Credit line evaluation method and related device

Abstract

The invention discloses a credit line evaluation method and a related device, and relates to the technical field of big data, and the method comprises the steps that a data source end obtains target credit information of a to-be-credit party; and performing homomorphic encryption on the target indexes by using the public key to obtain a homomorphic encryption polynomial of each target index. And sending the encrypted credit granting information to a data evaluation end. And the data evaluation end performs homomorphic operation on the homomorphic encryption polynomial of each target index based on a pre-configured credit evaluation model to obtain a ciphertext credit line. And the data evaluation end uses the private key to decrypt the ciphertext credit line to obtain the plaintext credit line. Therefore, according to the method, the target credit information of the to-be-credit party is subjected to homomorphic encryption operation and decryption operation, so that the credit line of the to-be-credit enterprise can be quickly calculated by using the pre-configured credit evaluation model under the condition of ensuring the data privacy of each party. And the data security and the reliability of the credit line of the to-be-credit enterprise are improved.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to a credit line assessment method and related devices. Background Art

[0002] With the development of the times, the group of small and medium-sized enterprises is growing day by day. In daily operations, small and medium-sized enterprises often provide goods and invoices first, and then wait for customers to settle payments on a quarterly or fiscal year basis. Compared with large enterprises, the capital chain stability of small and medium-sized enterprises is lower, and they often need to obtain financial support through financing, loans, etc. When the enterprise system applies for financing, loans and other services from the bank system, the bank system needs to query various types of enterprise information of the applicant enterprise, and through the credit model configured by the bank system, accurately evaluate the credit and repayment ability of the enterprise based on various types of enterprise information, obtain the credit line, and improve the reliability of the credit. However, there is enterprise information involving information protection or sensitive enterprise data, so it is necessary to improve the data security in the credit line evaluation process. Summary of the invention

[0003] In view of the above problems, the present application provides a credit line assessment method and related devices to achieve the purpose of improving the data security of the credit line assessment process. The specific scheme is as follows:

[0004] The first aspect of the present application provides a credit line assessment method, comprising:

[0005] The data source obtains target credit information of the party to be granted credit, wherein the target credit information includes a target indicator and a corresponding indicator value.

[0006] The data source uses a public key to homomorphically encrypt each target indicator to obtain a homomorphic encryption polynomial of each target indicator;

[0007] The data source sends the encrypted credit information to the data evaluation end, wherein the encrypted credit information includes the homomorphic encryption polynomials of each target indicator;

[0008] The data evaluation terminal performs homomorphic operations on homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain a ciphertext credit limit of the party to be granted credit;

[0009] The data evaluation terminal uses a private key to decrypt the ciphertext credit limit of the party to be granted credit, and obtains the plaintext credit limit of the party to be granted credit.

[0010] In a possible implementation, the data source obtains target credit information of the party to be credited, including:

[0011] The data source end obtains the original data of the party to be granted credit in response to the credit business application of the party to be granted credit, and performs data preprocessing on the original data to obtain the credit information to be evaluated of the party to be granted credit; wherein the original data includes a preset credit evaluation index and a corresponding index value, and the data preprocessing includes a data cleaning operation, a data conversion operation, and a data encoding operation

[0012] The data source extracts features of the credit information to be evaluated of the party to be granted credit, determines target indicators in the credit information to be evaluated, and obtains the target credit information.

[0013] In a possible implementation, the data source uses a public key to homomorphically encrypt each target indicator to obtain a homomorphic encryption polynomial of each target indicator, including:

[0014] The data source end calls the HEAAN algorithm library to generate a key, wherein the key includes the private key and the public key; the HEAAN algorithm library is pre-configured with a homomorphic encryption function, a homomorphic operation function, and a homomorphic decryption function;

[0015] The data source end calls the HEAAN algorithm library to convert each target indicator into a polynomial;

[0016] The data source calls the HEAAN algorithm library and uses the public key to homomorphically encrypt the polynomials of each target indicator to obtain the homomorphic encrypted polynomials of each target indicator.

