CN117910031A

CN117910031A - Data query method and device, nonvolatile storage medium and electronic equipment

Info

Publication number: CN117910031A
Application number: CN202311776600.2A
Authority: CN
Inventors: 孙军芳; 李生帛; 苟晓侃; 张海宁; 李海龙; 王光辉; 宋继红; 李宝海; 张容福; 张广德; 王钰琳; 马进财; 马英辉; 雷晓萍; 赵云鹏; 李晓艳; 马静
Original assignee: State Grid Corp of China SGCC; State Grid Qinghai Electric Power Co Ltd; Information and Telecommunication Branch of State Grid Qinghai Electric Power Co Ltd
Current assignee: State Grid Corp of China SGCC; State Grid Qinghai Electric Power Co Ltd; Information and Telecommunication Branch of State Grid Qinghai Electric Power Co Ltd
Priority date: 2023-12-22
Filing date: 2023-12-22
Publication date: 2024-04-19

Abstract

The invention discloses a data query method and device, a nonvolatile storage medium and electronic equipment. Wherein the method comprises the following steps: acquiring a query request sent by a user terminal, wherein the query request carries at least one target field; determining a target query condition table of the target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions for querying the corresponding preset field in the internet platform, and the target query condition table comprises: target query conditions for querying a target field, and noise query conditions for querying a noise field; receiving a query result returned by the internet platform according to the target query condition table, wherein the query result comprises: target data corresponding to the target field, noise data corresponding to the noise data; and sending the target data to the user terminal. The invention solves the technical problem that the existing data query mode can not protect the privacy of the querier.

Description

Data query method and device, nonvolatile storage medium and electronic equipment

Technical Field

The present invention relates to the field of data processing, and in particular, to a data query method and apparatus, a nonvolatile storage medium, and an electronic device.

Background

With the increasing importance of data as important social production data, the discovery and the play of data value become an important direction of data mining. In the past, data mining usually focuses on the discovery and action exertion of a data holding body on the existing data value, and is limited by factors such as an information system, an internet technology and the like, large-scale data interaction and transaction cannot be realized, but with the development of modern information technology and the arrival of the mobile internet age, the production and circulation modes of data are revolutionarily changed, the exertion of the discovery and action of the data value focuses on the discovery and action exertion of the value among a plurality of data sources, and the present people focus on gathering multi-source heterogeneous data together, and further the data value is mined from higher data concept and hierarchy, so that the exertion of the data value and action truly enters into a data asset age, and each person serving as a producer and consumer of data in the data asset age is a red age while protecting personal privacy better, thereby forming a privacy protection problem.

The same problem exists for enterprise users, once the enterprise becomes an internet platform user, data is inevitably generated on a network trace through enterprise operation and production behaviors as the personal user, part of the data also belongs to private information for the enterprise, different business secrets are involved, the enterprise also can consider the economic benefit of the enterprise, the platform is not expected to use the data under a non-legal framework, and the platform is not expected to resell the data to other people.

Particularly, along with the establishment and operation of large internet platform companies, personal privacy information is continuously deposited into the large platforms, such as personal identification card numbers, mobile phone numbers, bank accounts, card numbers and the like, and the large platforms often rely on the advantages of convenience in self service, low price and complete service types, and take advantage of ecological niches in the process of acquiring personal traffic, so that users of each large platform can present hundred million-level or even hundred-billion-level scales. Personal privacy information deposited on these platforms reaches a level of days, is susceptible to unpredictable loss once hacked or compromised, and presents a number of potential hazards to the user himself.

Aiming at the threats, the large platform company is generally careful in providing the functions of user privacy information inquiry and the like, and needs to submit verification information for many times to ensure the validity of the inquirer and inquiry behaviors and reduce the inquiry time and information quantity of the privacy information as much as possible.

However, due to the hysteresis of the existing supervision framework and the privacy query technology, when the large platform provides the privacy information query, the validity of the querier and the query behavior may not be fully determined, so that the privacy information is illegally queried and revealed, and the risk in the privacy query is actively ignored and the user information is unnecessarily revealed due to the consideration of the commercial benefit.

Thus, existing regulatory frameworks and privacy query techniques suffer from the following drawbacks:

1) The content to be queried is often visible to the platform, and the risk of actively revealing relevant information in the query process of the platform cannot be avoided;

2) The inquirer cannot protect the inquiry logic of the inquirer, the inquiry logic belongs to the private information of the inquirer, and if the private information is disclosed to a platform or a third party, the private information cannot be effectively protected.

Aiming at the problem that the existing data query mode cannot protect the privacy of a querier, no effective solution is proposed at present.

Disclosure of Invention

The embodiment of the invention provides a data query method, a data query device, a nonvolatile storage medium and electronic equipment, which at least solve the technical problem that the privacy of a querier cannot be protected in the existing data query mode.

According to an aspect of an embodiment of the present invention, there is provided a data query method including: acquiring a query request sent by a user terminal, wherein the query request carries at least one target field; determining a target query condition table of the target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions, each preset query condition is used for querying a corresponding preset field in an internet platform, and the target query condition table comprises: target query conditions for querying the target field, and noise query conditions for querying a noise field, the preset fields including: the target field and the noise field, the target field and the noise field being different; receiving a query result returned by the internet platform according to the target query condition table, wherein a plurality of preset data are prestored in the internet platform, each preset data corresponds to the preset field, and the query result comprises: target data and noise data, wherein the target data is the preset data corresponding to the target field, and the noise data is the preset data corresponding to the noise data; and sending the target data to the user terminal.

Optionally, before determining the target query condition table of the target field according to a preset query condition table, the method further includes: acquiring a first login request of an Internet platform, wherein the first login request carries a login account and a login password; and under the condition that the login account and the login password pass verification, establishing communication with the Internet platform, and acquiring a preset query condition table of the Internet platform.

