Optionally, the data to be anonymized can be the original data containing sensitive information. The content of the data to be anonymized varies depending on the specific application scenario. For example, in the civil aviation sector, the data to be anonymized could be a real production dataset generated by the actual business operations of the civil aviation information system. This dataset may contain sensitive information as defined by industry standards in the civil aviation sector.
[0047] Step S202: Identify sensitive fields from the data to be de-identified, and determine the target bitmap corresponding to the data to be de-identified based on the sensitive fields. Different bits in the target bitmap correspond to different sensitive fields, and the target bitmap represents the sensitive fields contained in the data to be de-identified based on the bit values.
[0048] In an optional embodiment, the system can define a pre-defined set of sensitive fields. The system can perform field-by-field parsing and matching on the data to be anonymized, and if a field belongs to the set of sensitive fields, then that field is determined to be a sensitive field.
[0049] Optionally, after identifying the sensitive fields, a target bitmap corresponding to the data to be anonymized is determined based on these sensitive fields. A bitmap is an efficient data structure based on bit operations, which can represent the binary state of an element (e.g., presence / absence) using a single bit. The target bitmap, also called the sensitive field bitmap, is a bitmap formed based on the position of the sensitive fields in the sensitive field set within the data to be anonymized. Each sensitive data field is represented by a bitmap placeholder; that is, different bits in the target bitmap correspond to different sensitive fields. For example, if the sensitive data field exists in the data to be anonymized, the corresponding bitmap placeholder is 1; if the sensitive data field does not exist, the corresponding bitmap placeholder is 0.
[0050] For example, the system initializes an N-bit sensitive field bitmap by setting each bit to 0. It receives the data to be anonymized, scans, analyzes, and slices it. The sliced data is then searched in the sensitive field set. If a sliced data point exists in the sensitive field set, it is identified as a sensitive field, and the corresponding position in the sensitive field bitmap is set to 1. Finally, the updated sensitive field bitmap is output.
[0051] For example, if the sensitive field set contains 7 fields, the target bitmap may be an array of length 7, such as "1000101", where each bit corresponds to a sensitive field. The sensitive fields corresponding to the bits set to 1 are the sensitive fields contained in the data to be de-identified, and the sensitive fields corresponding to the bits set to 0 are the sensitive fields not contained in the data to be de-identified.
[0052] Step S203: Determine the desensitization rule matching the target bitmap from the desensitization rule set, and desensitize the data to be desensitized according to the desensitization rule to obtain the desensitized data. The desensitization rule set includes desensitization rules matching different bitmaps.
[0053] Optionally, the target processing system can have a pre-defined set of de-identification rules. This set includes multiple de-identification rules, each corresponding to a different bitmap. In other words, sensitive fields in the sensitive field set can be combined to form different subsets of sensitive fields. Different de-identification rules can be set for these subsets based on business needs, thus forming a set of de-identification rules. These subsets can be represented using bitmaps, meaning different subsets of sensitive fields correspond to different bitmaps.
[0054] In an optional embodiment, the target processing system can find a de-identification rule that matches the target bitmap from the de-identification rule set using methods such as direct mapping, modulo mapping, or hash mapping.
[0055] After determining the desensitization rule for the target bitmap, the desensitization operation is performed on the data to be desensitized according to the selected desensitization rule, and the desensitized data is output.
[0056] In an optional embodiment, the target processing system includes a desensitization procedure. Figure 3 This is a schematic diagram of the desensitization process provided in the embodiments of this application, such as... Figure 3 As shown, the data masking program can achieve the mapping of masking rules and data masking based on the following steps:
[0057] Step 1: Input the data to be de-identified and the bitmap of the sensitive fields of the data into the de-identification program.
[0058] Step two: The de-identification rule set contains de-identification rules configured according to business requirements. The sensitive field bitmaps of the data to be de-identified are mapped to the de-identification rule set to obtain the specific de-identification rules that apply to that data.
[0059] Step 3: Perform data anonymization on the data to be anonymized according to the specific anonymization rules to obtain the anonymized data.
[0060] Step four: The desensitization program outputs the desensitized data.
[0061] In this embodiment, by identifying sensitive fields from the data to be anonymized and determining the target bitmap corresponding to the data based on these sensitive fields, the combination of sensitive fields involved in the data to be anonymized is accurately represented using a bitmap. By matching anonymization rules in the anonymization rule set based on the target bitmap, corresponding anonymization measures can be taken according to different scenarios and needs. That is, different anonymization methods can be adopted for different combinations of sensitive fields that may appear in the data to be anonymized, thereby improving the flexibility and accuracy of data anonymization.
