Data processing method, device, equipment, medium and program product

Abstract

The embodiments of the present disclosure provide a data processing method, apparatus, device, storage medium and program product for a first participant, and relate to the field of information security. The method comprises: receiving a query request sent by a querying party; if the query request is a first type of query request, encrypting the second target data using a first type of encryption algorithm to obtain the first target data; if the query request is a second type of query request, encrypting the third target data using a second type of encryption algorithm to obtain the first target data; and sending the first target data so that the querying party uses the first target data for data processing. The embodiments of the present disclosure can improve computing performance by determining different types of query requests and using encryption algorithms of corresponding types in a targeted manner. The embodiments of the present disclosure also provide data processing methods, apparatuses, devices, storage media and program products for the querying party and the second participant, respectively.

Description

Technical Field

[0001] The present disclosure relates to the field of information security, and more specifically, to a data processing method, apparatus, device, medium, and program product. Background Art

[0002] Individual institutions may have limited data sources and are often unable to share their data due to commercial confidentiality and privacy concerns. Multi-party secure computing technology can encrypt data sources from multiple participants and perform collaborative computing to achieve the desired result.

[0003] In the process of realizing the concept of the present disclosure, the inventors discovered that there are at least the following problems in the prior art: during the multi-party secure computation process, each participant will have to wait for a long time to obtain the final result, and the computing performance is low. Summary of the Invention

[0004] In view of the above problems, the present disclosure provides a data processing method, apparatus, device, medium and program product for improving the performance of multi-party secure computing.

[0005] One aspect of an embodiment of the present disclosure provides a data processing method based on multi-party secure computing for a first participant, comprising: receiving a query request sent by a querying party, wherein the query request is used to obtain first target data provided by the first participant; if the query request is a first-type query request, encrypting the second target data using a first-type encryption algorithm to obtain the first target data; if the query request is a second-type query request, encrypting the third target data using a second-type encryption algorithm to obtain the first target data, wherein the second target data and the third target data have different data ranges, and the encryption methods of the first-type encryption algorithm and the second-type encryption algorithm are different; and sending the first target data so that the querying party uses the first target data for data processing.

[0006] Another aspect of an embodiment of the present disclosure provides a data processing method based on multi-party secure computing for a querying party, including: in response to a user's query operation, determining the query type of the query operation; if the query type is a first type of operation, sending a first type of query request to a first participant, wherein the first type of query request includes a first type of encryption algorithm; if the query type is a second type of operation, sending a second type of query request to the first participant, wherein the second type of query request includes a second type of encryption algorithm, the first type of query request and the second type of query request are used to obtain target data of different ranges, and the encryption methods of the first type of encryption algorithm and the second type of encryption algorithm are different; obtaining first target data provided by the first participant for data processing, wherein the first participant is used to obtain the first target data using the first type of encryption algorithm or the second type of encryption algorithm.

[0007] Another aspect of an embodiment of the present disclosure provides a data processing method based on multi-party secure computing for a second participant, comprising: receiving a data processing instruction sent by a first participant, wherein the data processing instruction includes first target data and a third type of encryption algorithm; encrypting fifth target data using the third type of encryption algorithm; obtaining fourth target data based on the first target data and the encrypted fifth target data; sending the fourth target data so that the inquiring party performs data processing using the fourth target data; wherein the first participant is configured to: in response to the inquiring party's query request, encrypt local data using the third type of encryption algorithm to obtain the first target data.

[0008] Another aspect of an embodiment of the present disclosure provides a data processing device based on multi-party secure computing for a first participant, including: a first receiving module, used to receive a query request sent by a querying party, wherein the query request is used to obtain first target data provided by the first participant; a first encryption module, used to encrypt second target data using a first type of encryption algorithm to obtain the first target data if the query request is a first type of query request; a second encryption module, used to encrypt third target data using a second type of encryption algorithm to obtain the first target data if the query request is a second type of query request, wherein the second target data and the third target data have different data ranges, and the encryption methods of the first type of encryption algorithm and the second type of encryption algorithm are different; a first sending module, used to send the first target data so that the querying party uses the first target data for data processing.

[0009] Another aspect of an embodiment of the present disclosure provides a data processing device based on multi-party secure computing for a querying party, including: a type determination module, for determining the query type of the query operation in response to a user's query operation; a second sending module, for sending a first type of query request to a first participant if the query type is a first type of operation, wherein the first type of query request includes a first type of encryption algorithm; a third sending module, for sending a second type of query request to the first participant if the query type is a second type of operation, wherein the second type of query request includes a second type of encryption algorithm, the first type of query request and the second type of query request are used to obtain target data of different ranges, and the encryption methods of the first type of encryption algorithm and the second type of encryption algorithm are different; a second acquisition module, for acquiring first target data provided by the first participant for data processing, wherein the first participant is used to obtain the first target data using the first type of encryption algorithm or the second type of encryption algorithm.

[0010] Another aspect of an embodiment of the present disclosure provides a data processing device based on multi-party secure computing for a second participant, including: a second receiving module, used to receive a data processing instruction sent by a first participant, wherein the data processing instruction includes first target data and a third type of encryption algorithm; a third encryption module, used to encrypt fifth target data using the third type of encryption algorithm; a data calculation module, used to obtain fourth target data based on the first target data and the encrypted fifth target data; a fourth sending module, used to send the fourth target data so that the inquiring party uses the fourth target data for data processing; wherein the first participant is configured to: respond to the query request of the inquiring party, encrypt the local data using the third type of encryption algorithm to obtain the first target data.

[0011] Another aspect of an embodiment of the present disclosure provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the method described above.

[0012] Another aspect of the embodiments of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method described above.