Optionally, obtaining the preset query condition table of the internet platform includes: receiving a preset field table of the internet platform, wherein the preset field table is used for recording a plurality of preset fields stored in the internet platform; calculating a hash value of each preset field through a hash algorithm, and determining a preset query condition corresponding to each preset field; and storing preset query conditions corresponding to the preset fields into the preset query condition table.

Optionally, obtaining the preset query condition table of the internet platform includes: and receiving the preset query condition table of the Internet platform, wherein the Internet platform calculates hash values of a plurality of preset fields in a preset field table through a hash algorithm to obtain the preset query condition table, the preset query condition table comprises a plurality of preset query conditions, and each preset query condition is the hash value of the corresponding preset field.

Optionally, obtaining the query request sent by the user terminal includes: acquiring a second login request of a user terminal, wherein the second login request carries identity information of the user terminal; authenticating the identity information; and receiving the inquiry request sent by the user terminal under the condition that the identity information passes the authentication.

Optionally, determining the target query condition table of the target field according to a preset query condition table includes: determining that a preset query condition corresponding to the target field is the target query condition in the preset query condition table; determining a noise query condition among a plurality of preset query conditions in the preset query condition table; and determining the target query condition table according to the target query condition and the noise query condition.

Optionally, determining the noise query condition among the plurality of preset query conditions in the preset query condition table includes: determining extraction points in the preset query condition table, wherein a plurality of preset query conditions in the preset query condition table are sequentially arranged; and sequentially acquiring a preset number of preset query conditions serving as the noise query conditions from the extraction points serving as starting points in the preset query condition table.

According to another aspect of the embodiment of the present invention, there is also provided a data query apparatus, including: the acquisition module is used for acquiring a query request sent by the user terminal, wherein the query request carries at least one target field; the determining module is configured to determine a target query condition table of the target field according to a preset query condition table, where the preset query condition table includes a plurality of preset query conditions, each of the preset query conditions is configured to query a corresponding preset field in an internet platform, and the target query condition table includes: target query conditions for querying the target field, and noise query conditions for querying a noise field, the preset fields including: the target field and the noise field, the target field and the noise field being different; the receiving module is configured to receive a query result returned by the internet platform according to the target query condition table, where the internet platform stores a plurality of preset data in advance, each preset data corresponds to the preset field, and the query result includes: target data and noise data, wherein the target data is the preset data corresponding to the target field, and the noise data is the preset data corresponding to the noise data; and the sending module is used for sending the target data to the user terminal.

According to another aspect of the embodiment of the present invention, there is further provided a nonvolatile storage medium, where the nonvolatile storage medium is configured to store a program, and when the program runs, control a device where the nonvolatile storage medium is located to execute any one of the data query methods described above.

According to another aspect of the embodiment of the present invention, there is also provided an electronic device, including: the system comprises a memory and a processor, wherein the processor is used for running a program stored in the processor, and the data query method is executed when the program runs.

In the embodiment of the invention, a query request sent by a user terminal is obtained, wherein the query request carries at least one target field; determining a target query condition table of a target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions, each preset query condition corresponds to a preset field stored in an internet platform, and the target query condition table comprises: the method comprises the steps that a target query condition corresponding to a target field and a noise query condition corresponding to a noise field are used, a preset field comprises a target field and a noise field, and the target field and the noise field are different; receiving a query result returned by the internet platform according to a preset query condition table, wherein the query result comprises: target data based on the target field query and noise data based on the noise field query; the target data is sent to the user terminal, so that the target field and the noise field can be provided for the Internet platform for inquiring in the process of inquiring the target data by the Internet platform, the aim of avoiding revealing the inquiring intention of the inquirer is achieved, the technical effect of privacy protection of the inquirer is achieved, and the technical problem that the privacy of the inquirer cannot be protected by the existing data inquiring mode is solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:

FIG. 1 is a flow chart of a data query method according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a privacy query flow based on a hashing algorithm in accordance with an embodiment of the present invention;

FIG. 3 is a schematic diagram of a data querying device according to an embodiment of the present invention;

Fig. 4 is a block diagram of a computer terminal according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

In accordance with an embodiment of the present invention, there is provided a data query method embodiment, it being noted that the steps shown in the flowchart of the figures may be performed 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 performed in an order other than that shown or described herein.

Fig. 1 is a flowchart of a data query method according to an embodiment of the present invention, as shown in fig. 1, the method includes the steps of:

step S102, acquiring a query request sent by a user terminal, wherein the query request carries at least one target field;

Step S104, determining a target query condition table of the target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions, each preset query condition is used for querying a corresponding preset field in the Internet platform, and the target query condition table comprises: target query conditions for querying a target field, and noise query conditions for querying a noise field, the preset fields including: a target field and a noise field, the target field and the noise field being different;

Step S106, receiving a query result returned by the Internet platform according to the target query condition table, wherein a plurality of preset data are stored in the Internet platform in advance, each preset data corresponds to a preset field, and the query result comprises: target data and noise data, wherein the target data is preset data corresponding to a target field, and the noise data is preset data corresponding to the noise data;

Step S108, the target data is sent to the user terminal.

Optionally, the data query method may be executed in a privacy query system, where the privacy query system is used to connect the user terminal and the internet platform, so that the privacy information querier may access the privacy query system through the user terminal to perform data query on the privacy information recorded in the internet platform.

In the step S102, the user terminal may be an intelligent terminal such as a mobile phone or a computer, and the privacy information inquirer may send an inquiry request to the privacy inquiry system through the user terminal.

In the step S102, the target field in the query request indicates that the user terminal requests to query the target data in the internet platform, and the privacy query system may determine the query condition of the target data according to the target field in the query request, so that the privacy query system may obtain the target data from the internet platform according to the target query condition.

In the step S104, the privacy query system may obtain the preset field corresponding to the preset data stored in the internet platform in advance, and use the preset field as the query condition corresponding to the preset data, and establish the preset query condition table, so that the preset query condition table may record the preset query conditions of the plurality of preset data.

In step S104, a plurality of preset data, which may be privacy information recorded by the internet platform, and a preset field corresponding to each preset data are stored in the internet platform in advance.

