Data processing method and device based on query field

Abstract

The present application provides a data processing method and device based on a query field, which relates to the field of data processing technology and solves the technical problem of low data security for special field queries. The method includes: obtaining operation fingerprint data corresponding to the query operation for a specified field through an ultrasonic fingerprint recognition device, and obtaining operation pressing data corresponding to the query operation through a pressing force sensor; determining the actual proportion of the number of operation fingerprints that meet the fingerprint data of a specified user in all the operation fingerprint data corresponding to the mouse and multiple keyboards in all the operation fingerprint data, and judging whether the actual proportion is greater than a preset proportion threshold; analyzing the first operation habit data of the operator corresponding to the query operation according to the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area, and judging whether the first operation habit data meets the second operation habit data corresponding to the specified user.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method and device for data processing based on a query field. Background Art

[0002] For the massive amount of information collected from social media, news websites and other platforms, which is usually stored in the database of the information data platform, managers can currently query the content of these databases by querying fields. By querying fields, managers can selectively retrieve data in the table without having to obtain the entire table content. By using query fields reasonably, managers can efficiently retrieve the required data and improve query efficiency. For example, by specifying query fields, users can obtain the content of specific columns in the table, or use some conditions and restrictions to filter the required data. Managers can also sort, group and aggregate the query field content to better meet the query needs of managers. In the process of many field queries, many special fields with a high degree of confidentiality will be encountered. For these special fields, only some managers have the authority to query. However, the existing data security for queries on these special fields is low. Summary of the invention

[0003] The purpose of the present invention is to provide a data processing method and device based on query fields to solve the technical problem of low data security for special field queries.

[0004] In a first aspect, an embodiment of the present application provides a data processing method based on a query field, which is applied to a computer device, wherein an ultrasonic fingerprint recognition device and a pressure sensor are provided on a keyboard and a mouse in the computer device; the method comprises:

[0005] Acquire operation fingerprint data corresponding to the query operation for the specified field through the ultrasonic fingerprint recognition device, and acquire operation pressing data corresponding to the query operation through the pressing force sensor; wherein the operation pressing data includes a first pressing force, a first pressing duration, a first pressing frequency, and a first pressing contact area of ​​a key;

[0006] Determine the actual proportion of the number of operation fingerprints that match the designated user fingerprint data in all the operation fingerprint data corresponding to the mouse and the plurality of keyboards, and judge whether the actual proportion is greater than a preset proportion threshold; wherein the designated user fingerprint data is fingerprint data corresponding to the designated user who has the query permission for the designated field;

[0007] analyzing the first operation habit data of the operator corresponding to the query operation according to the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area, and determining whether the first operation habit data is consistent with the second operation habit data corresponding to the designated user;

[0008] If the actual proportion is greater than the preset proportion threshold, and the first operation habit data matches the second operation habit data, it is determined that the operator corresponding to the query operation has the query permission for the specified field;

[0009] If the actual proportion is less than or equal to the preset proportion threshold, or the first operation habit data does not conform to the second operation habit data, it is determined that the operator corresponding to the query operation does not have the query authority for the specified field, and an early warning process is performed.

[0010] In a possible implementation, after determining that the operator corresponding to the query operation has the query permission for the specified field if the actual proportion is greater than the preset proportion threshold and the first operation habit data matches the second operation habit data, the method further includes:

[0011] If at least one of the following situations exists, it is determined that the operator with query authority has queried the specified field in an abnormal state, and an early warning is performed:

[0012] The key operation rhythm formed by the combination of the first pressing duration and the first pressing frequency in the first operation habit data conforms to the preset warning signal operation rhythm; the number of key tappings in the first operation habit data where the first pressing force is greater than the preset force threshold exceeds the first preset number; the number of key operations in the first operation habit data where the first pressing duration is greater than the preset duration threshold exceeds the second preset number; the number of key operations in the first operation habit data where the first pressing frequency is greater than the preset frequency threshold exceeds the third preset number; the number of key operations in the first operation habit data where the first pressing contact area is greater than the preset area threshold exceeds the fourth preset number.

[0013] In a possible implementation, the determining whether the first operating habit data matches the second operating habit data corresponding to the designated user includes:

[0014] Acquire a second pressing force, a second pressing duration, a second pressing frequency, and a second pressing contact area of ​​each designated user performing a key operation on the computer device;

[0015] Analyzing and learning the second operation habit data of each of the designated users through AI based on the second pressing force, the second pressing duration, the second pressing frequency, and the second pressing contact area;

[0016] It is determined whether the first operation habit data matches the second operation habit data corresponding to the designated user.

[0017] In a possible implementation, the computer device is provided with a designated dedicated headset, and the designated dedicated headset is provided with a liveness detection device; after determining that the operator corresponding to the query operation has the query permission of the designated field if the actual proportion is greater than the preset proportion threshold and the first operation habit data matches the second operation habit data, the method further includes:

[0018] Detecting whether the person wearing the designated dedicated earphone matches the designated user through a liveness detection device; if the person wearing the designated dedicated earphone matches the designated user, obtaining a designated field query result according to the query operation on the designated field, and playing only the text portion of the designated field query result through the designated dedicated earphone;

[0019] For the image part in the query result of the specified field, the image part is converted into text description content for the image part through the language AI model, and the specified dedicated headset is controlled to play the text description content.

[0020] In a possible implementation, after detecting by a liveness detection device whether the person wearing the designated dedicated headset meets the designated user, the method further includes:

[0021] If the person wearing the designated dedicated headset matches the designated user, the body temperature and heart rate of the current person wearing the designated dedicated headset are detected by the liveness detection device;

[0022] Determine whether the body temperature and the heart rate exceed the preset normal body condition value range. If the body temperature and the heart rate exceed the preset normal body condition value range, determine that the current person is in an abnormal state, and control the designated dedicated headset to stop playing the field query result.