[0013] Another aspect of the embodiments of the present disclosure further provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0014] One or more of the above embodiments have the following beneficial effects:

[0015] By identifying different types of query requests and using the corresponding encryption algorithm, computing performance is improved. For example, if the second target data in a first-type query request has a different data range than the third target data in a second-type query request, the different encryption methods of the first and second-type encryption algorithms can be used to process the corresponding data range, achieving higher computing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0017] Figure 1 Schematically illustrates an application scenario diagram of a data processing method based on multi-party secure computing according to an embodiment of the present disclosure;

[0018] Figure 2 The following schematically shows a flow chart of a data processing method for a querying party according to an embodiment of the present disclosure;

[0019] Figure 3 Schematically shows a flow chart of a data processing method for a first participant according to an embodiment of the present disclosure;

[0020] Figure 4 Schematically shows a flow chart of a data processing method for a first participant according to another embodiment of the present disclosure;

[0021] Figure 5 Schematically shows a flow chart of a data processing method for a second participant according to an embodiment of the present disclosure;

[0022] Figure 6 The following schematically shows a structural block diagram of a data processing device for a first participant according to an embodiment of the present disclosure;

[0023] Figure 7 The structure block diagram of the data processing device for the second participant according to an embodiment of the present disclosure is schematically shown;

[0024] Figure 8 The following schematically shows a structural block diagram of a data processing device for a querying party according to an embodiment of the present disclosure;

[0025] Figure 9 Schematically shows a structural block diagram of a query client module according to an embodiment of the present disclosure;

[0026] Figure 10 Schematically shows a structural block diagram of a statistical query module according to an embodiment of the present disclosure;

[0027] Figure 11Schematically shows a structural block diagram of a common query module according to an embodiment of the present disclosure;

[0028] Figure 12 Schematically shows a structural block diagram of a credit risk calculation module according to an embodiment of the present disclosure;

[0029] Figure 13 The following schematically illustrates an operation flow chart of a data processing device for a querying party according to an embodiment of the present disclosure;

[0030] Figure 14 The block diagram schematically shows an electronic device suitable for implementing the data processing method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0031] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the detailed description below, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0032] The distinguishing feature of multi-party secure computation is that multiple participants can collaboratively compute a specified function using their respective ciphertext data as input. This computation process eliminates the need for decryption to restore the plaintext data, resulting in a trustless implementation of hardware, software, and individuals involved. Even if one or more parties are attacked, multi-party computation technology can still ensure that these inputs are not leaked and that the computation results are correct.

[0033] Multi-party secure computation technology can be used in scenarios involving multiple data sources, such as joint query and statistical analysis, personal privacy protection, obtaining training and input data for AI models, and information storage. For example, in traditional credit risk assessment in the financial industry, each financial institution independently uses its own customer data for credit risk analysis. However, each institution's data is limited and cannot be shared due to commercial confidentiality, laws and regulations, and customer privacy restrictions, making it impossible to comprehensively and reliably assess customer credit risk. Multi-party secure computation technology can be used to build a comprehensive credit risk assessment system that fully utilizes shared data from authoritative institutions such as governments, banks, and insurance companies, thereby reducing systemic financial risk.

[0034] While implementing the concepts of this disclosure, the inventors discovered that when acquiring data from various participants, each participant, regardless of the type of query or the scope of the plaintext data being queried, typically uses a fixed encryption algorithm to obtain ciphertext data. Due to the complex computational process of this encryption algorithm, the process of encrypting local plaintext data and ultimately obtaining the results of this multi-party secure computation is time-consuming and inefficient.

[0035] The embodiments of the present disclosure provide a data processing method based on multi-party secure computation. This method improves computing performance by identifying different types of query requests and using corresponding encryption algorithms. For example, if the second target data queried by a first type of query request has a different data range than the third target data queried by a second type of query request, higher computing performance can be achieved by processing the corresponding data ranges based on the different encryption methods of the first and second types of encryption algorithms.

[0036] In the technical solution disclosed herein, the collection, storage, use, processing, transmission, provision, disclosure and application of data of all participants or individual users involved comply with the provisions of relevant laws and regulations, take necessary confidentiality measures, and do not violate public order and good morals.

[0037] Figure 1 The application scenario diagram of the data processing method based on multi-party secure computing according to an embodiment of the present disclosure is schematically shown.

[0038] like Figure 1 As shown, the multi-party secure computing system 100 according to this embodiment may include a first server 101, a second server 102, a third server 103, a fourth server 104, and a network 105. The network 105 is used as a medium for providing communication links between the servers. The network 105 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0039] According to an embodiment of the present disclosure, the first server 101, the second server 102, the third server 103, and the fourth server 104 can form a centralized network or a point-to-point (P2P) network for communication. For example, building a system in a decentralized manner can enable the relative independence of the subsystems of the participating parties, thereby improving the high availability of the entire system. The first server 101, the second server 102, the third server 103, and the fourth server 104 can be the four participants in the multi-party secure computing system 100. Each participant can act as a query party to obtain data from other participants. Each participant participates in the multi-party secure computing as a data source providing local data.

[0040] Users can use terminal devices to interact with the first server 101, the second server 102, the third server 103, and the fourth server 104 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0041] The terminal device may be any electronic device that has a display screen and supports web browsing, including but not limited to a smart phone, a tablet computer, a laptop computer, a desktop computer, and the like.

[0042] The first server 101, the second server 102, the third server 103, and the fourth server 104 may be servers that provide various services, such as a backend management server that supports websites browsed by users using terminal devices (for example only). The backend management server may analyze and process received data such as user requests, and feed back the processing results (e.g., web pages, information, or data obtained or generated based on user requests) to the terminal device.

[0043] It should be understood that Figure 1 The number of networks and servers in the embodiment is only for illustration. Any number of networks and servers may be provided as required.

[0044] The following will be based on Figure 1 The scene described by Figures 2 to 5 The data processing method of the embodiment of the present disclosure is described in detail.

[0045] Figure 2 The flowchart of the data processing method for the querying party according to an embodiment of the present disclosure is schematically shown.