[0062] Therefore, the method provided in this application achieves the goal of using different desensitization methods for different combinations of sensitive fields involved in the data to be desensitized, realizes the technical effect of improving the flexibility of data desensitization, and solves the technical problem of low flexibility of data desensitization in related technologies.
[0063] Optionally, in the data desensitization method provided in this application embodiment, a target value is calculated based on the target bitmap, and the target value is mapped to a desensitization rule set to determine that the desensitization rule corresponding to the target value is a desensitization rule matching the target bitmap; a target value is calculated based on the target bitmap, and a modulo operation is performed on the target value, and the modulo result is mapped to a desensitization rule set to determine that the desensitization rule corresponding to the modulo result is a desensitization rule matching the target bitmap; a target value is calculated based on the target bitmap, and a hash operation is performed on the target value, and the hash result is mapped to a desensitization rule set to determine that the desensitization rule corresponding to the hash result is a desensitization rule matching the target bitmap.
[0064] In an optional embodiment, a target value is calculated based on the target bitmap. For example, if the target bitmap is binary data, it is converted to decimal to obtain the target value. The target value is then mapped to a set of desensitization rules to find a desensitization rule that matches the sequence. For example, assuming the target bitmap is "1000101", which represents the 1st, 5th, and 7th fields in the sensitive field set (containing a total of 7 sensitive fields) appearing in the data to be desensitized, after binary-to-decimal conversion, the value is 69. Then, 69 is mapped to the set of desensitization rules to find the corresponding rule, thereby obtaining the desensitization rule matching the target bitmap.
[0065] In an optional embodiment, a target value is calculated based on the target bitmap. A modulo operation is then performed on the target value. For example, the target bitmap is converted to decimal to obtain the target value, and then the modulo operation is performed on the target value to obtain the remainder result. For instance, assuming the target bitmap is "1000101", after converting from binary to decimal, the value 69 is obtained. Then, the value 69 is moduloed by the number of rules in the desensitization rule set or a preset value M, such as 69%M, to obtain the remainder result. The result of the remainder operation is used as an index to find the corresponding rule in the desensitization rule set, thereby obtaining the desensitization rule matching the target bitmap.
[0066] In an optional embodiment, a target value is calculated based on the target bitmap, and a hash operation is performed on the target value, assuming the resulting hash value is w1. Then, the hash value w1 is mapped to a set of de-identification rules to find the corresponding de-identification rule, thereby obtaining the de-identification rule that matches the target bitmap.
[0067] It should be noted that direct mapping provides the most straightforward way to look up rules, suitable for situations where the rule set is small or the rules have a direct correspondence with the bitmap pattern. The modulo operation increases the randomness and flexibility in the rule matching process, which is helpful in scenarios where the rule set is large and the security of the de-identification process needs to be increased. The hash operation provides high scalability and security. Through the above methods, different business needs and security levels can be flexibly adapted, thereby further improving the flexibility of data de-identification.
[0068] Optionally, in the data desensitization method provided in this application embodiment, identifying sensitive fields from the data to be desensitized includes: identifying multiple fields from the data to be desensitized; for each field, determining whether a preset set of sensitive fields includes the field; and if the field is included in the set of sensitive fields, determining the field as a sensitive field.
[0069] In an optional embodiment, the target processing system may perform traversal processing on the data to be de-identified in order to identify multiple fields.
[0070] In an optional embodiment, the sensitive field set includes all de-identified fields that may be involved in the de-identification process. For each field, the target processing system can determine whether the field is included in the preset sensitive field set. If the field is indeed in the sensitive field set, it is marked or identified as a sensitive field. Conversely, if the field does not exist in the sensitive field set, it is determined that the field is not a sensitive field.
[0071] For example, in the civil aviation context, the sensitive fields involved include, but are not limited to, the following:
[0072] Table 1
[0073]
[0074] An optional set of sensitive fields can be recorded in the following form:
[0075] Table 2
[0076]
[0077] In this context, Username represents the username field, idCard represents the ID card number field, passportNumber represents the passport number field, frequentFlyerNumber represents the frequent flyer card number field, flightNumber represents the flight number field, seatNumber represents the seat number field, and password represents the password field.