[0017] In a possible implementation, the data source sends the encrypted credit information to the data evaluation end, including:

[0018] The data source sends the encrypted credit information and credit business information to the data evaluation end, and the credit business information includes the identification of the party to be credited, the identification of the crediting party and the identification of the credit business.

[0019] In a possible implementation, the data evaluation end performs homomorphic operations on homomorphic encryption polynomials of the target indicators based on a preconfigured credit evaluation model to obtain the ciphertext credit limit of the party to be credited, including:

[0020] The data evaluation terminal obtains a credit evaluation rule based on the credit business information, and configures a homomorphic operation rule of the credit evaluation model based on the credit evaluation rule;

[0021] The data evaluation end calls the HEAAN algorithm library, and based on the credit evaluation model, performs homomorphic operations on the homomorphic encryption polynomials of each target indicator to obtain the ciphertext credit limit of the party to be credited.

[0022] A second aspect of the present application provides a credit line evaluation system, including: a data source end and a data evaluation end;

[0023] The data source end is used to: obtain target credit information of the party to be granted credit, wherein the target credit information includes target indicators and corresponding indicator values; use the public key to homomorphically encrypt each of the target indicators to obtain the homomorphically encrypted polynomials of each of the target indicators; send the encrypted credit information to the data evaluation end, wherein the encrypted credit information includes the homomorphically encrypted polynomials of each of the target indicators;

[0024] The data evaluation end is used to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted credit; use a private key to decrypt the ciphertext credit limit of the party to be granted credit to obtain the plaintext credit limit of the party to be granted credit.

[0025] In a possible implementation, the credit limit assessment system further includes: a pre-configured HEAAN algorithm library, wherein the HEAAN algorithm library is pre-configured with a homomorphic encryption function, a homomorphic operation function, and a homomorphic decryption function;

[0026] The data source end is specifically used to use the public key to perform homomorphic encryption on each of the target indicators, and when the homomorphic encryption polynomials of the target indicators are obtained, it is specifically used to call the HEAAN algorithm library to use the public key to perform homomorphic encryption on each of the target indicators, and obtain the homomorphic encryption polynomials of the target indicators;

[0027] The data evaluation end is used to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted; when using a private key to decrypt the ciphertext credit limit of the party to be granted to obtain the plaintext credit limit of the party to be granted, it is specifically used to call the HEAAN algorithm library to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted; and use a private key to decrypt the ciphertext credit limit of the party to be granted to obtain the plaintext credit limit of the party to be granted.

[0028] A third aspect of the present application provides a computer program product, comprising computer-readable instructions, which, when executed on an electronic device, enables the electronic device to implement the credit limit assessment method of the first aspect or any implementation of the first aspect.

[0029] A fourth aspect of the present application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein:

[0030] The memory is used to store computer programs;

[0031] The processor is used to execute the computer program so that the electronic device can implement the credit limit assessment method of the above-mentioned first aspect or any implementation manner of the first aspect.

[0032] A fifth aspect of the present application provides a computer storage medium, which carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement the credit limit evaluation method of the above-mentioned first aspect or any implementation method of the first aspect.

[0033] By means of the above technical scheme, the present application provides a credit line evaluation method and related devices, in which the data source end obtains the target credit information of the party to be granted. The target indicator is homomorphically encrypted using the public key to obtain the homomorphic encryption polynomial of each target indicator. The encrypted credit information is sent to the data evaluation end. Based on the pre-configured credit evaluation model, the data evaluation end performs homomorphic operations on the homomorphic encryption polynomials of each target indicator to obtain the ciphertext credit line. The data evaluation end uses the private key to decrypt the ciphertext credit line to obtain the plaintext credit line. It can be seen that this method can quickly calculate the credit line of the enterprise to be granted by using the pre-configured credit evaluation model under the condition of ensuring the data privacy of all parties by performing homomorphic encryption and decryption operations on the target credit information of the party to be granted. Improve data security and the reliability of the credit line of the enterprise to be granted. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0035] Figure 1 A schematic diagram of the credit line assessment system architecture provided for this application;

[0036] Figure 2 A schematic diagram of the hardware structure of a terminal provided in this application;

[0037] Figure 3 A schematic diagram of the hardware structure of a server provided for this application;