In the step S104, the privacy query system may record preset query conditions of a plurality of preset data through a preset query condition table, where each preset query condition is determined according to a preset field corresponding to each preset data, and further, in case of receiving a query request, the privacy query system may query a target query condition corresponding to a target field carried in the query request in the preset query condition table according to the target field, and query the target data in the internet platform according to the target query condition.

In step S104, the preset query condition table records the preset query conditions and the corresponding preset fields, and after determining the target query conditions corresponding to the target fields from the preset query condition table, the noise fields and the noise query conditions corresponding to the noise fields may be obtained from the preset query condition table.

In the step S104, the target query condition table includes both the target query condition and the noise query condition, the target data can be queried based on the target query condition, and the noise data can be queried based on the noise query condition, so that the target query condition is hidden through the noise query condition, the real query intention of the user terminal is prevented from being known by the internet platform, and the technical effect of privacy protection of the querier is realized.

In the step S106, the query result received by the privacy query system includes both the target data queried based on the target query condition and the noise data queried based on the noise query condition, but the query request of the user terminal only requests to acquire the target data of the target field, so that the privacy query system can separate the target data and the noise data, send the target data to the user terminal, and delete the noise data.

In step S106, the internet platform cannot distinguish the target query condition from the noise query condition in the target query condition table, and performs data query as the query condition to be queried, so that in the query process, the preset field recorded in the internet platform can be matched with the query condition to be queried, and the preset data corresponding to the matched preset field can be used as the query result based on the query condition to be queried.

As an alternative embodiment, before determining the target lookup condition table of the target field according to the preset lookup condition table, the method further includes: acquiring a first login request of an Internet platform, wherein the first login request carries a login account and a login password; under the condition that the login account and the login password pass verification, communication is established with the Internet platform, and a preset query condition table of the Internet platform is obtained.

According to the embodiment of the invention, the internet platform can acquire the connection authority for establishing communication connection with the privacy inquiring system through the login account and the login password, and further the internet platform can send a first login request carrying the login account and the login password to the privacy inquiring system, and establish communication between the privacy inquiring system and the internet platform under the condition that the login account and the login password in the first login request pass verification, so as to acquire a preset inquiring condition table of the internet platform.

It should be noted that, in the case of determining the preset query condition corresponding to each preset field, a hash value of each preset field may be calculated by a hash algorithm, and the hash value is used as a preset query price corresponding to the preset field to establish a preset query condition table.

It should be noted that the hashing algorithm: also known as a Hash function, a Hash function (also known as a digest algorithm) is a function that changes an input message string of arbitrary length into an output string of fixed length. This output string is called the hash value of the message. Typically for generating a message digest, key encryption, etc.

It should be noted that the characteristics of the hash algorithm include:

① The length of the calculated message digest is always fixed, no matter how long the incoming message is.

② The message digest appears to be "random". These bits appear to be hashed together in a messy way.

③ Generally, whenever an input message is different, the digest message generated after it is digested must also be different; but the same input must produce the same output.

④ The message digest function is a trapdoor-free one-way function, i.e., only forward message digests can be performed, but any message cannot be recovered from the digests, and even any information related to the original information cannot be found at all.

For example. MD5 (Message-Digest Algorithm 5) is a widely used cryptographic hash function that produces a 128-bit (16-byte) hash value (also known as a hash value) to ensure that the information transfer is completely consistent. The hash algorithm will generate a string of fixed length 128 bits (e 4b0190b2fadc0adbe54471ffd79a 729), also known as a hash value, which is essentially unique.

For example: the hash value (also referred to as hash value) of "MESSAGE DIGEST Algorithm" is: e4b0190b2fadc0adbe54471ffd a729.

As an alternative example, the following is MD5 calculation of this string "your good:

Inputting text: you are good.

Step 1: the input text is converted into a string of bytes.

Converting the input text "your good" into a string of bytes: 0x68 0x65 0x6C 0x6C 0x6F.

Step 2: hash computation is performed on the byte string.

The byte strings are hashed using the MD5 algorithm. The results obtained were: 0x23 0x8F 0x4A 0x9E 0x4D 0x32 0x45 0x8D 0xSB 0x28 0x43 0x4D 0x4E 0x3A 0x4B 0x3D.

Step 3: the hash result is converted into hexadecimal character strings.

Converting each byte of the hash result into hexadecimal, and obtaining a hexadecimal character string: 238F4A9E4D32458D5B28434D4E3A4B3D.

Step 4: and outputting a result.

The output MD5 calculation result is: 238F4A9E4D32458D5B28434D4E3A4B3D.

The SHA hash algorithm is a more secure hash algorithm that can convert any length of data into a fixed length hash value. The hash value length of the SHA algorithm may be 160 bits, 256 bits, 384 bits, or 512 bits, with SHA-256 and SHA-512 being the two most widely used algorithms.

According to the embodiment of the application, the hash value calculation is carried out on the data to be queried, then the hash value matching is carried out on the data of the data provider, and meanwhile, the content of the data queried by the querying user and the query behavior logic are protected by adding the confusion item data.

Optionally, the hash value of each preset field is calculated through a hash algorithm, and the process of determining the preset query condition corresponding to each preset field can be performed in a privacy query system or an internet platform.

As an alternative embodiment, obtaining the preset query condition table of the internet platform includes: receiving a preset field table of an internet platform, wherein the preset field table is used for recording a plurality of preset fields stored in the internet platform; calculating a hash value of each preset field through a hash algorithm, and determining a preset query condition corresponding to each preset field; and storing the preset query conditions corresponding to the preset fields into a preset query condition table.

According to the embodiment of the invention, the privacy query system can receive the preset field table of the Internet platform, hash algorithm calculation is carried out in the privacy query system, and the hash value of each preset field is used for completing construction of the preset query condition table.