[0078] During the data anonymization process, these fields are examined one by one to determine whether the data contains sensitive information, and thus decide whether anonymization rules need to be applied. For example, if the fields "username" and "password" appear in the data to be anonymized, the corresponding bits in the sensitive field bitmap will be set to 1, indicating the presence of sensitive fields that require anonymization. Subsequently, based on the sensitive field bitmap and a pre-defined set of anonymization rules, it can be determined how to anonymize these sensitive fields to prevent information leakage while maintaining data availability and functionality.
[0079] It should be noted that the above method enables the accurate identification of sensitive fields contained in the data to be anonymized.
[0080] Optionally, in the data desensitization method provided in this application embodiment, determining the target bitmap corresponding to the data to be desensitized based on sensitive fields includes: determining an initial bitmap according to a preset set of sensitive fields, wherein the number of sensitive fields in the set of sensitive fields is equal to the number of bits in the initial bitmap; updating the initial bitmap based on the sensitive fields contained in the data to be desensitized to obtain the target bitmap.
[0081] Optionally, the system can determine an initial bitmap based on a preset set of sensitive fields. The length of the initial bitmap is equal to the number of sensitive fields in the set. That is, each bit in the initial bitmap represents a sensitive field in the set, and different bits represent different sensitive fields. The value of each bit in the initial bitmap is an initial value, indicating that the sensitive field corresponding to that bit does not exist in the data to be de-identified.
[0082] For example, suppose the preset set of sensitive fields in the civil aviation field may include seven fields: username, idCard, passportNumber, frequentFlyerNumber, flightNumber, seatNumber, and password. Then the initial bitmap can be set to "0000000", which means that no sensitive fields have been identified yet.
[0083] Optionally, after identifying the sensitive fields contained in the data to be anonymized, the initial bitmap is updated based on these sensitive fields to obtain the target bitmap. Optionally, if the data to be anonymized contains any sensitive fields, the corresponding bit in the initial bitmap will be updated from 0 to 1; otherwise, it will remain 0. For example, suppose the data to be anonymized contains the fields username, flightNumber, and password. Then, in the initial bitmap "0000000", based on the sensitive fields identified from the data to be anonymized, the 1st bit (corresponding to username), the 4th bit (flightNumber), and the 7th bit (password) are updated to 1, resulting in the target bitmap "1001001".
[0084] In an optional embodiment, the data to be de-identified is scanned, analyzed, and sliced. The slicing results are searched in a set of sensitive fields. Each sensitive data field is represented by a bitmap placeholder. If the sensitive data field exists in the data to be de-identified, the corresponding bitmap placeholder is 1; if the sensitive data field does not exist, the corresponding bitmap placeholder is 0. After the scan is completed, an N-bit sensitive field bitmap is obtained.
[0085] For example, the target processing system has a pre-installed scanning program. Figure 4 This is a schematic diagram illustrating the determination of a target bitmap according to an embodiment of this application, such as... Figure 4 As shown, the scanning program can determine the target bitmap based on the following steps:
[0086] Step 1: Input the data to be anonymized into the scanning program. The data to be anonymized may contain some sensitive information. Then initialize the sensitive field bitmap (i.e., the initial bitmap).
[0087] Step 2: Analyze the data to be de-identified, and perform analysis and segmentation on the data.
[0088] Step 3: Search for all slices of the data to be anonymized in the sensitive field set. If slice i exists in the sensitive fields and is the j-th sensitive field in the sensitive field set, then set the position j of the sensitive field bitmap to 1, and so on, to generate the sensitive field bitmap (i.e., the target bitmap) of the data to be anonymized.
[0089] The fourth step is to output the generated bitmap of sensitive fields of the data to be de-identified to the next processing program.
[0090] In an optional embodiment, the process of determining the target bitmap is illustrated by a specific example. For example, the following is an example fragment of data to be anonymized. The data to be anonymized is an aviation business message, and the message adopts a key-value pair format: "{"flightNumber":"CA1202 / 2025-11-2016:33","cookie":"2","digestChecked ":"0","eTermLang":"1","eTermType":"0","eTermVersion":"3860","hostId":"MCSS165","ip":"172.16.181.194","ip2":"172.16.181.194","mac":"00ffc72abcff","msgType":"0x01","password":"123456@","platform":"0x00","pro ductVersion":"0000","rid":"0x00","serverName":"server-test5","sid":"0x00","socketNo":"4","subtype":"1" ,"trace":"1","transId":"BXXMCSS0072025112011043000000129","type":"0","username":"zhangsan","ver":"2"}".