[0046] like Figure 2 As shown, the data processing method for the querying party of this embodiment includes operations S210 to S240.

[0047] In operation S210 , in response to a query operation by a user, a query type of the query operation is determined.

[0048] Illustratively, a query operation can be an operation in which a user retrieves local data from the querying party, as well as local data from other participating parties. The query type can be determined based on the scope of the data retrieved by the user. Alternatively, the user can be provided with different types of options to select from, in which case the type is determined based on the user's selection.

[0049] In operation S220, if the query type is a first type of operation, a first type of query request is sent to the first party, wherein the first type of query request includes a first type of encryption algorithm.

[0050] In operation S230, if the query type is a second type of operation, a second type of query request is sent to the first participant, wherein the second type of query request includes a second type of encryption algorithm, the first type of query request and the second type of query request are used to obtain target data in different ranges, and the encryption methods of the first type of encryption algorithm and the second type of encryption algorithm are different.

[0051] For example, the first type of operation may be a statistical query operation, and the first type of query request may be a statistical query request. Statistical queries refer to queries for statistically aggregated data. For example, in credit risk assessment, borrowers may be divided into several groups and their respective recurring loan amounts and default probabilities calculated. The second type of operation may be a general query operation, and the second type of query request may be a general query request. General queries refer to queries for data that does not require statistical aggregation, such as the borrower's highest daily consumption record over the past year, whether there is any overdue payment record over the past year, etc.

[0052] Statistical query requests and ordinary query requests retrieve different data ranges. Statistical queries can retrieve batches of source data for processing. Ordinary queries retrieve individual source data for processing.

[0053] For example, the first type of encryption algorithm may include differential privacy algorithms. Differential privacy primarily uses random noise to ensure that the results of querying publicly visible information do not leak an individual's private information. This provides a method for maximizing the accuracy of data queries while minimizing the chance of identifying records. Simply put, it removes individual features while retaining statistical features to protect user privacy. The second type of encryption algorithm may include algorithms such as obfuscated circuits, homomorphic encryption, secret sharing, and oblivious transfer.

[0054] The primary implementation mechanism for differential privacy is to add randomized noise to the input or output, such as Laplace noise, Gaussian noise, and exponential noise. Algorithms such as obfuscated circuits, homomorphic encryption, secret sharing, and oblivious transfer can encrypt plaintext data into ciphertext. Therefore, the first and second types of encryption algorithms differ in their encryption methods.

[0055] In some embodiments, taking the second type of query request as an example, it may include more than just the second type of encryption algorithm. Specifically, after determining the second type of encryption algorithm, the querying party may generate a key pair. The second type of query request may include the encryption algorithm and the public key. Other participants may perform encryption based on the encryption algorithm and the public key.

[0056] In operation S240, first target data provided by the first participant is obtained for data processing, wherein the first participant is configured to obtain the first target data using a first type of encryption algorithm or a second type of encryption algorithm.

[0057] Exemplarily, the querying party or first party may be any party in a multi-party secure computing system. Acquiring the first target data in operation S240 may involve directly receiving data sent by the first party, or the first party may send the first target data to other parties and then acquire the data by receiving data sent by the other parties.

[0058] According to the embodiments of the present disclosure, by determining different types of query operations and adaptively sending corresponding query requests, it is easy to select the corresponding encryption algorithm and improve encryption processing efficiency. By using the encryption algorithm predetermined by the querying party, each participating party is required to perform processing according to the encryption algorithm, ensuring consistency in encryption processing among all participating parties. This allows for faster acquisition of target data while maintaining privacy protection and improving overall computing performance.

[0059] According to an embodiment of the present disclosure, the method further includes: determining a data transfer rule in response to a query operation and sending the rule to the first participant, wherein the data transfer rule is used by the first participant to determine the destination for sending the first target data. The purpose of determining the data transfer rule is to improve the degree of data privacy protection by determining the calculation order of the multi-party secure computation, so that each participant can iteratively calculate in sequence (the next participant uses local data and the output of the previous participant to perform the calculation), thereby improving the degree of data privacy protection.

[0060] In some embodiments, determining the data transfer rule includes determining a data transfer order between the participants, wherein the first participant is configured to determine the next participant in the data transfer order as the transmission destination. The data transfer order is used to predetermine the number of iterations in which each participant participates in the calculation, thereby improving computational efficiency and preventing a participant from performing repeated calculations, resulting in inaccurate results.

[0061] In other embodiments, determining the data transfer rule includes: each participant calculates the encrypted data and returns it to the querying party, and then the querying party re-determines the next participant.

[0062] In other embodiments, determining the data transmission rule includes determining a random determination rule. For example, the first participant may obtain data from other participants that are not participating in the computation and randomly determine one of them as the next participant in the computation. The purpose of random determination is to prevent the leakage of the pre-determined transmission order, which would allow an attacker to reversely infer the data provided by a particular participant.

[0063] Figure 3The flowchart of the data processing method for the first participant according to the embodiment of the present disclosure is schematically shown.

[0064] like Figure 3 As shown, the data processing method for the first participant in this embodiment includes operations S310 to S340.

[0065] In operation S310, a query request sent by a querying party is received, wherein the query request is used to obtain first target data provided by a first participant.

[0066] For example, the first party may be the first party to receive the query request, or may not be the first party to receive the query request. If it is not the first party to receive the query request, the first party receives the query request from another party, such as receiving a data processing instruction, which includes the query request.

[0067] In operation S320 , if the query request is a first type query request, the second target data is encrypted using a first type encryption algorithm to obtain the first target data.

[0068] In operation S330, if the query request is a second-type query request, the third target data is encrypted using the second-type encryption algorithm to obtain the first target data, wherein the second target data and the third target data have different data ranges, and the encryption methods of the first-type encryption algorithm and the second-type encryption algorithm are different.