[0023] In a possible implementation, the designated dedicated earphone is further provided with an ambient volume detection device; and the method further includes:

[0024] In the process of playing the query result of the designated field by the designated dedicated earphone, detecting the ambient volume of the designated dedicated earphone by the ambient volume detection device;

[0025] The playback volume of the designated dedicated earphones is automatically adjusted according to the noise conditions corresponding to the ambient volume, so as to increase the playback volume of the designated dedicated earphones when the ambient volume is greater than a preset volume threshold, and reduce the playback volume of the designated dedicated earphones when the ambient volume is less than or equal to the preset volume threshold.

[0026] In a possible implementation, a language AI model is provided in the computer device; and the method further includes:

[0027] Conducting a dialogue with the current operator of the computer device through the AI ​​dialogue module corresponding to the language AI model, and determining the data that the current operator needs to query according to the dialogue content;

[0028] Determine a data query result according to the data to be queried, and filter the data related to the specified field in the data query result based on the specified field to obtain a first data result after excluding the data related to the specified field and a filtered second data result related to the specified field;

[0029] Based on the second data result, content simplification processing is performed by the language AI model, so that the simplified data of the second data result has no association relationship with the designated field;

[0030] The first data result and the brief data are merged and processed through the language AI model, and the final data content after the merging and processing is played.

[0031] In one possible implementation, the method further includes:

[0032] Obtain the query operation for the specified field;

[0033] Detecting whether at least one of the following conditions exists during the input process of the query statement of the query operation, and determining that the operator corresponding to the query operation inputs the query statement in an abnormal state if at least one of the following conditions exists during the input process of the query statement:

[0034] The number of times the query statement has been modified is greater than the specified number, the number of repeated contents with the same semantics in the query statement is greater than the preset number, the query statement does not comply with the specified sentence fluency rules, the query statement does not comply with the specified sentence grammar, the query statement input stop time is greater than the specified time, and the query statement's idiom habits or idiom habits are inconsistent with the operator's historical idiom habits or historical idiom habits.

[0035] In a second aspect, a data processing device based on a query field is provided, which is applied to a computer device, wherein an ultrasonic fingerprint recognition device and a pressure sensor are provided on a keyboard and a mouse of the computer device; the device comprises:

[0036] an acquisition module, configured to acquire operation fingerprint data corresponding to a query operation on a specified field through the ultrasonic fingerprint recognition device, and acquire operation pressing data corresponding to the query operation through the pressing force sensor; wherein the operation pressing data includes a first pressing force, a first pressing duration, a first pressing frequency, and a first pressing contact area of ​​a key;

[0037] A judgment module, used to determine the actual proportion of the number of operation fingerprints that match the designated user fingerprint data in all the operation fingerprint data corresponding to the mouse and the plurality of keyboards, and to judge whether the actual proportion is greater than a preset proportion threshold; wherein the designated user fingerprint data is fingerprint data corresponding to the designated user who has the query authority for the designated field;

[0038] an analysis module, configured to analyze first operation habit data of an operator corresponding to the query operation according to the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area, and determine whether the first operation habit data is consistent with second operation habit data corresponding to the designated user;

[0039] A first determination module, configured to determine that the operator corresponding to the query operation has query authority for the specified field if the actual proportion is greater than the preset proportion threshold and the first operation habit data matches the second operation habit data;

[0040] The second determination module is used to determine that the operator corresponding to the query operation does not have the query authority for the specified field and perform early warning processing if the actual proportion is less than or equal to the preset proportion threshold, or the first operation habit data does not conform to the second operation habit data.

[0041] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program that can be executed on the processor, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0042] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to execute the method described in the first aspect above.

[0043] The embodiments of the present application bring the following beneficial effects:

[0044] The embodiment of the present application provides a data processing method and device based on query fields, which can obtain operation fingerprint data corresponding to the query operation for a specified field through the ultrasonic fingerprint recognition device, and obtain operation pressing data corresponding to the query operation through the pressing force sensor; wherein the operation pressing data includes a first pressing force, a first pressing duration, a first pressing frequency, and a first pressing contact area of ​​a key; determine the actual proportion of the number of operation fingerprints that conform to the designated user fingerprint data in all the operation fingerprint data corresponding to the mouse and the plurality of keyboards, and determine whether the actual proportion is greater than a preset proportion threshold; wherein the designated user fingerprint data is the designated user corresponding to the designated user with the query permission for the specified field. pattern data; analyzing the first operation habit data of the operator corresponding to the query operation according to the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area, and judging whether the first operation habit data is consistent with the second operation habit data corresponding to the designated user; if the actual proportion is greater than the preset proportion threshold, and the first operation habit data is consistent with the second operation habit data, then determining that the operator corresponding to the query operation has the query permission for the designated field; if the actual proportion is less than or equal to the preset proportion threshold, or the first operation habit data does not conform to the second operation habit data, then determining that the operator corresponding to the query operation does not have the query permission for the designated field, and performing early warning processing. In this scheme, through fingerprint recognition, pressure strength recognition, pressing duration recognition, pressing frequency recognition, and pressing contact area recognition during the user field query operation, it is possible to more accurately determine whether the current operation habit data conforms to the operation habit data of the specified user. Moreover, only when the number of operation fingerprints that conform to the fingerprint data of the specified user actually accounts for a large proportion of the total operation fingerprint data and conforms to the operation habit data of the specified user, it is determined that the current operation user has the query authority. This can avoid the situation where a small number of individual operations affect the determination of user authority due to special circumstances such as environmental influences or recognition errors. Moreover, the above-mentioned precise recognition of the user's operation habit data can improve the accuracy of judging abnormal operation behaviors of business personnel in querying fields, and can identify situations where authorized operators query special data fields under abnormal circumstances, thereby enhancing the system's sensitivity to special data queries, improving the data security of queries on these special designated fields, and solving the technical problem of low data security for queries on special fields.