As an alternative embodiment, obtaining the preset query condition table of the internet platform includes: and receiving a preset query condition table of the Internet platform, wherein the Internet platform calculates hash values of a plurality of preset fields in the preset field table through a hash algorithm to obtain the preset query condition table, and the preset query condition table comprises a plurality of preset query conditions, and each preset query condition is a hash value of a corresponding preset field.

According to the embodiment of the invention, the hash algorithm calculation can be performed in the Internet platform, the hash value of each preset field is used for completing the construction of the preset query condition table, and the constructed preset query condition table is sent to the privacy query system.

As an optional embodiment, obtaining the query request sent by the user terminal includes: acquiring a second login request of the user terminal, wherein the second login request carries identity information of the user terminal; authenticating the identity information; and receiving a query request sent by the user terminal under the condition that the identity information passes the authentication.

According to the embodiment of the invention, the user terminal can be an intelligent terminal such as a mobile phone, and the like, the portability of the scheme is considered, and the query object can use any user terminal to apply for access to the privacy query system; in order to ensure the security of the query process, under the condition that the query object accesses the privacy query system through the user terminal, the second login request sent by the user terminal can carry the identity information of the query object, the identity information is authenticated through the privacy query system, and then after the identity information of the user terminal passes the authentication, the privacy query system only receives the query request sent by the user terminal to query the target data.

Optionally, different privacy objects have different query rights, so in the process of authenticating identity information, the query rights corresponding to each identity information can be determined, and a query request sent by a user terminal using the identity information can be executed according to the query rights.

As an alternative embodiment, determining the target lookup condition table of the target field according to the preset lookup condition table includes: determining a preset query condition corresponding to the target field as a target query condition in a preset query condition table; determining a noise query condition among a plurality of preset query conditions in a preset query condition table; and determining a target query condition table according to the target query condition and the noise query condition.

According to the embodiment of the invention, after the target query condition is determined from the preset query condition table, the noise query condition can be obtained from the preset query condition table, and the target query condition can be hidden through the noise query condition, so that the technical effect of privacy protection of a querier is realized.

Alternatively, the noise query condition may be randomly selected in a preset query condition table.

As an alternative embodiment, determining the noise query condition among a plurality of preset query conditions of the preset query condition table includes: determining extraction points in a preset query condition table, wherein a plurality of preset query conditions in the preset query condition table are sequentially arranged; and sequentially acquiring a preset number of preset query conditions serving as noise query conditions from the extraction points serving as starting points in the preset query condition table.

In the above embodiment of the present invention, the preset query condition table stores a plurality of preset query conditions in a sequential arrangement, and when determining the noise query condition from the preset query condition table, the preset query condition of the extraction point may be determined as a starting point among the plurality of preset query conditions in the sequential arrangement, so as to obtain a preset number of noise query conditions, thereby implementing the determination of the noise query condition.

The application also provides an optional embodiment, which provides a privacy query system based on a hash algorithm, wherein the privacy query system can be an open platform based on distributed deployment, centralized deployment or cloud deployment and is divided into a system end and a client end, wherein the system end can be deployed to various internet platforms for inputting privacy information to be queried by the internet platforms, and the client end can be deployed to a personal mobile phone or a desktop computer of a user so as to conveniently use various privacy query functions provided by the privacy query system pointed by the application.

Optionally, the privacy query flow system based on the hash algorithm comprises: an internet platform P (e.g. an online mall) for providing private information, a private inquiring system S based on a hash algorithm, and a private information inquirer I.

Alternatively, the privacy information inquirer may be a user individual of an online mall or may be a regulatory agency.

Fig. 2 is a schematic diagram of a privacy query flow based on a hash algorithm according to an embodiment of the present invention, as shown in fig. 2, including the following steps:

s21, carrying out hash operation on all fields of the platform P.

Optionally, the internet platform P logs in to the privacy query system S through the system user account password, and calculates hash values corresponding to all fields of the internet platform P through a hash algorithm (for the hash algorithm, whether the hash algorithm is built in the privacy query system S or the hash algorithm is deployed at the internet platform P, and there is no difference), and since most fields exist in a key manner, the result after the hash operation can be replaced by a preset query condition table H-key, where H represents hash operation performed on the entire field table, and the preset query condition table H-key includes a plurality of preset query conditions.

S22, the H-key is stored.

Optionally, the preset query condition table H-key includes a plurality of preset query conditions.

Optionally, if the hash algorithm is deployed in the internet platform P, the internet platform P pushes the preset query condition table H-key to the privacy query system S, and if the hash algorithm is built in the privacy query system S, the privacy query system S may directly store the preset query condition table H-key for standby, and use it as a condition table for querying the privacy information.

S23, the inquirer logs in and authenticates.

Optionally, the querier I logs in the privacy query system S through the client, and the privacy query system S completes authentication of the identity thereof, so as to ensure compliance of the private information query main body, ensure that the query is completed in a compliance framework, including the queried private information, the queried logic and the like, and all meet relevant regulations.

S24, query condition generation.

Optionally, the privacy information querier I makes a query request to the privacy query system S, and the content includes the fields of the query, which must be consistent with the fields of the internet platform P, otherwise, invalid query is caused, or all returned values after query are null. The target query condition F may include a plurality of, and may be expressed as: f=f1 (key 1, key2, key3,.. The term.) wherein key represents each target field to be queried, i.e. target query condition, keyn represents the n-th target field to be queried.

Optionally, the value range of n is not greater than the number of preset field keys in the preset query condition table H-key, otherwise, an invalid query is formed.

S25, adding noise to the query condition.

Optionally, the privacy query system S selects, by a random method, an unequal number of noise query conditions keys from a preset query condition table H-key, and forms a noise query condition F ' as a complement of the target query condition F to form a target query condition table F-F ', so as to achieve the purpose of confusion of the target query condition F, so that no matter which deployment method is adopted, the internet platform P cannot determine the real target query condition F, the target query condition table F-F ' may be expressed as F-F ' =f2 (F, (rand (kernel)), where the query condition in the target query condition table is formed by superimposing noise F ' by F, and the noise needs to be extracted from the preset query condition table H-key by a random algorithm, where two parameters are set during extraction, namely, the extraction point key-point and the extraction number num (i.e., preset number) respectively, and the key-point represents the number of noise query conditions extracted from which point is the beginning.