[0091] The data to be anonymized in the above example is scanned and sliced to obtain the data set of key fields of the data to be anonymized after slicing. An example of the data set of key fields after slicing is as follows: "{"flightNumber","cookie","digestChecked ","eTermLang","eTermType","eTermVersion","hostId","ip","ip2","mac","msgType","password","platform","productVersion","rid","serverName","sid","socketNo","subtype","trace","transId","type","username","ver"}".
[0092] After slicing the data to be anonymized, the key field set is searched in the sensitive field set. Each sensitive data field is represented by a bitmap placeholder. According to the example of the sensitive field set in Table 2, the sensitive field bitmap is a 7-bit bitmap, and each bit is initialized to 0. If the keys "flightNumber", "username" and "password" are found in the key field set of the data to be anonymized, the first, fifth and seventh bits of the sensitive data field bitmap are set to 1, and the resulting sensitive field bitmap is "1000101".
[0093] Optionally, the sensitive field bitmap output by the scanning program can be mapped to a set of desensitization rules, find the corresponding desensitization rules, and use the desensitization rules to desensitize the data to be desensitized.
[0094] It should be noted that the above method can quickly identify the fields that need to be de-identified, skip those non-sensitive fields, and use a simple bitmap to show the combination of sensitive fields corresponding to the data to be de-identified, thereby saving computing resources and improving the efficiency of data de-identification.
[0095] Optionally, in the data desensitization method provided in this application embodiment, the initial bitmap is updated based on the sensitive fields contained in the data to be desensitized, including: for each sensitive field in the data to be desensitized, determining the bit corresponding to the sensitive field from the initial bitmap; updating the value of the bit corresponding to the sensitive field to a target value, wherein the target value is used to characterize that the sensitive field exists in the data to be desensitized.
[0096] In an optional embodiment, the value of each bit in the initial bitmap is an initial value, which indicates that the sensitive field corresponding to that bit does not exist in the data to be de-identified.
[0097] Optionally, for each sensitive field in the data to be anonymized, the corresponding bit for that sensitive field is determined from the initial bitmap. For example, if the data to be anonymized contains the fields username, flightNumber, and password, then in the initialized "0000000" bitmap, the bits corresponding to these three fields need to be located. Assuming username corresponds to the 1st bit, flightNumber to the 4th bit, and password to the 7th bit, then these specified bits need to be found.
[0098] Optionally, after determining the bit corresponding to the sensitive field from the initial bitmap, the value of the bit corresponding to the sensitive field is updated to the target value. For example, after finding the bits corresponding to username, flightNumber, and password, the values of these bits are updated from 0 to 1, thus obtaining a new target bitmap "1001001".
[0099] In an optional embodiment, the target bitmap is determined after all sensitive fields in the data to be de-identified have had their bit values updated.
[0100] It should be noted that by matching sensitive fields to specific locations in the bitmap and updating the values at those locations to the target values, the accuracy of identifying the target bitmap can be improved.
[0101] Optionally, in the data desensitization method provided in this application embodiment, the desensitization rule for target bitmap matching includes multiple desensitization sub-rules. The desensitization of the data to be desensitized according to the desensitization rule includes: for each desensitization sub-rule, determining the sensitive field corresponding to the desensitization sub-rule from the data to be desensitized; and desensitizing the field value of the sensitive field corresponding to the desensitization sub-rule based on the desensitization sub-rule.
[0102] In a set of de-identification rules, each rule may contain multiple sub-rules, each corresponding to one or more specific sensitive fields. For example, suppose the de-identification rules obtained from the target bitmap mapping contain two sub-rules: rule A (partially masking the username field) and rule B (hash-based de-identification of the password field). The system can then find the username and password fields related to rule A and rule B from the data to be de-identified.
[0103] After identifying the sensitive fields corresponding to each de-identification sub-rule, the values of these fields are de-identified according to the specific instructions of the sub-rule. For example, for rule A, the username field is partially masked, such as replacing the last few characters of the username field with asterisks (" "). For rule B, the password field is hashed using an encryption algorithm. This means the original real username might become "zhang". ", and password became an encrypted string.
[0104] In an optional embodiment, the set of de-identification rules is configured in a configuration center, and different versions of the set can be released as needed. For example, some of the de-identification rules included in the set might look like this:
[0105] Rule 1: Empty.