[0045] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 A flowchart of a data processing method based on a query field provided in an embodiment of the present application;

[0048] Figure 2 Another schematic diagram of a flow chart of a data processing method based on a query field provided in an embodiment of the present application;

[0049] Figure 3 A schematic diagram of the structure of a data processing device based on a query field provided in an embodiment of the present application;

[0050] Figure 4 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution of the present application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on 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 the present application.

[0052] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0053] The massive amount of information collected by platforms such as social media and news websites is usually stored in the database of the information data platform. Currently, managers can query the content of these databases by querying fields. In the process of querying many fields, many special fields with high confidentiality will be encountered. For these special fields, only some managers have the authority to query. However, the existing data security of querying these special fields is low.

[0054] Based on this, an embodiment of the present application provides a data processing method and device based on a query field, through which the technical problem of low data security for special field queries can be solved. The method is applied to a database management system.

[0055] The embodiments of the present invention are further described below in conjunction with the accompanying drawings.

[0056] Figure 1 A flowchart of a data processing method based on a query field provided in an embodiment of the present application. The method is applied to a computer device, and an ultrasonic fingerprint recognition device and a pressure sensor are provided on the keyboard and mouse of the computer device. Figure 1 As shown, the method includes:

[0057] Step S110: acquiring operation fingerprint data corresponding to the query operation on the designated field through an ultrasonic fingerprint recognition device, and acquiring operation pressure data corresponding to the query operation through a pressure sensor.

[0058] The operation pressing data includes a first pressing force, a first pressing duration, a first pressing frequency, and a first pressing contact area of ​​the key.

[0059] In the process of querying fields by decryption, the decryption method can be fingerprint unlocking. For example, fingerprints are recognized by ultrasonic method to determine whether to decrypt, and ultrasonic fingerprint recognition devices are set on the pressing point of each button on the mouse (palmprint recognition and fingerprint recognition) and keyboard to ensure that the operator of the computer querying the field has the query authority of the special data field to avoid computer theft.

[0060] As a possible implementation, when a user queries a special data field by decryption, further analysis is performed, which may be analysis of the "query special data field" or analysis of the query content authority of the query personnel. Exemplarily, the above decryption method may also be other decryption methods. For encryption and decryption, for example, loop each byte for encryption and decryption, single-byte encryption through inputStream.read, inputStream.read returns a byte of content, which can be directly XOR-encrypted; single-byte decryption through inputStream.read. For another example, load the entire file for encryption and decryption, load the entire file through inputStream.read(bytes), inputStream.read(bytes) returns bytes of bytes size, puts them into bytes array, and encrypts them by XOR-loop; load the entire file through inputStream.read(bytes) for decryption. For another example, load a small array for file encryption and decryption, load the entire file through inputStream.read(b), inputStream.read(b) returns bytes of b size, puts them into b array, and encrypts them by XOR-loop; load the entire file through inputStream.read(b) for decryption.

[0061] Step S120, determining the actual proportion of the number of operation fingerprints that match the fingerprint data of the designated user in all the operation fingerprint data corresponding to the mouse and the multiple keyboards in all the operation fingerprint data, and judging whether the actual proportion is greater than a preset proportion threshold.

[0062] The designated user fingerprint data is the fingerprint data corresponding to the designated user who has the query authority for the designated field.

[0063] Exemplarily, the fingerprint recognition results correspond to a preset ratio threshold (preset proportion threshold) such as 70%. If 80% (greater than 70%) of the comprehensive fingerprint recognition results on all buttons match the specified fingerprint with special data field query permission, it is determined that the current operator has the special data field query permission; if 60% (less than 70%) of the comprehensive fingerprint recognition results on all buttons match the specified fingerprint, it is determined that the current operator does not have the special data field query permission, and an early warning can be issued when the operator queries the special data field.

[0064] As an optional implementation, a process can be constructed to determine the actual proportion of the number of operation fingerprints that match the specified user fingerprint data in the total operation fingerprint data. R , and determine whether the actual proportion is greater than the preset proportion threshold θ : First, determine all operation fingerprint data: merge the operation fingerprint data of the mouse and keyboard to obtain the set of all operation fingerprint dataT , T = M ∪ K ,in, M Represents a collection of mouse operation fingerprint data. K Represents a collection of keyboard operation fingerprint data. T Represents the set of all operation fingerprint data. Then, determine the number of operation fingerprints that match the specified user fingerprint data: find the number of operation fingerprints that match the specified user fingerprint data in all operation fingerprint data. U The number of matching operation fingerprints S , S =|{ t ∈ T ∣ t : U}∣, where U Indicates the fingerprint data of the specified user. t Indicates operation fingerprint data; S Indicates the number of operation fingerprints that match the specified user fingerprint data, | | indicates the cardinality of the set (i.e. the number of elements), t:U Indicates operation fingerprint data t With the specified user fingerprint data U Then, calculate the actual proportion: calculate the number of operation fingerprints that match the specified user fingerprint data S Fingerprint data in all operations T The actual proportion of R , R =S / | T ∣. Finally, determine whether the actual proportion is greater than the preset proportion threshold: compare the actual proportion R Compared with the preset ratio threshold θ, R > θ. It should be noted that R Indicates the actual proportion; θ Indicates the preset percentage threshold.

[0065] Combining the above steps, we can construct a complete formula to express this process:

[0066] R =|{ t ∈ T t : U}∣ / ∣ T ∣. Then, we can judge R Is it greater than the preset percentage threshold? θ : Result = True, if R > θ; orResult = False, otherwise. This formula simply and intuitively expresses how to determine the actual proportion of the number of operation fingerprints that match the fingerprint data of the specified user in the total operation fingerprint data based on the operation fingerprint data of the mouse and keyboard, and determine whether the actual proportion is greater than the preset proportion threshold.

[0067] Step S130, analyzing the first operation habit data of the operator corresponding to the query operation according to the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area, and determining whether the first operation habit data conforms to the second operation habit data corresponding to the specified user.