[0038] Figure 4 A flowchart of a credit line evaluation method provided in an embodiment of the present application;

[0039] Figure 5 A specific implementation flow chart of a credit line evaluation method provided in an embodiment of the present application;

[0040] Figure 6 A specific framework diagram of a credit line evaluation provided in an embodiment of the present application;

[0041] Figure 7 A schematic diagram of the structure of a credit line evaluation system provided in an embodiment of the present application;

[0042] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following describes the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. The terms used in the implementation method section of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0044] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0045] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, which is only to describe the distinction mode adopted by the objects of the same attributes when describing in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0046] The present application can be applied in the field of information security technology, and specifically can be applied to a scenario where abnormal data is obtained in a credit line assessment scenario. A credit line assessment method provided in an embodiment of the present application can be applied to a credit line assessment system, and the credit line assessment method can be implemented through a terminal or a server in the credit line assessment system, or the credit line assessment method can be implemented through the interaction between a terminal and a server in the credit line assessment system.

[0047] See also Figure 1 , Figure 1 A schematic diagram of a credit line assessment system architecture is shown. The system may include a terminal 100 and a server 200. The server 200 may include one or more servers ( Figure 1 In the example, a server is included, and the server 200 can provide the method provided in the embodiment of the present application for one or more terminals.

[0048] Among them, a credit line assessment application can be installed on the terminal 100. The above application and web page can provide an interface. The terminal 100 can receive relevant parameters entered by the user on the credit line assessment interface and send the above parameters to the server 200. The server 200 can obtain processing results based on the received parameters and return the processing results to the terminal 100.

[0049] It should be understood that in some optional implementations, the terminal 100 can also complete the action of obtaining the processing result based on the received parameters by itself without the cooperation of the server, and the embodiments of the present application are not limited to this.

[0050] Next describe Figure 1 The product form of the mid-terminal 100;

[0051] The terminal 100 in the embodiment of the present application can be a mobile phone, a tablet computer, a wearable device, a vehicle-mounted device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook, a personal digital assistant (PDA), etc., and the embodiment of the present application does not impose any limitation on this.

[0052] Figure 2 An optional hardware structure diagram of the terminal 100 is shown.

[0053] refer to Figure 2 As shown, the terminal 100 may include a radio frequency unit 110, a memory 120, an input unit 130, a display unit 140, a camera 150 (optional), an audio circuit 160 (optional), a speaker 161 (optional), a microphone 162 (optional), an earphone jack 163 (optional), a processor 170, an external interface 180, a power supply 190 and other components. Those skilled in the art will appreciate that Figure 2 These are merely examples of terminals or multi-function devices and do not constitute limitations on the terminals or multi-function devices, which may include more or fewer components than those shown in the figures, or combinations of certain components, or different components.

[0054] The input unit 130 can be used to receive input digital or character information, and generate key signal input related to the user settings and function control of the portable multifunctional device. Specifically, the input unit 130 may include a touch screen 131 (optional) and / or other input devices 132. The touch screen 131 can collect the user's touch operations on or near it (such as the user's operation on or near the touch screen using any suitable object such as fingers, joints, stylus, etc.), and drive the corresponding connection device according to a pre-set program. The touch screen can detect the user's touch action on the touch screen, convert the touch action into a touch signal and send it to the processor 170, and can receive and execute the command sent by the processor 170; the touch signal at least includes the touch point coordinate information. The touch screen 131 can provide an input interface and an output interface between the terminal 100 and the user. In addition, the touch screen can be implemented using multiple types such as resistive, capacitive, infrared and surface acoustic wave. In addition to the touch screen 131, the input unit 130 can also include other input devices. Specifically, other input devices 132 may include, but are not limited to, one or more of a physical keyboard, function keys (such as a volume control key, a switch key, etc.), a trackball, a mouse, a joystick, and the like.

[0055] Among them, the input device 132 can receive input data and the like.

[0056] The display unit 140 may be used to display information input by the user or provided to the user, various menus of the terminal 100, interactive interfaces, file displays, and / or playback of any multimedia files. In an embodiment of the present application, the display unit 140 may be used to display an interface for evaluating a credit limit, processing results, and the like.