[0069] For example, the first or second encryption algorithms can be predetermined by the querying party or determined by the first party based on the type of query request. The second and third target data are local data of the first party. Local data refers to data that the party has the authority to collect, store, use, process, transmit, provide, disclose, and apply. This disclosure does not limit this data to local storage.

[0070] According to an embodiment of the present disclosure, the second target data includes data obtained by the first participant performing a statistical aggregation operation, and the encryption processing of the second target data using the first type of encryption algorithm includes: using the first type of encryption algorithm to add data noise to the second target data to obtain the first target data. The first type of query request can be a statistical query request, which is used to query statistically aggregated data. The first type of encryption algorithm can include a differential privacy algorithm. The effect of adding data noise is that the range of data involved in the statistical aggregation operation is relatively wide. If the ciphertext data is obtained for all plaintext data, the computational efficiency may be poor. Therefore, the computational efficiency can be improved by adding noise.

[0071] According to an embodiment of the present disclosure, the third target data includes data obtained by the first participant without performing statistical aggregation operations. Encrypting the third target data using the second type of encryption algorithm includes: using the second type of encryption algorithm to obtain first ciphertext data based on the plaintext data of the third target data, wherein the first target data includes the first ciphertext data. The second type of query request can be a common query request used to obtain data that does not require statistical aggregation. The second type of encryption algorithm can include algorithms such as obfuscation circuits, homomorphic encryption, secret sharing, and oblivious transfer.

[0072] Using the second type of encryption algorithm for the target data of common query requests improves the accuracy of common query results. For example, if a user has a desired record in the past year, the result is either "yes" or "no." For such a single result, injecting data noise could alter the "yes" or "no" result, resulting in inaccuracy. Therefore, encrypting the plaintext "yes" or "no" to obtain ciphertext data can avoid such inaccuracies.

[0073] In operation S340 , the first target data is transmitted so that the querying party performs data processing using the first target data.

[0074] For example, the first participant may directly send the first target data to the querying party, or may send the first target data to other participants. Then, the other participants perform calculations based on the first target data and output the results to the querying party.

[0075] According to the embodiments of the present disclosure, computing performance is improved by identifying different types of query requests and using corresponding encryption algorithms. For example, if the second target data queried by a first type of query request has a different data range than the third target data queried by a second type of query request, higher computing performance can be achieved by processing the corresponding data ranges based on the different encryption methods of the first and second types of encryption algorithms.

[0076] Figure 4 The flowchart of the data processing method for the first participant according to another embodiment of the present disclosure is schematically shown.

[0077] like Figure 4 As shown, the data processing method for the first participant in this embodiment includes operations 310 to S330, and also includes operations 410 to S420. Operations 310 to S330 can refer to the above embodiment and are not described in detail here.

[0078] In operation S410 , a query request is parsed to obtain a data transfer rule, wherein the data transfer rule is used to determine a sending target of first target data.

[0079] Transmitting the first target data in operation S340 includes operation S420. In operation S420, the first target data is transmitted to a transmission target according to a data transmission rule. The transmission target includes a second participant, and the second participant is configured to use the first target data to obtain fourth target data, so that the querying party can use the fourth target data for data processing. The purpose of the data transmission rule is to clarify to the first participant how to determine the next participant, thereby improving data transmission efficiency.

[0080] According to an embodiment of the present disclosure, the data transfer rule includes a data transfer order between each participant predetermined by the querying party. In operation S420, sending the first target data to the second participant according to the data transfer rule includes: after determining the second participant from the data transfer order, sending the first target data to the second participant, wherein the second participant is the next participant after the first participant in the data transfer order. The purpose of the data transfer order is to improve computational efficiency by allowing the querying party to predetermine the number of iterative calculations in which each participant will participate, thereby avoiding the situation in which the first participant may send data to a participant that has already participated in the calculation, resulting in inaccurate results obtained from repeated calculations.

[0081] According to an embodiment of the present disclosure, in operation S420, sending the first target data to the second participant according to the data transmission rule includes: randomly determining a participant from the participants who have not participated in the calculation as the sending target, and sending the first target data to the sending target.

[0082] In some embodiments, different computation orders may result in different intermediate results output by different participants. The purpose of random determination is to prevent the leakage of the pre-determined transmission order, which would allow an attacker to reversely infer the data provided by a participant.

[0083] It should be noted that in some embodiments, the querying party may also be a second participant. For example, although the querying party issues a query request, the query request may obtain the querying party's local data for calculation. In this case, the querying party is also a participant in the iterative calculation.

[0084] Figure 5 The flowchart of the data processing method for the second participant according to the embodiment of the present disclosure is schematically shown.

[0085] like Figure 5 As shown, the data processing method for the second participant in this embodiment includes operations S510 to S540.

[0086] In operation S510, a data processing instruction is received from a first party, wherein the data processing instruction includes first target data and a third-type encryption algorithm. The first party is configured to, in response to a query request from a querying party, encrypt the local data using the third-type encryption algorithm to obtain the first target data.

[0087] Exemplarily, data processing instructions may also include query requests. The purpose of the data processing instructions is to carry the information required by each participant to perform a multi-party secure computation, thereby improving the efficiency of this iterative computation. The third type of encryption algorithm is either the first or second type of encryption algorithm. Specifically, as described in the above embodiments, the type of third type of encryption algorithm is determined by the type of query request and is not further elaborated here.

[0088] In operation S520, the fifth target data is encrypted using the third encryption algorithm.

[0089] For example, the fifth target data may be local data of the second participant, and the second participant has the right to collect, store, use, process, transmit, provide, disclose, and apply the fifth target data.

[0090] In operation S530, fourth target data is obtained based on the first target data and the encrypted fifth target data.

[0091] For example, if the third type of encryption algorithm is the second type of encryption algorithm, for example, the third type of encryption algorithm is a homomorphic encryption algorithm. The first target data and the fifth target data after encryption are both ciphertext data. Based on the two ciphertext data, the fourth target data is calculated again, which can increase the difficulty of reverse cracking by an attacker.