[0068] In an optional embodiment, the above process of determining whether the first operation habit data is consistent with the second operation habit data corresponding to the specified user may specifically include the following steps: obtaining the second pressing force, second pressing duration, second pressing frequency, and second pressing contact area of ​​each specified user's key operation on the computer device; based on the second pressing force, second pressing duration, second pressing frequency, and second pressing contact area, analyzing and learning the second operation habit data of each specified user through AI; determining whether the first operation habit data is consistent with the second operation habit data corresponding to the specified user.

[0069] In the embodiment of the present application, a force sensor is added to the button for force sensing. Based on the data such as the key pressing force, pressing duration, pressing frequency, pressing contact area, etc. collected by the force sensor, the operation habits of each designated operator are accurately learned through AI, and the key operation habits of each operator are analyzed. Data permissions can be determined based on the key operation habits, and an over-permission alarm can be issued. If the over-permission query is repeated multiple times within a certain period, an alarm will be issued upward. For the above-mentioned over-permission situation, for example, compared with the preset permissions, the over-permission does not meet the requirements.

[0070] In an optional implementation, a process may be constructed to determine the first operation habit data of the operator corresponding to the query operation. H 1, and determine whether it conforms to the second operation habit data corresponding to the specified user H 2: First, define the first operation habit data: use the given first pressing force P , First press duration D , First pressing frequency F and the first pressing contact area A To determine the first operation habit data H 1, H 1=( P , D , F , A). Then, define the second operation habit data: Assume that the second operation habit data of the specified user is known H 2 is a combination of a specific pressing force, pressing duration, pressing frequency and pressing contact area. Then, the similarity between the first operation habit data and the second operation habit data is calculated: a similarity function F is used to evaluate the first operation habit data H 1 and 2 operation habit data H 2. The similarity function can be defined according to the specific situation, for example, Euclidean distance or Manhattan distance can be used.

[0071] F( H 1, H 2)= ,or

[0072] F( H 1, H 2)= .

[0073] in, P 2, D 2, F 2, A 2 are the second operation habit data H 2. The pressing force, pressing duration, pressing frequency and pressing contact area.

[0074] Finally, it is determined whether the first operation habit data is consistent with the second operation habit data: if the value of the similarity function is less than or equal to a preset threshold, it is considered that the first operation habit data is consistent with the second operation habit data. H 1Complies with the second operation habit data H 2. F( H 1, H 2)≤ δ ;in, δ is a preset threshold.

[0075] In summary, a complete formula can be constructed to express this process:

[0076] Result= True, if F((P,D,F,A),(P2,D2,F2,A2))≤δ; or, Result=False, otherwise.

[0077] Wherein, P represents the first pressing force; D represents the first pressing duration; F represents the first pressing frequency; A represents the first pressing contact area; H 1 represents the first operation habit data, which is jointly determined by the first pressing force, the first pressing duration, the first pressing frequency and the first pressing contact area; H2 represents the second operation habit data of the specified user; F represents the similarity function used to compare the two operation habit data. It should be noted that, here, it is assumed that F uses the Euclidean distance as the similarity measurement method.

[0078] Step S140: If the actual proportion is greater than the preset proportion threshold, and the first operation habit data matches the second operation habit data, it is determined that the operator corresponding to the query operation has the query authority for the specified field.

[0079] In actual applications, if the current operation habit data such as the pressing force, pressing duration, pressing frequency, pressing area, etc. of the current key operation are consistent with the historical operation habit data of the corresponding designated operator of the computer, it is determined that the operator corresponding to the query operation has the query authority for the specified field.

[0080] For example, the fingerprint recognition result corresponds to a preset ratio threshold such as 50%. If 55% of the comprehensive fingerprint recognition results on all keys meet the specified fingerprint with special data field query permission, and the first operation habit data meets the second operation habit data, it is determined that the current operator has the special data field query permission.

[0081] For another example, if the current operation habit data does not match the historical operation habit data, but the fingerprint recognition matches the specified fingerprint of the specified operator, it is not certain whether the operator corresponding to the query operation has the query permission for the specified field, thereby preventing the operator from querying special data fields under abnormal conditions and improving the system's sensitivity to special data queries.

[0082] Step S150: If the actual proportion is less than or equal to the preset proportion threshold, or the first operation habit data does not conform to the second operation habit data, it is determined that the operator corresponding to the query operation does not have the query authority for the specified field, and an early warning process is performed.

[0083] As an example, if the current operation habit data of the current key operation, such as the pressing force, pressing duration, pressing frequency, pressing area, etc., does not conform to the historical operation habit data of the designated operator corresponding to the computer, an early warning is issued.

[0084] As another example, if the comprehensive fingerprint recognition results on all keys do not match the specified fingerprint, and / or the first operating habit data does not match the second operating habit data, it is determined that the current operator does not have the permission to query the special data field, and an alert is issued when he queries the special data field.

[0085] As another example, if the current operation habit data does not match the historical operation habit data, but the fingerprint recognition matches the designated fingerprint of the designated operator, an early warning is also issued to prevent the operator from querying special data fields under abnormal conditions, thereby improving the system's sensitivity to special data queries.

[0086] In the embodiment of the present application, through fingerprint recognition, pressure strength recognition, pressing duration recognition, pressing frequency recognition, and pressing contact area recognition during the user field query operation, it is possible to more accurately determine whether the current operating habit data conforms to the operating habit data of the specified user. Moreover, when the number of operating fingerprints that conform to the fingerprint data of the specified user actually accounts for a large proportion of the total operating fingerprint data and conforms to the operating habit data of the specified user, it is determined that the current operating user has the query authority. This can avoid the situation where a small number of individual operations affect the determination of user authority due to special circumstances such as environmental influences or recognition errors. Moreover, the above-mentioned precise recognition of the user's operating habit data can improve the accuracy of judging abnormal operating behaviors of business personnel in querying fields, and can identify situations where authorized operators query special data fields under abnormal circumstances, thereby enhancing the system's sensitivity to special data queries and improving the query security of special designated fields.