[0106] Rule 2: Empty.
[0107] Rule 32: Keep the first 6 digits and the last 4 digits of the idCard, and use "" for the middle 8 digits. "Replacement".
[0108] Rule 69: Encrypt the password; if the flightNumber's date is later than the current time, perform a linear transformation on the flightNumber.
[0109] Rule 96: Keep the first 2 and last 4 digits of the idCard, and use "" for the middle 12 digits. "Replacement".
[0110] In an optional embodiment, a mapping function is used to map the sensitive data field bitmap to rule 69. Rule 69 is then used to desensitize the data to be desensitized in the example above, resulting in the desensitized data as: "{"flightNumber":"DB2313 / 2025-11-2016:33","cookie":"2","digestChecked":"0 ","eTermLang":"1","eTermType":"0","eTermVersion":"3860","hostId":"MCSS165","ip":"172.16.181.194","ip2":"172.16.181.194","mac":"00ffc72abcff","msgType":"0x01","password":"0C8ABDB962F042D1857C66DD26B0C87B","platform": "0x00","productVersion":"0000","rid":"0x00","serverName":"server-test5","sid":"0x00","socketNo":"4","subtype ":"1","trace":"1","transId":"BXXMCSS0072025112011043000000129","type":"0","username":"zhangsan","ver":"2"}".
[0111] In an optional embodiment, the target bitmap is used to match the desensitization rules, but this does not mean that the desensitization rules must include sub-rules corresponding to sensitive fields in the target bitmap whose bit values are all set to the target value, as shown in rule 69 above. That is, the target bitmap is used to determine the combination of sensitive fields corresponding to the data to be desensitized, i.e., to determine a desensitization scenario, and the specific desensitization method is determined according to the desensitization rules.
[0112] Optionally, in the data desensitization method provided in this application embodiment, obtaining the data to be desensitized includes at least one of the following: when a data storage request is detected, determining the data in the data storage request as the data to be desensitized; during the logging process, determining the data to be recorded in the log as the data to be desensitized.
[0113] Optionally, when the system detects a data storage request—that is, when new data is to be stored in a database or data warehouse—sensitive information within this data needs to be identified and processed to prevent leakage during storage. For example, in a civil aviation information system, whenever new passenger information or flight data needs to be stored, the system can trigger a scanning procedure to process the data in these requests as data to be anonymized. For instance, when a flight booking request is received, the system will automatically capture all data in this request and use it as data to be anonymized for subsequent sensitive field scanning.
[0114] Optionally, during system operation, the system will record various operation logs for maintenance and other purposes. These log data may contain sensitive user information; therefore, sensitive fields need to be identified and processed before logging. For example, when any operation in the civil aviation system causes log recording (such as passenger information updates, flight status changes, etc.), the system will automatically treat the data involved in these operations as data to be anonymized. For instance, if the log record needs to include the username and password involved in a certain operation, these fields will be marked as data to be anonymized before logging.
[0115] It should be noted that by performing data anonymization before data storage, the stored data does not contain any sensitive information, thereby reducing the risk of data leakage and meeting data security requirements. By performing data anonymization during the log recording process, sensitive information can be prevented from being exposed due to log file leakage, while ensuring that the integrity and readability of the logs are not affected, thus improving the reliability of data anonymization.
[0116] In an alternative embodiment, Figure 5 This is a schematic diagram of a data desensitization method provided in an embodiment of this application. Figure 5 An optional application process of this embodiment will be described. For example... Figure 5 As shown, after acquiring the anonymized data, the target processing system uses a scanning program to identify sensitive fields from the data to be anonymized based on a set of sensitive fields, and determines a sensitive field bitmap based on the identified sensitive fields. Then, the anonymization program uses the sensitive field bitmap to identify matching anonymization rules from a set of anonymization rules. Finally, the anonymization rules are used to process the data to be anonymized, resulting in the anonymized data.
[0117] In this embodiment, by identifying sensitive fields from the data to be anonymized and determining the target bitmap corresponding to the data based on these sensitive fields, the combination of sensitive fields involved in the data to be anonymized is accurately represented using a bitmap. By matching anonymization rules in the anonymization rule set based on the target bitmap, corresponding anonymization measures can be taken according to different scenarios and needs. That is, different anonymization methods can be adopted for different combinations of sensitive fields that may appear in the data to be anonymized, thereby improving the flexibility and accuracy of data anonymization.