[0092] In operation S540 , the fourth target data is transmitted so that the querying party performs data processing using the fourth target data.

[0093] For example, the second participant can be any participant in the multi-party secure computing system. It can return the fourth target data directly to the inquiring party, or it can continue to send the fourth target data to the next participant for computation. For example, the next participant can encrypt the local data and combine it with the fourth target data for further computation. For example, the data processing instruction can also include data transfer rules, allowing the second participant to determine the next participant based on the data transfer rules.

[0094] For example, the first party may be the first party to receive the query request, or may not be the first party to receive the query request. If it is not the first party to receive the query request, the first party may perform a process similar to operations S510 to S540 to obtain the first target data.

[0095] The method where each participant encrypts local data and then directly returns it to the querying party makes it easy to reverse-cracker the data provided by the corresponding participant. According to the embodiments of the present disclosure, data security is improved during the multi-party secure computation process by transferring data between the various participants and performing iterative calculations on the encrypted data.

[0096] According to the embodiment of the present disclosure, referring to Figures 1 to 5 , the following further introduces the workflow diagram of the multi-party secure computing system 100.

[0097] For example, four participants, A, B, C, and D, respectively, form a multi-party secure computing system 100 based on a distributed computing architecture (e.g., a peer-to-peer network) through a first server 101, a second server 102, a third server 103, and a fourth server 104. This multi-party secure computing system 100, through the multi-party secure computing architecture, allows multiple governments and financial institutions (e.g., A, B, C, and D) to share customer data while ensuring that sensitive data itself is not leaked, thereby achieving a more reliable credit risk assessment system, reducing systemic financial risks, and increasing credit returns.

[0098] Each participant can deploy management and control nodes and computing nodes, connected via a dedicated network or the internet. Query processing (massaging and encryption) is performed locally on the data provider, and data is encrypted before transmission across the network. Risk calculations are performed locally on the querying party. Management and control nodes are primarily responsible for maintaining network node information, authentication (user login), and network firewalls. Software technologies such as Zookeeper (a registry) can be used to maintain network node information. Computing nodes handle business logic operations, including processing query requests and running risk models (calculations).

[0099] Take A as the querying party, B, C, and D as the first, second, and third parties respectively as an example.

[0100] First, when Party A needs to conduct a credit risk assessment on Client A, it submits a query request (for example, inputting Client A's identity information) through its own query client (e.g., deployed on a terminal device). The query client then sends the query request to the query processing server of Parties A, B, C, and D (e.g., deployed on a server, specifically a computing node).

[0101] In some embodiments, during the credit risk assessment of customer A, if the individual's financial record data is calculated, a general query request is sent. If the statistical financial record data of a group (e.g., an occupational group) to which the individual belongs is calculated, a statistical query request is sent. If both personal data and statistical data are calculated, the request sent may include both a general query request and a statistical query request, each of which is processed using an encryption algorithm.

[0102] Secondly, for example, Party A's query processing server first performs encrypted calculations on local data and then sends the encrypted data and query request to Party B. Specifically, Party B's control node is responsible for receiving the encrypted data and query request, performing identity authentication, and then sending the encrypted data and query request to the computing node for further processing by the query processing server. Following a similar process, Party C and Party D perform calculations in sequence. Ultimately, Party D sends the results to Party A.

[0103] Finally, after Party A obtains data from multiple parties, it uses the risk model to calculate and obtain the credit risk assessment results of Customer A.

[0104] In some embodiments, if the query request is a statistical query, a differential privacy algorithm can be used to inject noise (such as Laplace or exponentially distributed noise) into the source data and then output the statistical results. For example, Party B can inject noise into local data, then combine the encrypted data sent by Party A with the encrypted local data, inject further noise, and send the result to Party C.

[0105] In other embodiments, if the query request is a common query, a homomorphic encryption algorithm may be used. Homomorphic encryption algorithms may include additive homomorphism, multiplicative homomorphism, or full homomorphism. Here, the Paillier additive homomorphic algorithm is used as an example. The result of performing a "*" operation on the ciphertext domain is equal to the output of performing a "+" operation on the plaintext domain and then performing encryption. This property is additive homomorphism, as shown in Equation (1).

[0106] Formula (1)

[0107] Among them, there are public key encryption schemes: , where Keygen is the key generation function, Enc is the encryption function, and Dec is the decryption function. Using KeyGen(k), we generate a public-private key pair (pk, sk). Let M be the plaintext domain and C be the ciphertext domain, with the following relationship.

[0108]

[0109]

[0110] Assume that the risk model used by Party A is a linear regression model, as shown in formula (2).

[0111] Formula (2)

[0112] Where X is the basic data structure used for credit rating (usually a vector or matrix), and Y is the credit rating result. The least squares method is often used to determine the model parameters α and β. The calculation formula is as follows:

[0113]

[0114]

[0115] In the formula, (x i ,y i ) is a data set {(x1, y1), (x2, y2)…(x n ,y n )}. Each participant in the multi-party network provides a data pair (basic data structure and credit rating result). Because the data provided by each participant is encrypted, homomorphic encryption algorithms can be used to obtain α and β.

[0116] According to the calculation formula of parameters α and β, the intermediate calculation results are:

[0117] , , ,

[0118] For example, the encrypted intermediate calculation results that Party A can obtain are as follows:

[0119] ,

[0120] ,

[0121]

[0122] Each participant encrypts the locally provided data and performs iterative calculations across all parties. For example, Party A encrypts its own data and transmits it to Party B. Party B then adds its own encrypted data to Party A's data and transmits it to Party C, and so on. Finally, the encrypted intermediate calculation results are transmitted to Party A. Finally, Party A decrypts the plaintext intermediate calculation results (but cannot infer the original data of the parties involved). Using the aforementioned model parameter calculation formula, α and β are obtained. Once the model parameters are determined, credit risk calculations can be performed to obtain rating results.