It should be noted that, the number of extracted numbers num is not greater than the number of preset query condition keys after extracting the point key-point in the preset query condition table H-key.

Alternatively, if considering that the noise is too large and the transmission efficiency is easily reduced, the method may be limited by limiting the number of decimations num, if the condition num is set to be less than or equal to 3, it means that after the decimations, at most 3 noise query condition keys are selected, and the target query condition table F-F' may be modified as follows: F-F' =F2 (F, (rank-point, num:. Ltoreq.3)).

S26, inquiring condition issuing and privacy information uploading.

Optionally, the privacy query system S issues the target query condition table F-F ' to the internet platform P, and the internet platform P extracts the corresponding data set H-H ' (i.e., the query result) from the database and uploads the data set H-H ' to the privacy query system S.

It should be noted that, for the privacy query system S, the privacy information uploaded by the internet platform P is specified based on compliance requirements and related protocols, and the privacy query system S, serving as a privacy protection technology provider, is a neutral third party, and must meet compliance requirements of compliance on information transmitted by the internet platform P.

S27, private information pushing and noise data destroying are carried out.

Optionally, the privacy querying system S delivers the target data H to the privacy information querier I, which performs related information query, and destroys the noise data H'.

Alternatively, the private information querier I may only use the queried private information in the private query system S and must meet the related compliance requirements, but if the private information querier I is the owner of the private information of the internet platform, or the related supervisor, it is possible to obtain the private information data itself under the compliance framework.

As an alternative embodiment, the privacy query flow based on the hash algorithm includes the following steps:

in step S31, hash operation is performed on all the fields of the platform P.

Optionally, hash values corresponding to all keys of P are calculated by an MD5 hash algorithm.

For example: the result of the "Zhang San", calculated by the MD5 hash algorithm, is a hash value: 615DB57AA314529AAA0FBE95B3E95BD3. And (3) calculating all the data through an MD5 hash algorithm, and then establishing a table H-key of the original data and the hash value corresponding to the original data.

And step S32, the H-key is stored.

Alternatively, if the hash algorithm is deployed in P, the P pushes the table H-key of this hash value to the privacy query system S, and if the hash algorithm is built into S, S may directly store the H-key in reserve for use as a conditional table for privacy information query.

S33, the inquirer logs in and authenticates.

Optionally, the querier I logs in to S through the client, and the S completes authentication of the identity thereof, so as to ensure compliance of the private information querying body, ensure that the query is completed within a compliance framework, including the queried private information, the queried logic, and the like, and all conform to related regulations.

S34, query condition generation.

Optionally, the querier I makes a query request to S, the content including fields of the query such as { "Zhang san", "Li Si", "Wang Wu" }.

S35, adding noise to the query condition.

Optionally, the privacy querying system S picks an unequal number of keys from the H-keys as a complement to the F function by a random method.

For example, starting from the 5 th key (i.e., key-point=5) of the H-keys, 3 keys (i.e., num=3) are randomly selected using an average random algorithm: { "Zhao Liu", "Sun Qi", "Zhouba" } forms F-F' to-be-queried condition table, i.e., { "Zhang san", "Li Si", "Wang Wu", "Zhao Liu", "Sun Qi", "Zhouba" }, to achieve the purpose of confusing F, so that no matter which deployment method is adopted, P can not determine the true F. This process is implemented by equation (1).

The formula (1) is: F-F' =f2 (F, (rand (key-point, num))).

Obviously, the number of num must be less than the number of keys after the key-point extraction point.

Alternatively, if considering that noise is too large, which easily results in a decrease in transmission efficiency, the regulation may be performed by limiting num, if the condition num is set to be 3 or less, which means that after extracting points, at most 3 keys are selected as noise to be added to the query condition, the formula (1) may be deformed into the formula (2).

The formula (2) is: F-F' =F2 (F, (rank-point, num:. Ltoreq.3)).

S36, inquiring condition issuing and privacy information uploading.

Optionally, the privacy query system S issues the hash value {"615DB57AA314529AAA0FBE95B3E95BD3","36c942351ec9cc3ad124e288a5c9cf0b","3228f322c9c98a125554a24f875f0f7e","b43536d0468a4ab0ccc538b975623cd9","52a48bb45a786677e0f4fb28064c148f","0cf67fa426103e1c3aecdb93d91be7ab"} corresponding to the content F-F '{ "Zhang san", "Li Si", "Wang Wu", "Zhao Liu", "Sun Qi", "Zhou eight" } to the internet platform P, and P extracts the dataset {13312345678, 35, 123 … … } composed of the data in terms of the handset number or year or ammeter data corresponding to the' { "Zhang san", "Li Si", "Wang Wu", "Zhao Liu", "Sun Qi", "Zhou eight" }, and uploads to S, and it should be noted that, for S, the privacy information uploaded by P is specified based on compliance requirements and related protocols, and S is a neutral third party as to meet compliance requirements of compliance aspects on the information transferred by P.

S37, private information pushing and noise data destroying are carried out.

Optionally, the privacy querying system S delivers the datasets {13312345678, 35, 123, … … } corresponding to { "Zhang san", "Li four", "Wang five" }, to I, which performs related information query, and destroys the datasets {189987654328, 47, 879, … … } corresponding to { "Zhao Liu", "Sun Qi", "Zhou eight" }. In general, I is a querier, which may only use the queried privacy information in S and must meet the related compliance requirements, but if I is the owner of the privacy information of the internet platform, or the related supervisor, it is possible to obtain the privacy information data itself under the compliance framework.

Or for example: the internet platform P for providing the private information takes the online shopping platform as the internet platform P for providing the private information, and the individual user as the private information inquirer I.