[0118] Therefore, the method provided in this application achieves the goal of using different desensitization methods for different combinations of sensitive fields involved in the data to be desensitized, realizes the technical effect of improving the flexibility of data desensitization, and solves the technical problem of low flexibility of data desensitization in related technologies.
[0119] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.
[0120] Example 2
[0121] This application also provides a data desensitization device. It should be noted that the data desensitization device of this application can be used to execute the data desensitization method provided in this application. The data desensitization device provided in this application is described below.
[0122] According to embodiments of this application, an apparatus for implementing the above-described data desensitization method is also provided, such as... Figure 6 As shown, the device includes:
[0123] Module 601 is used to acquire data to be de-identified;
[0124] The first determining module 602 is used to identify sensitive fields from the data to be de-identified and determine the target bitmap corresponding to the data to be de-identified based on the sensitive fields. Different bits in the target bitmap correspond to different sensitive fields, and the target bitmap represents the sensitive fields contained in the data to be de-identified based on the value of the bits.
[0125] The processing module 603 is used to determine the desensitization rule matching the target bitmap from the desensitization rule set, and desensitize the data to be desensitized according to the desensitization rule to obtain the desensitized data. The desensitization rule set includes desensitization rules matching different bitmaps.
[0126] In this embodiment, by identifying sensitive fields from the data to be anonymized and determining the target bitmap corresponding to the data based on these sensitive fields, the combination of sensitive fields involved in the data to be anonymized is accurately represented using a bitmap. By matching anonymization rules in the anonymization rule set based on the target bitmap, corresponding anonymization measures can be taken according to different scenarios and needs. That is, different anonymization methods can be adopted for different combinations of sensitive fields that may appear in the data to be anonymized, thereby improving the flexibility and accuracy of data anonymization.
[0127] Therefore, the method provided in this application achieves the goal of using different desensitization methods for different combinations of sensitive fields involved in the data to be desensitized, realizes the technical effect of improving the flexibility of data desensitization, and solves the technical problem of low flexibility of data desensitization in related technologies.
[0128] Optionally, in the data desensitization apparatus provided in this application embodiment, the processing module further includes one of the following: a first determining submodule, which calculates a target value based on a target bitmap, maps the target value to a desensitization rule set, and determines that the desensitization rule corresponding to the target value is a desensitization rule matching the target bitmap; a second determining submodule, which calculates a target value based on a target bitmap, performs a modulo operation on the target value, maps the modulo result to a desensitization rule set, and determines that the desensitization rule corresponding to the modulo result is a desensitization rule matching the target bitmap; and a third determining submodule, which calculates a target value based on a target bitmap, performs a hash operation on the target value, maps the hash result to a desensitization rule set, and determines that the desensitization rule corresponding to the hash result is a desensitization rule matching the target bitmap.
[0129] Optionally, in the data desensitization device provided in the embodiments of this application, the first determining module further includes: an identification submodule, used to identify multiple fields from the data to be desensitized; a judging submodule, used to judge whether a preset sensitive field set includes the field for each field; and a fourth determining submodule, used to determine the field as a sensitive field if the sensitive field set includes the field.
[0130] Optionally, in the data desensitization apparatus provided in this application embodiment, the first determining module further includes: a fifth determining submodule, used to determine an initial bitmap according to a preset set of sensitive fields, wherein the number of sensitive fields in the set of sensitive fields is equal to the number of bits in the initial bitmap; and an updating submodule, used to update the initial bitmap based on the sensitive fields contained in the data to be desensitized, to obtain a target bitmap.
[0131] Optionally, in the data desensitization apparatus provided in this application embodiment, the update submodule further includes: a determining unit, used to determine the bit corresponding to each sensitive field in the data to be desensitized from the initial bitmap; and an updating unit, used to update the value of the bit corresponding to the sensitive field to a target value, wherein the target value is used to characterize that the sensitive field exists in the data to be desensitized.
[0132] Optionally, in the data desensitization apparatus provided in this application embodiment, the update submodule further includes: a determining unit, used to determine the bit corresponding to each sensitive field in the data to be desensitized from the initial bitmap; and an updating unit, used to update the value of the bit corresponding to the sensitive field to a target value, wherein the target value is used to characterize that the sensitive field exists in the data to be desensitized.