[0123] According to the embodiments of the present disclosure, differential privacy technology is used for statistical queries, and obfuscation circuits, homomorphic encryption, etc. are used for ordinary queries according to the type of query data, thereby enhancing the confidentiality of data shared by multiple parties and improving the performance of system operation.

[0124] Based on the above data processing method, the present disclosure also provides data processing devices for the first participant, the second participant and the querying party. Figures 6 to 13The device is described in detail.

[0125] Figure 6 The structural block diagram of a data processing device for a first participant according to an embodiment of the present disclosure is schematically shown.

[0126] like Figure 6 As shown, the data processing device 600 of this embodiment includes a first receiving module 610 , a first encryption module 620 , a second encryption module 630 and a first sending module 640 .

[0127] The first receiving module 610 may perform operation S310 to receive a query request sent by a querying party, wherein the query request is used to obtain first target data provided by a first participant.

[0128] The first encryption module 620 may perform operation S320 to encrypt the second target data using the first encryption algorithm to obtain the first target data if the query request is a first type of query request.

[0129] The second encryption module 630 can perform operation S330, which is used to encrypt the third target data using the second encryption algorithm to obtain the first target data if the query request is a second-type query request, wherein the second target data and the third target data have different data ranges, and the encryption methods of the first encryption algorithm and the second encryption algorithm are different.

[0130] The first sending module 640 may perform operation S340 to send the first target data, so that the querying party performs data processing using the first target data.

[0131] Figure 7 The structural block diagram of a data processing device for a second participant according to an embodiment of the present disclosure is schematically shown.

[0132] like Figure 7 As shown, the data processing device 700 of this embodiment includes a second receiving module 710 , a third encryption module 720 , a data calculation module 730 and a fourth sending module 740 .

[0133] The second receiving module 710 may execute operation S510 to receive a data processing instruction sent by the first party, wherein the data processing instruction includes the first target data and the third type of encryption algorithm. The first party is configured to, in response to the query request of the querying party, encrypt the local data using the third type of encryption algorithm to obtain the first target data.

[0134] The third encryption module 720 may perform operation S520 to encrypt the fifth target data by using the third encryption algorithm.

[0135] The data calculation module 730 may perform operation S530 to obtain fourth target data according to the first target data and the encrypted fifth target data.

[0136] The fourth sending module 740 may perform operation S540 to send the fourth target data, so that the querying party performs data processing using the fourth target data.

[0137] Figure 8 The structural block diagram of a data processing device for a querying party according to an embodiment of the present disclosure is schematically shown.

[0138] like Figure 8 As shown, the data processing device 800 of this embodiment includes a type determination module 810 , a second sending module 820 , a third sending module 830 and a second acquisition module 840 .

[0139] The type determination module 810 may perform operation S210 for determining a query type of a query operation in response to a query operation of a user.

[0140] The second sending module 820 may perform operation S220 for sending a first-type query request to the first party if the query type is a first-type operation, wherein the first-type query request includes a first-type encryption algorithm.

[0141] The third sending module 830 can execute operation S230, which is used to send a second-type query request to the first participant if the query type is a second-type operation, wherein the second-type query request includes a second-type encryption algorithm, and the first-type query request and the second-type query request are used to obtain target data in different ranges, and the encryption methods of the first-type encryption algorithm and the second-type encryption algorithm are different.

[0142] The second acquisition module 840 may execute operation S240 to acquire first target data provided by the first party for data processing, wherein the first party is configured to obtain the first target data using the first type of encryption algorithm or the second type of encryption algorithm.

[0143] Figure 9 The structural block diagram of the query client module according to an embodiment of the present disclosure is schematically shown.

[0144] like Figure 9 As shown, the data processing device 800 of this embodiment may include a query client module 850. The query client module 850 is used by the querying party (user) to log in, submit requests to query multi-party data, and view query results and credit risk assessment results. It also implements user login authentication and permission control. The query client module 850 may include a user management unit 851, a query scheduling unit 852, and a result storage and display unit 853.

[0145] The user management unit 851 is used to perform identity authentication and authority control on logged-in users. The system administrator can configure the roles and permissions of other users.

[0146] The query scheduling unit 852 is used to forward the query request according to the type of the query request submitted by the user.

[0147] The result storage and display unit 853 is used to store data query results and credit risk calculation results, and use a user-friendly interface to achieve data visualization display.

[0148] Figure 10 The structural block diagram of the statistical query module according to an embodiment of the present disclosure is schematically shown.

[0149] like Figure 10 As shown, the data processing device 800 of this embodiment may include a statistical query module 860. Statistical query module 860 is used to process statistical query requests using differential privacy technology, primarily using Laplace and exponentially distributed noise, and outputting noisy statistical results. Statistical query module 860 may include a differential privacy parameter unit 861, a Laplace distributed noise unit 862, and an exponentially distributed noise unit 863.

[0150] The differential privacy parameter unit 861 is used to adjust the noise level of the data statistical results by configuring the parameters of the differential privacy algorithm.

[0151] The Laplace distribution noise unit 862 is used to perform data statistical query, add Laplace distribution noise, and output statistical results with noise.

[0152] The exponential distribution noise unit 863 is used to perform data statistical query, add exponential distribution noise, and output statistical results with noise.

[0153] Figure 11 The structural block diagram of a common query module according to an embodiment of the present disclosure is schematically shown.

[0154] like Figure 11 As shown, the data processing device 800 of this embodiment may include a normal query module 870. Normal query module 870 is used to process normal query requests, mainly using obfuscation circuits and homomorphic encryption technology, and output encrypted query results. Normal query module 870 may include an obfuscation circuit unit 871 and a homomorphic encryption unit 872.

[0155] The obfuscation circuit unit 871 is used to perform ordinary queries and use the obfuscation circuit algorithm to output encrypted query results.