Optionally, if the personal user I performs the query operation of the private data in the shopping internet platform P through the private query system S, the personal user needs to query the own purchase commodity record, which includes: purchased goods, date of purchase, time of purchase. The internet platform related data is subjected to random related supplementation, and the fields after supplementation comprise: purchased goods, purchase date, time, shipping address, purchaser, contact, shipping address. Thus, the user I submits the application f=f1 (commodity name, purchase date, purchase time).

According to the embodiment of the invention, the hash value calculation encryption is carried out on the privacy information field to be queried by using the hash algorithm, the noise is increased, and the content of the data queried by the querying user and the query behavior logic are protected by matching with the hash value of the data provider. Making it invisible to the internet platform that owns the original information.

It should be noted that, the private data query method provided by the application protects the privacy of both the query party and the data party, but not only protects the privacy of the data party.

In the embodiment of the invention, the output query content is encrypted by carrying out hash algorithm processing on the query content; comparing the plaintext with MD5 codes of different parts of the decrypted file, and sampling to check the consistency degree of all codes; and encrypting the query logic of the querier; the method and the device achieve the aim of encrypting and protecting the query content of the user, so that the query content is invisible to a platform or a third party, and the risk of actively revealing the related information in the query process by the platform is avoided, the technical effects of making the query logic privacy information of the querier invisible to the platform or the third party, and protecting the query logic privacy information of the querier are achieved, and the technical problems that the query content of the querier is visible to the platform, so that the risk of actively revealing the related information in the query process by the platform cannot be avoided, and the technical problems that the querier cannot protect the privacy information of the query logic part of the querier are solved.

According to the embodiment of the present invention, a data query device is further provided, and it should be noted that the data query device may be used to execute the data query method in the embodiment of the present invention, where the data query method in the embodiment of the present invention may be executed in the data query device.

FIG. 3 is a schematic diagram of a data query device according to an embodiment of the present invention, as shown in FIG. 3, the device may include: the obtaining module 32 is configured to obtain a query request sent by the user terminal, where the query request carries at least one target field; the determining module 34 is configured to determine a target query condition table of the target field according to a preset query condition table, where the preset query condition table includes a plurality of preset query conditions, and each preset query condition is used to query a corresponding preset field in the internet platform, and the target query condition table includes: target query conditions for querying a target field, and noise query conditions for querying a noise field, the preset fields including: a target field and a noise field, the target field and the noise field being different; the receiving module 36 is configured to receive a query result returned by the internet platform according to the target query condition table, where a plurality of preset data are pre-stored in the internet platform, each preset data corresponds to a preset field, and the query result includes: target data and noise data, wherein the target data is preset data corresponding to a target field, and the noise data is preset data corresponding to the noise data; a transmitting module 38, configured to transmit the target data to the user terminal.

It should be noted that, the acquiring module 32 in this embodiment may be used to perform step S102 in the embodiment of the present application, the determining module 34 in this embodiment may be used to perform step S104 in the embodiment of the present application, the receiving module 36 in this embodiment may be used to perform step S106 in the embodiment of the present application, and the transmitting module 38 in this embodiment may be used to perform step S108 in the embodiment of the present application. The above modules are the same as examples and application scenarios implemented by the corresponding steps, but are not limited to what is disclosed in the above embodiments.

As an alternative embodiment, the apparatus further comprises: the first acquisition sub-module is used for acquiring a first login request of the Internet platform before determining a target query condition table of a target field according to a preset query condition table, wherein the first login request carries a login account and a login password; and the second acquisition sub-module is used for establishing communication with the Internet platform under the condition that the login account and the login password pass verification, and acquiring a preset query condition table of the Internet platform.

As an alternative embodiment, the second acquisition sub-module includes: the first receiving unit is used for receiving a preset field table of the internet platform, wherein the preset field table is used for recording a plurality of preset fields stored in the internet platform; the first determining unit is used for calculating the hash value of each preset field through a hash algorithm and determining a preset query condition corresponding to each preset field; and the storage unit is used for storing the preset query conditions corresponding to the preset fields into a preset query condition table.

As an alternative embodiment, the second acquisition sub-module includes: the second receiving unit is used for receiving a preset query condition table of the internet platform, wherein the internet platform calculates hash values of a plurality of preset fields in the preset field table through a hash algorithm to obtain the preset query condition table, the preset query condition table comprises a plurality of preset query conditions, and each preset query condition is the hash value of the corresponding preset field.

As an alternative embodiment, the obtaining module includes: the acquisition unit is used for acquiring a second login request of the user terminal, wherein the second login request carries identity information of the user terminal; an authentication unit for authenticating the identity information; and the third receiving unit is used for receiving the inquiry request sent by the user terminal under the condition that the identity information passes the authentication.

As an alternative embodiment, the determining module includes: the second determining unit is used for determining that the preset query condition corresponding to the target field is the target query condition in the preset query condition table; a third determining unit, configured to determine a noise query condition among a plurality of preset query conditions in a preset query condition table; and the fourth determining unit is used for determining a target query condition table according to the target query condition and the noise query condition.

As an alternative embodiment, the third determining unit comprises: a first determining subunit, configured to determine an extraction point in a preset query condition table, where a plurality of preset query conditions in the preset query condition table are sequentially arranged; and the second determining subunit is used for sequentially acquiring a preset number of preset query conditions serving as noise query conditions from the extraction points serving as starting points in the preset query condition table.

Embodiments of the present invention may provide a computer terminal, which may be any one of a group of computer terminals. Alternatively, in the present embodiment, the above-described computer terminal may be replaced with a terminal device such as a mobile terminal.

Alternatively, in this embodiment, the above-mentioned computer terminal may be located in at least one network device among a plurality of network devices of the computer network.

In this embodiment, the computer terminal may execute the program code of the following steps in the data query method: acquiring a query request sent by a user terminal, wherein the query request carries at least one target field; determining a target query condition table of the target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions, each preset query condition is used for querying a corresponding preset field in an internet platform, and the target query condition table comprises: target query conditions for querying a target field, and noise query conditions for querying a noise field, the preset fields including: a target field and a noise field, the target field and the noise field being different; receiving a query result returned by the internet platform according to the target query condition table, wherein a plurality of preset data are stored in the internet platform in advance, each preset data corresponds to a preset field, and the query result comprises: target data and noise data, wherein the target data is preset data corresponding to a target field, and the noise data is preset data corresponding to the noise data; and sending the target data to the user terminal.