[0057] The memory 120 can be used to store instructions and data. The memory 120 can mainly include an instruction storage area and a data storage area. The data storage area can store various data, such as multimedia files, texts, etc.; the instruction storage area can store software units such as operating systems, applications, instructions required for at least one function, or their subsets and extensions. It can also include a non-volatile random access memory; provide the processor 170 with hardware, software and data resources including management of computing and processing equipment, and support control software and applications. It is also used for the storage of multimedia files, and the storage of running programs and applications.

[0058] The processor 170 is the control center of the terminal 100. It uses various interfaces and lines to connect various parts of the entire terminal 100. By running or executing instructions stored in the memory 120 and calling data stored in the memory 120, it executes various functions of the terminal 100 and processes data, thereby controlling the terminal device as a whole. Optionally, the processor 170 may include one or more processing units; preferably, the processor 170 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application program, and the modem processor mainly processes wireless communication. It is understandable that the above-mentioned modem processor may not be integrated into the processor 170. In some embodiments, the processor and the memory may be implemented on a single chip, and in some embodiments, they may also be implemented separately on separate chips. The processor 170 may also be used to generate corresponding operation control signals, send them to corresponding components of the computing and processing device, read and process data in the software, especially read and process data and programs in the memory 120, so that each functional module therein performs corresponding functions, thereby controlling the corresponding components to act according to the requirements of the instructions.

[0059] Among them, the memory 120 can be used to store software codes related to the credit limit assessment method, the processor 170 can execute the steps of the credit limit assessment method, and can also schedule other units (such as the above-mentioned input unit 130 and display unit 140) to achieve corresponding functions.

[0060] The radio frequency unit 110 (optional) can be used for receiving and sending information or receiving and sending signals during a call, for example, after receiving the downlink information of the base station, it is sent to the processor 170 for processing; in addition, the designed uplink data is sent to the base station. Generally, the RF circuit includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (Low Noise Amplifier, LNA), a duplexer, etc. In addition, the radio frequency unit 110 can also communicate with network devices and other devices through wireless communication. The wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile communication (Global System of Mobile communication, GSM), General Packet Radio Service (General Packet Radio Service, GPRS), Code Division Multiple Access (Code Division Multiple Access, CDMA), Wideband Code Division Multiple Access (Wideband Code Division Multiple Access, WCDMA), Long Term Evolution (Long Term Evolution, LTE), email, Short Messaging Service (SMS), etc.

[0061] In this embodiment of the present application, the RF unit 110 can send data to the server 200 and receive processing results sent by the server 200.

[0062] It should be understood that the radio frequency unit 110 is optional and can be replaced by other communication interfaces, such as a network port.

[0063] The terminal 100 also includes a power supply 190 (such as a battery) for supplying power to various components. Preferably, the power supply can be logically connected to the processor 170 through a power management system, so that the power management system can manage functions such as charging, discharging, and power consumption.

[0064] The terminal 100 further includes an external interface 180 , which may be a standard Micro USB interface or a multi-pin connector, and may be used to connect the terminal 100 to communicate with other devices, or to connect a charger to charge the terminal 100 .

[0065] Although not shown, the terminal 100 may also include a flashlight, a wireless fidelity (WiFi) module, a Bluetooth module, sensors with different functions, etc., which are not described in detail here. Some or all of the methods described below may be applied in the following embodiments. Figure 2 In the terminal 100 shown.

[0066] Next describe Figure 1 The product form of the server 200;

[0067] Figure 3 A structural diagram of a server 200 is provided, such as Figure 3 As shown, the server 200 includes a bus 201, a processor 202, a communication interface 203, and a memory 204. The processor 202, the memory 204, and the communication interface 203 communicate with each other via the bus 201.

[0068] The bus 201 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0069] The processor 202 may be any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0070] The memory 204 may include a volatile memory, such as a random access memory (RAM). The memory 204 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0071] The memory 204 may be used to store software codes related to the credit limit assessment method, and the processor 202 may execute the steps of the credit limit assessment method of the chip, and may also schedule other units to implement corresponding functions.