[0156] The homomorphic encryption unit 872 is used to execute ordinary queries and use a homomorphic encryption algorithm to output encrypted query results.

[0157] Figure 12 The structure block diagram of the credit risk calculation module according to an embodiment of the present disclosure is schematically shown.

[0158] like Figure 12 As shown, the data processing device 800 of this embodiment may include a credit risk calculation module 880. Credit risk calculation module 880 is configured to perform calculations based on multi-party data using a credit risk model and output credit risk calculation results. Credit risk calculation module 880 may include a data cache unit 881, a risk model unit 882, and a parameter adjustment unit 883.

[0159] The data cache unit 881 is used to store the multi-party data query results in the local cache for credit risk calculation. The credit risk calculation results are stored in the local cache for client query.

[0160] The risk model unit 882 is used to load and update the credit risk model and use the model and multi-party data to calculate credit risk.

[0161] The parameter adjustment unit 883 is used to adjust various parameters of the credit risk model (such as error parameters, etc.) according to the type of credit risk model.

[0162] Figure 13 The following schematically shows an operation flow chart of a data processing device 800 for a querying party according to an embodiment of the present disclosure.

[0163] like Figure 13 As shown, the user can use the data processing device 800 to perform operations S1301 to S1307.

[0164] Operation S1301: system startup.

[0165] Operation S1302: An authorized user logs in and prepares to query data.

[0166] Operation S1303: The user submits a multi-party data query request.

[0167] In operation S1304 , the system performs a query on multi-party data.

[0168] Operation S1305: The multi-party data query result is returned to the querying party, and credit risk calculation is initiated using the multi-party data.

[0169] Operation S1306: Generate a credit risk assessment report based on the credit risk calculation result using data visualization technology.

[0170] In operation S1307, the user initiates a re-query based on demand, and the system re-queries the multi-party data and generates a credit risk assessment report.

[0171] According to an embodiment of the present disclosure, any multiple modules in the data processing device 600, the data processing device 700, or the data processing device 800 may be combined into a single module for implementation, or any one of the modules may be split into multiple modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of other modules and implemented in a single module.

[0172] According to an embodiment of the present disclosure, at least one module in the data processing device 600, the data processing device 700, or the data processing device 800 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application-specific integrated circuit (ASIC), or may be implemented in hardware or firmware by any other reasonable means of integrating or packaging circuits, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in an appropriate combination of any of them. Alternatively, at least one module in the data processing device 600, the data processing device 700, or the data processing device 800 may be at least partially implemented as a computer program module, which may perform corresponding functions when executed.

[0173] It should be noted that the implementation methods, technical problems solved, functions implemented, and technical effects achieved of each module / unit / sub-unit in the device part embodiment are the same or similar to the implementation methods, technical problems solved, functions implemented, and technical effects achieved of each corresponding step in the method part embodiment, and will not be repeated here.

[0174] Figure 14 The block diagram schematically shows an electronic device suitable for implementing the data processing method according to an embodiment of the present disclosure.

[0175] like Figure 14 As shown, the electronic device 1400 according to an embodiment of the present disclosure includes a processor 1401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1402 or a program loaded from a storage portion 1408 into a random access memory (RAM) 1403. The processor 1401 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1401 may also include onboard memory for caching purposes. The processor 1401 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present disclosure.

[0176] Various programs and data required for the operation of the electronic device 1400 are stored in the RAM 1403. The processor 1401, the ROM 1402, and the RAM 1403 are connected to each other via a bus 1404. The processor 1401 performs various operations of the method flow according to the embodiment of the present disclosure by executing the programs in the ROM 1402 and / or the RAM 1403. It should be noted that the programs may also be stored in one or more memories other than the ROM 1402 and the RAM 1403. The processor 1401 may also perform various operations of the method flow according to the embodiment of the present disclosure by executing the programs stored in the one or more memories.

[0177] According to an embodiment of the present disclosure, electronic device 1400 may further include an input / output (I / O) interface 1405, which is also connected to bus 1404. Electronic device 1400 may also include one or more of the following components connected to I / O interface 1405: an input section 1406 including a keyboard, mouse, etc.; an output section 1407 including devices such as a cathode ray tube (CRT), liquid crystal display (LCD), and speakers; a storage section 1408 including a hard disk; and a communication section 1409 including a network interface card such as a LAN card or modem. Communication section 1409 performs communication processing via a network such as the Internet. A drive 1410 is also connected to I / O interface 1405 as needed. Removable media 1411, such as a magnetic disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed in drive 1410 as needed, so that computer programs read from the removable media can be installed into storage section 1408 as needed.

[0178] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not be incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when executed, implements the method according to the embodiments of the present disclosure.

[0179] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, and may include, for example, but not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1402 and / or RAM 1403 described above, and / or one or more memories other than ROM 1402 and RAM 1403.

[0180] The embodiments of the present disclosure also include a computer program product, which includes a computer program containing program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the method provided by the embodiments of the present disclosure.

[0181] The computer program executes the above functions defined in the system / device of the embodiment of the present disclosure when the processor 1401 executes the computer program. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0182] In one embodiment, the computer program may be stored on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may be transmitted and distributed in the form of a signal on a network medium, downloaded and installed via the communication portion 1409, and / or installed from removable media 1411. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0183] In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 1409 and / or installed from the removable medium 1411. When the computer program is executed by the processor 1401, the above-described functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the systems, devices, means, modules, units, etc. described above can be implemented by computer program modules.

[0184] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computer programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect via the Internet).

[0185] The embodiments of the present disclosure are described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be used in combination to advantage. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A data processing method based on multi-party secure computing, for a first participant, comprising: receiving a query request sent by a querying party, wherein the query request is used to obtain first target data provided by the first participant; If the query request is a first-type query request, encrypt the second target data using a first-type encryption algorithm to obtain the first target data; If the query request is a second-type query request, encrypt the third target data using the second-type encryption algorithm to obtain the first target data, wherein the second target data and the third target data have different data ranges, and the first-type encryption algorithm and the second-type encryption algorithm have different encryption methods; The first target data is sent so that the querying party performs data processing using the first target data.