Alternatively, fig. 4 is a block diagram of a computer terminal according to an embodiment of the present invention. As shown in fig. 4, the computer terminal 40 may include: one or more (only one is shown) processors 42, and memory 44.

The memory may be used to store software programs and modules, such as program instructions/modules corresponding to the data query method and apparatus in the embodiments of the present invention, and the processor executes the software programs and modules stored in the memory, thereby executing various functional applications and data processing, that is, implementing the data query method described above. 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 examples, the memory may further include memory remotely located with respect to the processor, which may be connected to the terminal 40 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The processor may call the information and the application program stored in the memory through the transmission device to perform the following steps: acquiring a query request sent by a user terminal, wherein the query request carries at least one target field; determining a target query condition table of the target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions, each preset query condition is used for querying a corresponding preset field in an internet platform, and the target query condition table comprises: target query conditions for querying a target field, and noise query conditions for querying a noise field, the preset fields including: a target field and a noise field, the target field and the noise field being different; receiving a query result returned by the internet platform according to the target query condition table, wherein a plurality of preset data are stored in the internet platform in advance, each preset data corresponds to a preset field, and the query result comprises: target data and noise data, wherein the target data is preset data corresponding to a target field, and the noise data is preset data corresponding to the noise data; and sending the target data to the user terminal.

Optionally, the above processor may further execute program code for: before a target query condition table of a target field is determined according to a preset query condition table, a first login request of an Internet platform is obtained, wherein the first login request carries a login account and a login password; under the condition that the login account and the login password pass verification, communication is established with the Internet platform, and a preset query condition table of the Internet platform is obtained.

Optionally, the above processor may further execute program code for: receiving a preset field table of an internet platform, wherein the preset field table is used for recording a plurality of preset fields stored in the internet platform; calculating a hash value of each preset field through a hash algorithm, and determining a preset query condition corresponding to each preset field; and storing the preset query conditions corresponding to the preset fields into a preset query condition table.

Optionally, the above processor may further execute program code for: and receiving a preset query condition table of the Internet platform, wherein the Internet platform calculates hash values of a plurality of preset fields in the preset field table through a hash algorithm to obtain the preset query condition table, and the preset query condition table comprises a plurality of preset query conditions, and each preset query condition is a hash value of a corresponding preset field.

Optionally, the above processor may further execute program code for: acquiring a second login request of the user terminal, wherein the second login request carries identity information of the user terminal; authenticating the identity information; and receiving a query request sent by the user terminal under the condition that the identity information passes the authentication.

Optionally, the above processor may further execute program code for: determining a preset query condition corresponding to the target field as a target query condition in a preset query condition table; determining a noise query condition among a plurality of preset query conditions in a preset query condition table; and determining a target query condition table according to the target query condition and the noise query condition.

Optionally, the above processor may further execute program code for: determining extraction points in a preset query condition table, wherein a plurality of preset query conditions in the preset query condition table are sequentially arranged; and sequentially acquiring a preset number of preset query conditions serving as noise query conditions from the extraction points serving as starting points in the preset query condition table.

By adopting the embodiment of the invention, a scheme for inquiring data is provided. In the embodiment of the invention, a query request sent by a user terminal is obtained, wherein the query request carries at least one target field; determining a target query condition table of a target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions, each preset query condition corresponds to a preset field stored in an internet platform, and the target query condition table comprises: the method comprises the steps that a target query condition corresponding to a target field and a noise query condition corresponding to a noise field are used, a preset field comprises a target field and a noise field, and the target field and the noise field are different; receiving a query result returned by the internet platform according to a preset query condition table, wherein the query result comprises: target data based on the target field query and noise data based on the noise field query; the target data is sent to the user terminal, so that the target field and the noise field can be provided for the Internet platform for inquiring in the process of inquiring the target data by the Internet platform, the aim of avoiding revealing the inquiring intention of the inquirer is achieved, the technical effect of privacy protection of the inquirer is achieved, and the technical problem that the privacy of the inquirer cannot be protected by the existing data inquiring mode is solved.

It will be appreciated by those skilled in the art that the structure shown in fig. 4 is only illustrative, and the computer terminal may be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, a Mobile internet device (Mobile INTEMET DEVICES, MID), a PAD, etc. Fig. 4 is not limited to the structure of the electronic device. For example, the computer terminal 40 may also include more or fewer components (e.g., network interfaces, display devices, etc.) than shown in FIG. 4, or have a different configuration than shown in FIG. 4.

Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be implemented by a program for instructing a terminal device to execute on hardware associated with the terminal device, the program may be stored in a nonvolatile storage medium, and the nonvolatile storage medium may include: flash disk, read-only memory (ROM), random-access memory (Random Access Memory, RAM), magnetic disk or optical disk, etc.

Embodiments of the present invention also provide a nonvolatile storage medium. Alternatively, in this embodiment, the above-described nonvolatile storage medium may be used to store the program code executed by the data query method provided in the above-described embodiment.