[0072] It should be understood that the above-mentioned terminal 100 and server 200 can be centralized or distributed devices, and the processors in the above-mentioned terminal 100 and server 200 (such as processor 170 and processor 202) can be hardware circuits (such as application specific integrated circuit (ASIC), field-programmable gate array (FPGA), general-purpose processor, digital signal processor (DSP), microprocessor or microcontroller, etc.), or a combination of these hardware circuits. For example, the processor can be a hardware system with an instruction execution function, such as a CPU, DSP, etc., or a hardware system without an instruction execution function, such as an ASIC, FPGA, etc., or a combination of the above-mentioned hardware systems without an instruction execution function and hardware systems with an instruction execution function.

[0073] A credit line assessment method provided in an embodiment of the present application is applied to the field of information security technology and can be applied to the following scenarios: a core enterprise in the supply chain of the enterprise to be credited sends the credit data of the enterprise to be credited (i.e., the customer) to a financial institution to apply for financing, loans and other credit services for the enterprise to be credited, and the financial institution assesses the credit line of the enterprise to be credited through the credit data of the enterprise to be credited sent by the core enterprise.

[0074] In this process, the credit data is exchanged between the core enterprise's terminal and the financial institution's terminal. In order to improve the security of data interaction and ensure the reliability of the evaluation results, the present application embodiment provides a credit line evaluation method. The credit line evaluation method of the present application embodiment is described in detail below with reference to the accompanying drawings.

[0075] Reference Figure 4 , Figure 4 A flow chart of a credit line evaluation method provided in an embodiment of the present application is shown as follows: Figure 4 As shown, a credit line evaluation method provided in an embodiment of the present application is applied to a credit line evaluation system, wherein the credit line evaluation system includes a data source end and a data evaluation end, wherein the data source end as a data holder of credit data can be a terminal or a service end of a core enterprise, and the data evaluation end as a data receiver of credit data can be a terminal or a service end of a financial institution, and the data source end and the data evaluation end pre-build a communication channel, and the specific communication method is not limited in this embodiment, such as Figure 4 As shown, the method may include the following steps:

[0076] S401. The data source obtains target credit information of the party to be credited.

[0077] In this embodiment, the target credit information includes a target indicator and a corresponding indicator value.

[0078] S402. The data source uses the public key to homomorphically encrypt each target indicator to obtain a homomorphic encryption polynomial of each target indicator.

[0079] S403: The data source sends the encrypted credit information to the data evaluation end.

[0080] In this embodiment, the encrypted credit information includes homomorphic encryption polynomials of various target indicators.

[0081] S404. The data evaluation end performs homomorphic operations on the homomorphic encryption polynomials of various target indicators based on the pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be credited.

[0082] In this embodiment, the homomorphic operation includes a homomorphic addition operation and a homomorphic multiplication operation.

[0083] S405. The data evaluation terminal uses the private key to decrypt the ciphertext credit limit to obtain the plaintext credit limit of the party to be granted credit.

[0084] It can be seen from the above technical solution that the credit line assessment method provided in the embodiment of the present application can quickly calculate the credit line of the party to be granted credit by using a pre-configured credit assessment model under the condition of ensuring the data privacy of all parties by performing homomorphic encryption and decryption operations on the target credit information of the party to be granted credit, thereby improving data security and the reliability of the credit line of the party to be granted credit.

[0085] Furthermore, the credit limit assessment system also includes a HEAAN (Homomorphic Encryption for Arithmetic of Approximate Numbers) algorithm library. Both the data source end and the data assessment end are configured with an interface for calling a preset HEAAN algorithm library. The HEAAN algorithm library is called through the interface. It should be noted that the HEAAN algorithm library is an algorithm library based on the homomorphic encryption algorithm, which makes it convenient for us to apply it.