[0087] The above steps are described in detail below.

[0088] In some embodiments, after the above step S140, the method may further include the following steps: if at least one of the following situations exists, determining that an operator with query authority has queried a specified field in an abnormal state, and performing an early warning process:

[0089] The key operation rhythm formed by the combination of the first pressing duration and the first pressing frequency in the first operation habit data conforms to the preset warning signal operation rhythm; the number of key tappings in the first operation habit data where the first pressing force is greater than the preset force threshold exceeds the first preset number; the number of key operations in the first operation habit data where the first pressing duration is greater than the preset duration threshold exceeds the second preset number; the number of key operations in the first operation habit data where the first pressing frequency is greater than the preset frequency threshold exceeds the third preset number; the number of key operations in the first operation habit data where the first pressing contact area is greater than the preset area threshold exceeds the fourth preset number.

[0090] As an example, if the current key operation force is greater than the key operation habitual force threshold, a warning will be processed. If the operator queries a special field under an abnormal state, it can be possible to detect whether the force with which the operator taps the keyboard when entering the query for the special field is greater than a preset threshold (that is, the above-mentioned first pressing force is greater than the preset force threshold), and then a warning can be issued when it is identified that the number of key tapping exceeds the first preset number, thereby preventing the operator from querying special data fields under abnormal circumstances.

[0091] As another example, if the above-mentioned current operation habit data meets the specified warning operation habit data, for example, the length of the pressing time of multiple consecutive pressing operations (current operation habit data) meets the code or identifier (specified warning operation habit data) of the preset warning signal (preset warning signal operation rhythm), but the fingerprint recognition meets the specified fingerprint of the specified operator, then a warning is issued to prevent the operator from querying special data fields under abnormal circumstances, thereby improving the system's sensitivity to special field queries and further improving the data security of special field queries.

[0092] In some embodiments, a designated dedicated headset is provided on the computer device, and a liveness detection device is provided on the designated dedicated headset; after the above step S140, the method may further include the following steps:

[0093] Detecting whether the person wearing the designated dedicated earphones is a designated user through a liveness detection device; if the person wearing the designated dedicated earphones is a designated user, obtaining a designated field query result according to a query operation on the designated field, and playing only the text portion of the designated field query result through the designated dedicated earphones;

[0094] For the image part in the query result of the specified field, the image part is converted into text description content for the image part through the language AI model, and the specified dedicated headphones are controlled to play the text description content.

[0095] As an optional implementation, a special headset is plugged into the computer, and the operator uses the special headset to listen to the special data query results, which are not displayed on the computer screen to prevent leakage of the special data query results.

[0096] Exemplarily, the text portion of the special data query results can be played using dedicated headphones. For the image (picture, video) portion of the special data query results, AI can convert it into text content describing the image and control the dedicated headphones to play it.

[0097] In the embodiment of the present application, through the use of the above-mentioned special headphones, liveness detection device and language AI model, there is no need to display the queried special field content on the screen, which can prevent the special field content displayed on the screen from being stolen, and further improve the data security of special field queries.

[0098] In some embodiments, after the liveness detection device is used to detect whether the person wearing the designated dedicated headset meets the designated user, the method may further include the following steps:

[0099] If the person wearing the designated dedicated headset meets the designated user, the body temperature and heart rate of the current person wearing the designated dedicated headset are detected by the liveness detection device;

[0100] Determine whether the body temperature and heart rate exceed the preset normal body state value range. If the body temperature and heart rate exceed the preset normal body state value range, it is determined that the current person is in an abnormal state, and the designated dedicated headphones are controlled to stop playing the field query results.

[0101] In actual applications, the liveness detection device installed on the special headset can also perform human body status detection, such as body temperature, heart rate, etc., to prevent the playback of special data query results under abnormal conditions of the operator, thereby improving the confidentiality and security of data playback.

[0102] In some embodiments, the designated dedicated earphone is also provided with an ambient volume detection device; the method may further include the following steps:

[0103] In the process of playing the query result of the specified field by the specified dedicated earphone, detecting the ambient volume of the specified dedicated earphone by the ambient volume detection device;

[0104] Automatically adjust the playback volume of the designated dedicated headphones according to the noise conditions corresponding to the ambient volume, so as to increase the playback volume of the designated dedicated headphones when the ambient volume is greater than a preset volume threshold, and reduce the playback volume of the designated dedicated headphones when the ambient volume is less than or equal to the preset volume threshold.

[0105] As a possible implementation method, the dedicated earphones are also provided with an environmental volume detection device, which automatically adjusts the playback volume of the earphones according to the detected environmental noise. The earphones can automatically adjust the volume, and manual volume adjustment is not allowed, thereby preventing the queried special fields from being stolen, further improving the confidentiality and security of data playback in special fields.

[0106] In some embodiments, a language AI model is provided in the computer device; Figure 2 As shown, the method may also include the following steps:

[0107] Step S210, communicating with the current operator of the computer device through the AI ​​dialogue module corresponding to the language AI model, and determining the data that the current operator needs to query according to the content of the dialogue;

[0108] Step S220, determining a data query result according to the data to be queried, and filtering the data related to the specified field in the data query result based on the specified field, to obtain a first data result after excluding the data related to the specified field and a second data result related to the specified field after filtering;

[0109] Step S230, performing content simplification processing based on the second data result through the language AI model, so that the simplified summary data of the second data result has no association relationship with the specified field;

[0110] Step S240: merge the first data result and the brief data through the language AI model, and play the final data content after the merge.