Alternatively, in this embodiment, the above-mentioned nonvolatile storage medium may be located in any one of the computer terminals in the computer terminal group in the computer network, or in any one of the mobile terminals in the mobile terminal group.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: acquiring a query request sent by a user terminal, wherein the query request carries at least one target field; determining a target query condition table of the target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions, each preset query condition is used for querying a corresponding preset field in an internet platform, and the target query condition table comprises: target query conditions for querying a target field, and noise query conditions for querying a noise field, the preset fields including: a target field and a noise field, the target field and the noise field being different; receiving a query result returned by the internet platform according to the target query condition table, wherein a plurality of preset data are stored in the internet platform in advance, each preset data corresponds to a preset field, and the query result comprises: target data and noise data, wherein the target data is preset data corresponding to a target field, and the noise data is preset data corresponding to the noise data; and sending the target data to the user terminal.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: before a target query condition table of a target field is determined according to a preset query condition table, a first login request of an Internet platform is obtained, wherein the first login request carries a login account and a login password; under the condition that the login account and the login password pass verification, communication is established with the Internet platform, and a preset query condition table of the Internet platform is obtained.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: receiving a preset field table of an internet platform, wherein the preset field table is used for recording a plurality of preset fields stored in the internet platform; calculating a hash value of each preset field through a hash algorithm, and determining a preset query condition corresponding to each preset field; and storing the preset query conditions corresponding to the preset fields into a preset query condition table.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: and receiving a preset query condition table of the Internet platform, wherein the Internet platform calculates hash values of a plurality of preset fields in the preset field table through a hash algorithm to obtain the preset query condition table, and the preset query condition table comprises a plurality of preset query conditions, and each preset query condition is a hash value of a corresponding preset field.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: acquiring a second login request of the user terminal, wherein the second login request carries identity information of the user terminal; authenticating the identity information; and receiving a query request sent by the user terminal under the condition that the identity information passes the authentication.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: determining a preset query condition corresponding to the target field as a target query condition in a preset query condition table; determining a noise query condition among a plurality of preset query conditions in a preset query condition table; and determining a target query condition table according to the target query condition and the noise query condition.

Optionally, in the present embodiment, the non-volatile storage medium is arranged to store program code for performing the steps of: determining extraction points in a preset query condition table, wherein a plurality of preset query conditions in the preset query condition table are sequentially arranged; and sequentially acquiring a preset number of preset query conditions serving as noise query conditions from the extraction points serving as starting points in the preset query condition table.

The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.

In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed technology may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a non-volatile storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a non-volatile storage medium, including instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned nonvolatile storage medium includes: a usb disk, a read-only memory (ROM), a random access memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.

Claims

1. A method of querying data, comprising:

Acquiring a query request sent by a user terminal, wherein the query request carries at least one target field;

Determining a target query condition table of the target field according to a preset query condition table, wherein the preset query condition table comprises a plurality of preset query conditions, each preset query condition is used for querying a corresponding preset field in an internet platform, and the target query condition table comprises: target query conditions for querying the target field, and noise query conditions for querying a noise field, the preset fields including: the target field and the noise field, the target field and the noise field being different;

Receiving a query result returned by the internet platform according to the target query condition table, wherein a plurality of preset data are prestored in the internet platform, each preset data corresponds to the preset field, and the query result comprises: target data and noise data, wherein the target data is the preset data corresponding to the target field, and the noise data is the preset data corresponding to the noise data;

And sending the target data to the user terminal.

2. The method of claim 1, wherein prior to determining the target lookup condition table for the target field based on a preset lookup condition table, the method further comprises:

Acquiring a first login request of an Internet platform, wherein the first login request carries a login account and a login password;

And under the condition that the login account and the login password pass verification, establishing communication with the Internet platform, and acquiring a preset query condition table of the Internet platform.

3. The method of claim 2, wherein obtaining the preset lookup condition table of the internet platform comprises:

Receiving a preset field table of the internet platform, wherein the preset field table is used for recording a plurality of preset fields stored in the internet platform;

calculating a hash value of each preset field through a hash algorithm, and determining a preset query condition corresponding to each preset field;

and storing preset query conditions corresponding to the preset fields into the preset query condition table.

4. The method of claim 2, wherein obtaining the preset lookup condition table of the internet platform comprises:

And receiving the preset query condition table of the Internet platform, wherein the Internet platform calculates hash values of a plurality of preset fields in a preset field table through a hash algorithm to obtain the preset query condition table, the preset query condition table comprises a plurality of preset query conditions, and each preset query condition is the hash value of the corresponding preset field.

5. The method of claim 1, wherein obtaining the query request sent by the user terminal comprises:

Acquiring a second login request of a user terminal, wherein the second login request carries identity information of the user terminal;

Authenticating the identity information;

and receiving the inquiry request sent by the user terminal under the condition that the identity information passes the authentication.

6. The method of claim 1, wherein determining the target lookup condition table for the target field based on a preset lookup condition table comprises:

Determining that a preset query condition corresponding to the target field is the target query condition in the preset query condition table;

determining a noise query condition among a plurality of preset query conditions in the preset query condition table;

and determining the target query condition table according to the target query condition and the noise query condition.

7. The method of claim 6, wherein determining a noise query condition among a plurality of the preset query conditions of the preset query condition table comprises:

Determining extraction points in the preset query condition table, wherein a plurality of preset query conditions in the preset query condition table are sequentially arranged;

And sequentially acquiring a preset number of preset query conditions serving as the noise query conditions from the extraction points serving as starting points in the preset query condition table.

8. A data query device, comprising:

The acquisition module is used for acquiring a query request sent by the user terminal, wherein the query request carries at least one target field;

The determining module is configured to determine a target query condition table of the target field according to a preset query condition table, where the preset query condition table includes a plurality of preset query conditions, each of the preset query conditions is configured to query a corresponding preset field in an internet platform, and the target query condition table includes: target query conditions for querying the target field, and noise query conditions for querying a noise field, the preset fields including: the target field and the noise field, the target field and the noise field being different;

The receiving module is configured to receive a query result returned by the internet platform according to the target query condition table, where the internet platform stores a plurality of preset data in advance, each preset data corresponds to the preset field, and the query result includes: target data and noise data, wherein the target data is the preset data corresponding to the target field, and the noise data is the preset data corresponding to the noise data;

And the sending module is used for sending the target data to the user terminal.

9. A non-volatile storage medium for storing a program, wherein the program, when executed, controls a device in which the non-volatile storage medium is located to perform the data query method of any one of claims 1 to 7.

10. An electronic device, comprising: a memory and a processor for executing a program stored in the processor, wherein the program is executed to perform the data query method of any one of claims 1 to 7.