[0086] The core component layer of the HEAAN algorithm library mainly includes some data format parsing and intelligent rule logic recognition functions. Data integration mainly prepares data for the calculation model, connects to various data source channels such as enterprise ERP, obtains data of various dimensions of the enterprise, and converts the source data pushed by each system into system standard data after repeatability verification for subsequent use; the format parsing module mainly unifies various data formats such as integer, floating point, Boolean, etc.; type parsing mainly unifies the type of the integrated data to conform to the polynomial calculation input type. Rule parsing is to realize the homomorphic encryption and calculation of the processed and integrated input source data, obtain the ciphertext result, and decrypt it. The database layer mainly stores commonly used dictionary data, as well as data such as credit assessment models edited and saved online by operators.

[0087] The core functions of the HEAAN algorithm library include the following aspects:

[0088] Construction of polynomial ring: The HEAAN algorithm is based on a polynomial ring, where the polynomial coefficients are integers. By choosing appropriate parameters, a polynomial ring is constructed in which the polynomials can represent approximate numbers and perform addition and multiplication operations.

[0089] Correspondingly, the inverse operation of the encoding function is realized by the decoding function. The input of the decode function is m(x) and the output is a complex vector This process is called data decoding, which is used to restore the polynomial.

[0090] Homomorphic encryption: The HEAAN algorithm uses homomorphic encryption to encrypt polynomials.

[0091] Homomorphic encryption technology allows addition and multiplication operations to be performed in an encrypted state without decryption. The specific implementation of homomorphic encryption can use an encryption scheme based on the LWE (Learning with Errors) problem.

[0092] Optionally, encryption is implemented through the encrypt function, and the input of the encrypt function is , the returned ciphertext is (a(x), b(x)), which is used to encrypt the plaintext data into a ciphertext using the secret key.

[0093] Encryption operation: In the HEAAN algorithm, the plaintext polynomial can be converted into an encrypted polynomial through an encryption algorithm. Each coefficient of the encrypted polynomial is homomorphically encrypted, thus ensuring the security of the encrypted data.

[0094] Encryption operation functions include:

[0095] Homomorphic addition add function: input two ciphertexts and return the addition result of the two ciphertexts.

[0096] Homomorphic transformation - split square function: input a ciphertext and return the split result of the ciphertext, which is used to convert the encrypted data into two encrypted ciphertexts. Converting one data into two similar metadata increases the complexity of the data.

[0097] Homomorphic multiplication mult function: Input two ciphertexts and return the multiplication result of the ciphertexts, which is used for the multiplication operation of two encrypted data.

[0098] Homomorphic rotation rotate function: input a ciphertext and return the rotated ciphertext, which is used to rotate the encrypted data.

[0099] Decryption process: In the HEAAN algorithm, the decryption operation is obtained by inversely transforming the coefficients of the encryption polynomial. The decryption process can restore the coefficients of the plaintext polynomial to obtain the final plaintext result.

[0100] Optionally, the decryption function implements decryption. The input of the decrypt function is (a(x), b(x)), and the returned plaintext is , used to decrypt the ciphertext data into a plaintext using the secret key.

[0101] It should be noted that the algorithm parameters of the HEAAN algorithm are pre-configured, for example, , and the standard deviation of the Gaussian distribution . Based on historical data, the algorithm parameters are dynamically adjusted to adjust the encryption deviation and achieve higher security.

[0102] Based on this, Figure 5 A specific implementation flow chart of a credit line evaluation method provided in an embodiment of the present application is as follows: Figure 5 As shown, this method specifically includes:

[0103] S501. The data source end obtains original data of the party to be granted credit in response to the credit business application of the party to be granted credit, and performs data preprocessing on the original data to obtain the credit information to be evaluated of the party to be granted credit.

[0104] In this embodiment, the original data includes preset credit assessment indicators and corresponding indicator values. The credit assessment indicators are indicators that need to participate in credit assessment, such as the historical credit limit of the business, the registered capital of the party to be granted credit, etc.

[0105] Specifically, the data source and the party to be granted credit pre-agree on a number of credit assessment indicators for credit assessment. After receiving the credit business application from the party to be granted credit, the data source obtains the customer data of the party to be granted credit from a pre-configured database, and obtains original data from the customer data based on the pre-agreed credit assessment indicators, wherein the database stores the customer data of the party to be granted credit, and optionally, the customer data includes historical credit business information, customer information and other data.

[0106] In this embodiment, data preprocessing includes data cleaning operations, data conversion operations, and data encoding operations.