[0111] In an embodiment of the present application, the operator can also conduct an AI dialogue with the computer, inform the AI ​​of the data that the operator needs to query, and the AI ​​only controls the computer to play or display non-special fields in the data query results, filter out special fields, or summarize and play only simplified content corresponding to special fields, and give brief answers to them, so as to perform more targeted confidentiality processing on the relevant content of special fields, and avoid affecting the operator's overall query results for normal data queries.

[0112] In some embodiments, the method may further include the following steps:

[0113] Get the query operation for the specified field; detect whether at least one of the following conditions exists during the input process of the query statement of the query operation. If at least one of the following conditions exists during the input process of the query statement, determine that the operator corresponding to the query operation enters the query statement in an abnormal state:

[0114] The number of modification times of the query statement is greater than the specified number, the number of repeated contents with the same semantics in the query statement is greater than the preset number, the query statement does not comply with the specified sentence fluency rules, the query statement does not comply with the specified sentence grammar, the stop input time of the query statement is greater than the specified time, and the idioms or idioms of the query statement are inconsistent with the historical idioms or idioms of the operator.

[0115] In the process of manually inputting query statements, check whether the statement stays for a long time or is repeatedly revised, check whether the statement is not smooth or violates the grammar to a large extent, check whether there are multiple words or sentences with the same semantics or repeated content, (first record and learn the idiomatic vocabulary or idiomatic grammar of the designated operator) check whether there is a situation that is obviously inconsistent with the idiomatic vocabulary or idiomatic grammar of the designated operator. If any of the above situations occurs, it is determined to be an abnormal situation, preventing authorized operators from querying special fields in abnormal states, thereby further improving the sensitivity to abnormal behavior in the query process of special fields.

[0116] Figure 3 A schematic diagram of a data processing device based on a query field is provided. The device can be applied to a computer device, wherein an ultrasonic fingerprint recognition device and a pressure sensor are provided on a keyboard and a mouse of the computer device. Figure 3 As shown, the data processing device 300 based on the query field includes:

[0117] The acquisition module 301 is used to acquire the operation fingerprint data corresponding to the query operation for the specified field through the ultrasonic fingerprint recognition device, and acquire the operation pressing data corresponding to the query operation through the pressing force sensor; wherein the operation pressing data includes the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area of ​​the key;

[0118] The judgment module 302 is used to determine the actual proportion of the number of operation fingerprints that match the designated user fingerprint data in all the operation fingerprint data corresponding to the mouse and the plurality of keyboards, and to judge whether the actual proportion is greater than a preset proportion threshold; wherein the designated user fingerprint data is fingerprint data corresponding to the designated user who has the query permission for the designated field;

[0119] An analysis module 303 is used to analyze the first operation habit data of the operator corresponding to the query operation according to the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area, and determine whether the first operation habit data is consistent with the second operation habit data corresponding to the designated user;

[0120] A first determination module 304 is configured to determine that the operator corresponding to the query operation has query authority for the specified field if the actual proportion is greater than the preset proportion threshold and the first operation habit data matches the second operation habit data;

[0121] The second determination module 305 is used to determine that the operator corresponding to the query operation does not have the query authority for the specified field, and perform early warning processing if the actual proportion is less than or equal to the preset proportion threshold, or the first operation habit data does not conform to the second operation habit data.

[0122] In some embodiments, the apparatus further comprises:

[0123] A third determination module is used for, after determining that the operator corresponding to the query operation has the query authority for the specified field if the actual proportion is greater than the preset proportion threshold and the first operation habit data conforms to the second operation habit data, determining that the operator with the query authority has the query authority for the specified field under abnormal conditions if at least one of the following conditions exists: the key operation rhythm formed by the combination of the first pressing duration and the first pressing frequency in the first operation habit data conforms to the preset warning signal operation rhythm; the number of key strokes in the first operation habit data where the first pressing force is greater than the preset force threshold exceeds the first preset number; the number of key operations in the first operation habit data where the first pressing duration is greater than the preset duration threshold exceeds the second preset number; the number of key operations in the first operation habit data where the first pressing frequency is greater than the preset frequency threshold exceeds the third preset number; the number of key operations in the first operation habit data where the first pressing contact area is greater than the preset area threshold exceeds the fourth preset number.

[0124] In some embodiments, the analysis module is specifically used to:

[0125] Acquire a second pressing force, a second pressing duration, a second pressing frequency, and a second pressing contact area of ​​each designated user performing a key operation on the computer device;

[0126] Analyzing and learning the second operation habit data of each of the designated users through AI based on the second pressing force, the second pressing duration, the second pressing frequency, and the second pressing contact area;

[0127] It is determined whether the first operation habit data matches the second operation habit data corresponding to the designated user.

[0128] In some embodiments, the computer device is provided with a designated dedicated headset, and the designated dedicated headset is provided with a liveness detection device; the device also includes a fifth determination module, which is used for: if the actual proportion is greater than the preset proportion threshold, and the first operation habit data conforms to the second operation habit data, then after determining that the operator corresponding to the query operation has the query authority for the designated field, detecting through the liveness detection device whether the person wearing the designated dedicated headset conforms to the designated user; if the person wearing the designated dedicated headset conforms to the designated user, obtaining the designated field query result according to the query operation for the designated field, and only playing the text part of the designated field query result through the designated dedicated headset; for the image part in the designated field query result, converting the image part into text description content for the image part through the language AI model, and controlling the designated dedicated headset to play the text description content.

[0129] In some embodiments, the device also includes a first detection module, which is used to: after detecting whether the person wearing the designated special headset meets the designated user through the liveness detection device, if the person wearing the designated special headset meets the designated user, detect the body temperature and heart rate of the current person wearing the designated special headset through the liveness detection device; determine whether the body temperature and the heart rate exceed the preset normal body state value range; if the body temperature and the heart rate exceed the preset normal body state value range, determine that the current person is in an abnormal state, and control the designated special headset to stop playing the field query result.