[0133] Optionally, in the data desensitization device provided in the embodiments of this application, the data desensitization device further includes at least one of the following: a second determining module, used to determine the data in the data storage request as data to be desensitized when a data storage request is detected; and a third determining module, used to determine the data to be recorded in the log as data to be desensitized during the log recording process.
[0134] It should be noted that the acquisition module 601, the first determination module 602, and the processing module 603 mentioned above correspond to steps S201 to S203 in Embodiment 1. The three modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and run in the computer terminal 10 provided in Embodiment 1.
[0135] Example 3
[0136] Embodiments of this application may provide an electronic device. Figure 7 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 7 As shown, the electronic device may include: one or more ( Figure 7 (Only one is shown) processor 1002, memory 1004, memory controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.
[0137] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the methods and apparatus in the embodiments of this application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the above-described methods. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
[0138] The processor can access information and applications stored in the memory via a transmission device to perform the following steps: acquiring data to be de-identified; identifying sensitive fields from the data to be de-identified, and determining the target bitmap corresponding to the data to be de-identified based on the sensitive fields, wherein different bits in the target bitmap correspond to different sensitive fields, and the target bitmap represents the sensitive fields contained in the data to be de-identified based on the bit values; determining the de-identification rules matching the target bitmap from the de-identification rule set, and de-identifying the data to be de-identified according to the de-identification rules to obtain the de-identified data, wherein the de-identification rule set includes de-identification rules matching different bitmaps.
[0139] The processor can also invoke information and applications stored in the memory via a transmission device to perform the following steps: The data desensitization method further includes one of the following: calculating a target value based on a target bitmap, mapping the target value to a set of desensitization rules, and determining that the desensitization rule corresponding to the target value is a desensitization rule matching the target bitmap; calculating a target value based on a target bitmap, performing a modulo operation on the target value, mapping the modulo result to a set of desensitization rules, and determining that the desensitization rule corresponding to the modulo result is a desensitization rule matching the target bitmap; calculating a target value based on a target bitmap, performing a hash operation on the target value, mapping the hash result to a set of desensitization rules, and determining that the desensitization rule corresponding to the hash result is a desensitization rule matching the target bitmap.
[0140] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: identify multiple fields from the data to be de-identified; for each field, determine whether the field is included in the preset sensitive field set; if the field is included in the sensitive field set, identify the field as a sensitive field.
[0141] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: determine an initial bitmap according to a preset set of sensitive fields, wherein the number of sensitive fields in the set of sensitive fields is equal to the number of bits in the initial bitmap; update the initial bitmap based on the sensitive fields contained in the data to be desensitized to obtain the target bitmap.
[0142] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: for each sensitive field in the data to be de-identified, determine the bit corresponding to the sensitive field from the initial bit map; update the value of the bit corresponding to the sensitive field to the target value, wherein the target value is used to characterize that the sensitive field exists in the data to be de-identified.
[0143] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: for each de-identification sub-rule, determine the sensitive field corresponding to the de-identification sub-rule from the data to be de-identified; and perform de-identification processing on the field value of the sensitive field corresponding to the de-identification sub-rule based on the de-identification sub-rule.
[0144] The processor can also invoke information and applications stored in the memory via the transmission device to perform the following steps: when a data storage request is detected, the data in the data storage request is identified as data to be de-identified; during the logging process, the data to be logged is identified as data to be de-identified.
[0145] In this embodiment, by identifying sensitive fields from the data to be anonymized and determining the target bitmap corresponding to the data based on these sensitive fields, the combination of sensitive fields involved in the data to be anonymized is accurately represented using a bitmap. By matching anonymization rules in the anonymization rule set based on the target bitmap, corresponding anonymization measures can be taken according to different scenarios and needs. That is, different anonymization methods can be adopted for different combinations of sensitive fields that may appear in the data to be anonymized, thereby improving the flexibility and accuracy of data anonymization.
[0146] Therefore, the method provided in this application achieves the goal of using different desensitization methods for different combinations of sensitive fields involved in the data to be desensitized, realizes the technical effect of improving the flexibility of data desensitization, and solves the technical problem of low flexibility of data desensitization in related technologies.
[0147] Those skilled in the art will understand that Figure 7 The structure shown is for illustrative purposes only. Electronic devices can also be smartphones, tablets, handheld computers, mobile internet devices (MIDs), PADs, and other terminal devices. Figure 7 This does not limit the structure of the aforementioned electronic device. For example, electronic devices may also include components that are more... Figure 7 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 7 The different configurations shown.