2. The method according to claim 1, wherein The second target data includes data obtained by the first participant performing a statistical aggregation operation, and the encryption processing of the second target data using the first type of encryption algorithm includes: The first type of encryption algorithm is used to add data noise to the second target data to obtain the first target data.

3. The method according to claim 1, wherein The third target data includes data obtained by the first participant without performing statistical aggregation operations, and the encryption processing of the third target data using the second type of encryption algorithm includes: The second-type encryption algorithm is used to obtain first ciphertext data based on the plaintext data of the third target data, wherein the first target data includes the first ciphertext data.

4. The method according to claim 1, wherein The method further comprises: parsing the query request to obtain a data transfer rule, wherein the data transfer rule is used to determine a sending target of the first target data; The sending of the first target data includes: According to the data transfer rule, the first target data is sent to the sending target.

5. The method according to claim 4, wherein The sending target includes a second participant, the data transfer rule includes a data transfer order between the participants predetermined by the querying party, and sending the first target data to the sending target according to the data transfer rule includes: After the second participant is determined from the data transfer sequence, the first target data is sent to the second participant, wherein the second participant is the next participant of the first participant in the data transfer sequence.

6. The method according to claim 4, wherein: The sending of the first target data to the sending target according to the data transfer rule includes: A participant is randomly determined from participants that have not participated in the calculation as the sending target, and the first target data is sent.

7. A data processing method based on multi-party secure computation, for use by a querying party, comprising: In response to a query operation by a user, determining a query type of the query operation; If the query type is a first type of operation, sending a first type of query request to the first participant, wherein the first type of query request includes a first type of encryption algorithm; If the query type is a second-type operation, sending a second-type query request to the first participant, wherein the second-type query request includes a second-type encryption algorithm, the first-type query request and the second-type query request are used to obtain target data in different ranges, and the first-type encryption algorithm and the second-type encryption algorithm have different encryption methods; Obtain first target data provided by the first participant for data processing, wherein the first participant is configured to obtain the first target data using the first type of encryption algorithm or the second type of encryption algorithm.

8. The method according to claim 7, wherein: The method further comprises: In response to the query operation, a data transfer rule is determined and sent to the first participant, wherein the data transfer rule is used by the first participant to determine a sending target for the first target data.

9. The method according to claim 8, wherein Determining the data transmission rule includes: A data transmission sequence between the participants is determined, wherein the first participant is configured to determine the next participant from the data transmission sequence as the sending target.

10. A data processing method based on multi-party secure computing, for a second party, comprising: Receiving a data processing instruction sent by the first participant, wherein the data processing instruction includes first target data and a third type of encryption algorithm; encrypting the fifth target data using the third encryption algorithm; Obtaining fourth target data according to the first target data and the encrypted fifth target data; sending the fourth target data so that the querying party performs data processing using the fourth target data; The first participant is configured to obtain the first target data in response to the query request of the query party: If the query request is a first-type query request, the second target data is encrypted using a first-type encryption algorithm to obtain the first target data; if the query request is a second-type query request, the third target data is encrypted using a second-type encryption algorithm to obtain the first target data, wherein the second target data and the third target data have different data ranges, and the encryption methods of the first-type encryption algorithm and the second-type encryption algorithm are different.

11. A data processing device based on multi-party secure computing, for a first participant, comprising: A first receiving module is configured to receive a query request sent by a querying party, wherein the query request is used to obtain first target data provided by the first participant; a first encryption module, configured to, if the query request is a first type of query request, encrypt the second target data using a first type of encryption algorithm to obtain the first target data; a second encryption module configured to, if the query request is a second-type query request, encrypt the third target data using a second-type encryption algorithm to obtain the first target data, wherein the second target data and the third target data have different data ranges, and the first-type encryption algorithm and the second-type encryption algorithm have different encryption modes; The first sending module is used to send the first target data, so that the querying party uses the first target data to perform data processing.

12. A data processing device based on multi-party secure computing, for use by a querying party, comprising: a type determination module, configured to determine a query type of a query operation in response to a user's query operation; a second sending module, configured to send a first-type query request to the first party if the query type is a first-type operation, wherein the first-type query request includes a first-type encryption algorithm; a third sending module, configured to, if the query type is a second-type operation, send a second-type query request to the first participant, wherein the second-type query request includes a second-type encryption algorithm, the first-type query request and the second-type query request are used to obtain target data in different ranges, and the first-type encryption algorithm and the second-type encryption algorithm have different encryption methods; The second acquisition module is configured to acquire first target data provided by the first participant for data processing, wherein the first participant is configured to obtain the first target data using the first type of encryption algorithm or the second type of encryption algorithm.

13. A data processing device based on multi-party secure computing, for a second party, comprising: A second receiving module is configured to receive a data processing instruction sent by the first participant, wherein the data processing instruction includes the first target data and the third type of encryption algorithm; A third encryption module, configured to encrypt the fifth target data using the third encryption algorithm; a data calculation module, configured to obtain fourth target data based on the first target data and the encrypted fifth target data; a fourth sending module, configured to send the fourth target data so that the querying party performs data processing using the fourth target data; The first participant is configured to obtain the first target data in response to the query request of the query party: If the query request is a first-type query request, the second target data is encrypted using a first-type encryption algorithm to obtain the first target data; if the query request is a second-type query request, the third target data is encrypted using a second-type encryption algorithm to obtain the first target data, wherein the second target data and the third target data have different data ranges, and the encryption methods of the first-type encryption algorithm and the second-type encryption algorithm are different.

14. An electronic device comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to execute the method according to any one of claims 1 to 10.

15. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to perform the method according to any one of claims 1 to 10.

16. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 10 is implemented.

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