[0130] In some embodiments, the designated dedicated headset is also provided with an environmental volume detection device; the device also includes an adjustment module, which is used to: during the process of the designated dedicated headset playing the designated field query result, detect the ambient volume of the designated dedicated headset through the environmental volume detection device; automatically adjust the playback volume of the designated dedicated headset according to the noise situation corresponding to the ambient volume, so as to increase the playback volume of the designated dedicated headset when the ambient volume is greater than a preset volume threshold, and reduce the playback volume of the designated dedicated headset when the ambient volume is less than or equal to the preset volume threshold.

[0131] In some embodiments, a language AI model is provided in the computer device; the device also includes a screening module, which is used to: conduct a dialogue with the current operator of the computer device through the AI ​​dialogue module corresponding to the language AI model, and determine the data that the current operator needs to query based on the dialogue content; determine the data query result based on the data to be queried, and filter the data related to the specified field in the data query result based on the specified field to obtain a first data result after excluding the data related to the specified field and a second data result related to the specified field that is screened out; perform content simplification processing based on the second data result through the language AI model, so that the simplified data of the second data result has no correlation with the specified field; merge the first data result with the simplified data through the language AI model, and play the final data content after the merge.

[0132] In some embodiments, the device also includes a second detection module, which is used to: obtain the query operation for the specified field; detect whether there is at least one of the following situations during the input process of the query statement of the query operation, and if at least one of the following situations exists during the input process of the query statement, determine that the query operation corresponds to an operator who inputs the query statement in an abnormal state: the number of modifications to the query statement is greater than a specified number, the number of semantically identical repeated contents in the query statement is greater than a preset number, the query statement does not comply with the specified statement fluency rules, the query statement does not comply with the specified statement grammar, the query statement input stop time is greater than a specified time, and the query statement's idiom habits or idiom grammar habits are inconsistent with the operator's historical idiom vocabulary habits or historical idiom grammar habits.

[0133] The data processing device based on query fields provided in the embodiment of the present application has the same technical features as the data processing method based on query fields provided in the above-mentioned embodiment, so it can also solve the same technical problems and achieve the same technical effects.

[0134] An electronic device provided in an embodiment of the present application is Figure 4 As shown, the electronic device 400 includes a processor 402 and a memory 401, wherein the memory stores a computer program that can be run on the processor, and the processor implements the steps of the method provided in the above embodiment when executing the computer program.

[0135] See also Figure 4The electronic device further includes: a bus 403 and a communication interface 404, a processor 402, a communication interface 404 and a memory 401 are connected via the bus 403; the processor 402 is used to execute an executable module stored in the memory 401, such as a computer program.

[0136] The memory 401 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 404 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used.

[0137] The bus 403 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0138] Among them, the memory 401 is used to store programs, and the processor 402 executes the program after receiving the execution instruction. The method executed by the device defined by the process disclosed in any embodiment of the present application can be applied to the processor 402 or implemented by the processor 402.

[0139] The processor 402 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 402. The above processor 402 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor to execute, or the hardware and software modules in the decoding processor are combined to execute. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 401, and the processor 402 reads the information in the memory 401 and completes the steps of the above method in combination with its hardware.

[0140] Corresponding to the above-mentioned data processing method based on query fields, an embodiment of the present application also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to execute the steps of the above-mentioned data processing method based on query fields.

[0141] The data processing device based on the query field provided in the embodiment of the present application can be specific hardware on the device or software or firmware installed on the device. The device provided in the embodiment of the present application, its implementation principle and the technical effect produced are the same as those in the aforementioned method embodiment. For the sake of brief description, the parts not mentioned in the device embodiment can refer to the corresponding contents in the aforementioned method embodiment. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can all refer to the corresponding processes in the aforementioned method embodiment, and will not be repeated here.

[0142] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components 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 communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0143] For another example, the flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the device, method and computer program product according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of the boxes in the block diagram and / or the flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0144] 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 multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0145] In addition, each functional unit in the embodiments provided in 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.

[0146] If the function is implemented in the form of 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 the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the data processing method based on the query field described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store program codes.

[0147] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description and are not to be understood as indicating or implying relative importance.

[0148] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solution of the present application, rather than to limit it. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the aforementioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solution recorded in the aforementioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solution deviate from the scope of the technical solution of the embodiment of the present application. They should all be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A data processing method based on a query field, characterized in that: Applied to computer equipment, the keyboard and mouse in the computer equipment are provided with an ultrasonic fingerprint recognition device and a pressure sensor; the method comprises: Acquire operation fingerprint data corresponding to the query operation for the specified field through the ultrasonic fingerprint recognition device, and acquire operation pressing data corresponding to the query operation through the pressing force sensor; wherein the operation pressing data includes a first pressing force, a first pressing duration, a first pressing frequency, and a first pressing contact area of ​​a key; Determine the actual proportion of the number of operation fingerprints that match the designated user fingerprint data in all the operation fingerprint data corresponding to the mouse and the plurality of keyboards, and judge whether the actual proportion is greater than a preset proportion threshold; wherein the designated user fingerprint data is fingerprint data corresponding to the designated user who has the query permission for the designated field; analyzing the first operation habit data of the operator corresponding to the query operation according to the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area, and determining whether the first operation habit data is consistent with the second operation habit data corresponding to the designated user; If the actual proportion is greater than the preset proportion threshold, and the first operation habit data matches the second operation habit data, it is determined that the operator corresponding to the query operation has the query permission for the specified field; If the actual proportion is less than or equal to the preset proportion threshold, or the first operation habit data does not conform to the second operation habit data, it is determined that the operator corresponding to the query operation does not have the query authority for the specified field, and an early warning process is performed.