[0148] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.
[0149] Example 4
[0150] Embodiments of this application also provide a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the data desensitization method provided in Embodiment 1.
[0151] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.
[0152] This application also provides a computer program product that, when executed on a data processing device, is suitable for performing data desensitization method steps.
[0153] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.
[0154] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.
[0155] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of units or modules may be electrical or other forms.
[0156] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.
[0157] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0158] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.
[0159] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.
Claims
1. A data anonymization method, characterized in that, include: Obtain the data to be anonymized; Sensitive fields are identified from the data to be de-identified, and a target bitmap corresponding to the data to be de-identified is determined based on the sensitive fields. Different bits in the target bitmap correspond to different sensitive fields, and the target bitmap represents the sensitive fields contained in the data to be de-identified based on the bit values. The desensitization rule matching the target bitmap is determined from the desensitization rule set, and the data to be desensitized is desensitized according to the desensitization rule to obtain the desensitized data. The desensitization rule set includes desensitization rules matching different bitmaps.
2. The method according to claim 1, characterized in that, The desensitization rule for matching the target bitmap is determined from the set of desensitization rules, including one of the following: The target value is calculated based on the target bitmap, and the target value is mapped to the desensitization rule set. The desensitization rule corresponding to the target value is determined to be the desensitization rule matching the target bitmap. The target value is calculated based on the target bitmap, the target value is subjected to a modulo operation, the modulo result is mapped to the desensitization rule set, and the desensitization rule corresponding to the modulo result is determined to be the desensitization rule matching the target bitmap. The target value is calculated based on the target bitmap, a hash operation is performed on the target value, the hash result is mapped to the desensitization rule set, and the desensitization rule corresponding to the hash result is determined to be the desensitization rule matching the target bitmap.
3. The method according to claim 1, characterized in that, Identify sensitive fields from the data to be anonymized, including: Multiple fields were identified from the data to be de-identified; For each field, determine whether the field is included in the preset set of sensitive fields; If the field is included in the set of sensitive fields, then the field is identified as the sensitive field.
4. The method according to claim 1, characterized in that, Determining the target bitmap corresponding to the data to be de-identified based on the sensitive fields includes: An initial bitmap is determined based on a preset set of sensitive fields, wherein the number of sensitive fields in the set of sensitive fields is equal to the number of bits in the initial bitmap; Based on the sensitive fields contained in the data to be de-identified, the initial bitmap is updated to obtain the target bitmap.
5. The method according to claim 4, characterized in that, Based on the sensitive fields contained in the data to be de-identified, the initial bitmap is updated, including: For each sensitive field in the data to be de-identified, determine the bit corresponding to that sensitive field from the initial bitmap; The value of the bit corresponding to the sensitive field is updated to the target value, wherein the target value is used to indicate that the sensitive field exists in the data to be de-identified.
6. The method according to claim 1, characterized in that, The de-identification rules for target bitmap matching include multiple de-identification sub-rules, wherein de-identifying the data to be de-identified according to the de-identification rules includes: For each de-identification sub-rule, the sensitive field corresponding to the de-identification sub-rule is determined from the data to be de-identified; Based on the aforementioned desensitization sub-rule, the field values of the sensitive fields corresponding to the desensitization sub-rule are desensitized.
7. The method according to claim 1, characterized in that, Obtain the data to be anonymized, including at least one of the following: Upon detecting a data storage request, the data in the data storage request is identified as the data to be de-identified. During the logging process, the data to be logged is identified as the data to be de-identified.
8. A data anonymization device, characterized in that, include: The acquisition module is used to acquire the data to be de-identified. The first determining module is used to identify sensitive fields from the data to be de-identified, and determine the target bitmap corresponding to the data to be de-identified based on the sensitive fields, wherein different bits in the target bitmap correspond to different sensitive fields, and the target bitmap characterizes the sensitive fields contained in the data to be de-identified based on the value of the bits; The processing module is used to determine the desensitization rule matching the target bitmap from the desensitization rule set, and desensitize the data to be desensitized according to the desensitization rule to obtain the desensitized data. The desensitization rule set includes desensitization rules matching different bitmaps.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device containing the computer-readable storage medium to perform the data desensitization method according to any one of claims 1 to 7.
10. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program executes the data desensitization method according to any one of claims 1 to 7 when it runs.