2. The method according to claim 1, characterized in that After determining that the operator corresponding to the query operation has the query permission for the specified field if the actual proportion is greater than the preset proportion threshold and the first operation habit data matches the second operation habit data, the method further includes: If at least one of the following situations exists, it is determined that the operator with query authority has queried the specified field in an abnormal state, and an early warning is performed: The key operation rhythm formed by the combination of the first pressing duration and the first pressing frequency in the first operation habit data conforms to the preset warning signal operation rhythm; the number of key tappings in the first operation habit data where the first pressing force is greater than the preset force threshold exceeds the first preset number; the number of key operations in the first operation habit data where the first pressing duration is greater than the preset duration threshold exceeds the second preset number; the number of key operations in the first operation habit data where the first pressing frequency is greater than the preset frequency threshold exceeds the third preset number; the number of key operations in the first operation habit data where the first pressing contact area is greater than the preset area threshold exceeds the fourth preset number.

3. The method according to claim 1, characterized in that The determining whether the first operation habit data matches the second operation habit data corresponding to the designated user includes: Acquire a second pressing force, a second pressing duration, a second pressing frequency, and a second pressing contact area of ​​each designated user performing a key operation on the computer device; Analyzing and learning the second operation habit data of each of the designated users through AI based on the second pressing force, the second pressing duration, the second pressing frequency, and the second pressing contact area; It is determined whether the first operation habit data matches the second operation habit data corresponding to the designated user.

4. The method according to claim 1, characterized in that: The computer device is provided with a designated dedicated earphone, and the designated dedicated earphone is provided with a liveness detection device; after determining that the operator corresponding to the query operation has the query authority of the designated field if the actual proportion is greater than the preset proportion threshold and the first operation habit data matches the second operation habit data, the method further includes: Detecting whether the person wearing the designated dedicated earphone matches the designated user through a liveness detection device; if the person wearing the designated dedicated earphone matches the designated user, obtaining a designated field query result according to the query operation on the designated field, and playing only the text portion of the designated field query result through the designated dedicated earphone; For the image part in the query result of the specified field, the image part is converted into text description content for the image part through the language AI model, and the specified dedicated headset is controlled to play the text description content.

5. The method according to claim 4, characterized in that After the living body detection device is used to detect whether the person wearing the designated dedicated headset is the designated user, the method further includes: If the person wearing the designated dedicated headset matches the designated user, the body temperature and heart rate of the current person wearing the designated dedicated headset are detected by the liveness detection device; Determine whether the body temperature and the heart rate exceed the preset normal body condition value range. If the body temperature and the heart rate exceed the preset normal body condition value range, determine that the current person is in an abnormal state, and control the designated dedicated headset to stop playing the field query result.

6. The method according to claim 4, characterized in that The designated dedicated earphone is also provided with an environmental volume detection device; the method further comprises: In the process of playing the query result of the designated field by the designated dedicated earphone, detecting the ambient volume of the designated dedicated earphone by the ambient volume detection device; The playback volume of the designated dedicated earphones is automatically adjusted according to the noise conditions corresponding to the ambient volume, so as to increase the playback volume of the designated dedicated earphones when the ambient volume is greater than a preset volume threshold, and reduce the playback volume of the designated dedicated earphones when the ambient volume is less than or equal to the preset volume threshold.

7. The method according to claim 1, characterized in that The computer device is provided with a language AI model; the method further comprises: Conducting a dialogue with the current operator of the computer device through the AI ​​dialogue module corresponding to the language AI model, and determining the data that the current operator needs to query according to the dialogue content; Determine a data query result according to the data to be queried, and filter the data related to the specified field in the data query result based on the specified field to obtain a first data result after excluding the data related to the specified field and a filtered second data result related to the specified field; Based on the second data result, content simplification processing is performed by the language AI model, so that the simplified data of the second data result has no association relationship with the designated field; The first data result and the brief data are merged and processed through the language AI model, and the final data content after the merging and processing is played.

8. The method according to claim 1, characterized in that The method further comprises: Obtain the query operation for the specified field; Detecting whether at least one of the following conditions exists during the input process of the query statement of the query operation, and determining that the operator corresponding to the query operation inputs the query statement in an abnormal state if at least one of the following conditions exists during the input process of the query statement: The number of times the query statement has been modified is greater than the specified number, the number of repeated contents with the same semantics in the query statement is greater than the preset number, the query statement does not comply with the specified sentence fluency rules, the query statement does not comply with the specified sentence grammar, the query statement input stop time is greater than the specified time, and the query statement's idiom habits or idiom habits are inconsistent with the operator's historical idiom habits or historical idiom habits.

9. A data processing device based on a query field, characterized in that: Applied to computer equipment, the keyboard and mouse in the computer equipment are provided with an ultrasonic fingerprint recognition device and a pressure sensor; the device comprises: an acquisition module, configured to acquire operation fingerprint data corresponding to a query operation on a specified field through the ultrasonic fingerprint recognition device, and acquire operation pressing data corresponding to the query operation through the pressing force sensor; wherein the operation pressing data includes a first pressing force, a first pressing duration, a first pressing frequency, and a first pressing contact area of ​​a key; A judgment module, used to determine the actual proportion of the number of operation fingerprints that match the designated user fingerprint data in all the operation fingerprint data corresponding to the mouse and the plurality of keyboards, and to judge whether the actual proportion is greater than a preset proportion threshold; wherein the designated user fingerprint data is fingerprint data corresponding to the designated user who has the query authority for the designated field; an analysis module, configured to analyze first operation habit data of an operator corresponding to the query operation according to the first pressing force, the first pressing duration, the first pressing frequency, and the first pressing contact area, and determine whether the first operation habit data is consistent with second operation habit data corresponding to the designated user; A first determination module, configured to determine that the operator corresponding to the query operation has query authority for the specified field if the actual proportion is greater than the preset proportion threshold and the first operation habit data matches the second operation habit data; The second determination module is used to determine that the operator corresponding to the query operation does not have the query authority for the specified field and perform early warning processing if the actual proportion is less than or equal to the preset proportion threshold, or the first operation habit data does not conform to the second operation habit data.

10. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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