[0107] In this embodiment, the data cleaning operation is used to remove errors, missing values, and outliers from the original data, including data cleaning, filling missing values, processing outliers, etc., to ensure the quality and accuracy of the data.

[0108] In this embodiment, the data conversion operation is used to convert the original data so that the original data meets the requirements of the model or reduces the complexity of the data. For example, the original data is logarithmically transformed, exponentially transformed, polynomially transformed, etc., in order to change the distribution form of the original data and extract more useful information.

[0109] In this embodiment, the data encoding operation is used to convert the categorical variables or text data in the original data into numerical values ​​to obtain the corresponding numerical form. The data encoding operation includes methods such as one-hot encoding and label encoding.

[0110] S502: The data source extracts features from the credit information to be evaluated of the credit granting party, determines target indicators in the credit information to be evaluated, and obtains target credit information.

[0111] In this embodiment, the target credit information includes a target indicator and a corresponding indicator value.

[0112] In this embodiment, various indicators in the credit information to be evaluated are analyzed through statistical analysis, feature correlation analysis, domain knowledge and other methods to obtain the first type of target indicators, that is, key indicators, and the second type of target indicators are obtained through the indicator configuration information of the customer to be granted credit, wherein the indicator configuration information of the customer to be granted credit includes the correspondence between the credit business and the encrypted credit indicator, wherein the encrypted credit indicator corresponding to the credit business is the credit indicator that the customer to be granted credit requires to be encrypted when applying for the credit business.

[0113] It should be noted that the data source obtains the credit information to be evaluated through S501 and S502, and distinguishes the target credit information that needs to be encrypted and the common credit information that does not need to be encrypted in the credit information to be evaluated. Taking the credit business as the financing business as an example, Table 1 illustrates various credit evaluation indicators in the credit information to be evaluated.

[0114] Table 1 Credit Assessment Index Table

[0115] It should be noted that Table 1 illustrates various credit assessment indicators in the credit information to be assessed for credit business applications, including target indicators and common indicators, and the target indicators require encrypted interaction.

[0116] S503: The data source calls the HEAAN algorithm library to generate a key.

[0117] In this embodiment, the key includes a public key and a private key. The method for the data source end to generate the key of the HEAAN algorithm specifically includes:

[0118] (1) Parameter setting: Select the parameters required by the HEAAN algorithm, including polynomial ring parameters, security parameters, and approximate number encoding parameters.

[0119] (2) Master key generation: Generate a master key, which is usually a large randomly generated integer.

[0120] (3) Key derivation: Generate public and private keys based on the master key using a key derivation algorithm. The key derivation algorithm includes operations on a polynomial ring and random number generation.

[0121] (4) Public key generation: Generate a public key based on the key derivation result. The public key consists of a set of polynomials in a polynomial ring.

[0122] (5) Private key generation: Generate a private key based on the key derivation result. The private key includes a set of polynomials in the polynomial ring and information related to the master key.

[0123] It should be noted that the decryption operation requires the use of a private key, so the security of the private key is of vital importance. The private key should be kept properly and only authorized users can perform decryption operations.

[0124] S504: The data source calls the HEAAN algorithm library to convert the target indicator in the target credit information into a polynomial.

[0125] In this embodiment, the construction of the polynomial is achieved through the encoding function pre-configured by the HEAAN algorithm library.

[0126] Specifically, the construction of the polynomial ring is realized by encoding the encode function, that is, data encoding. For example, the input of the encoding encode function is the corresponding indicator value of the target indicator. , the output is the polynomial m(x).

[0127] S505. The data source calls the HEAAN algorithm library to use the public key to homomorphically encrypt the polynomial to obtain the homomorphic encryption polynomial of each target indicator.

[0128] In this embodiment, the polynomial of each target indicator is encrypted using a public key through a pre-configured homomorphic encryption function to obtain a homomorphic encrypted polynomial of each target indicator.

[0129] S506: The data source sends the encrypted credit information and credit business information to the data evaluation end.

[0130] In this embodiment, the credit service information includes the identification of the party to be credited, the identification of the credit granting party and the identification of the credit service, and the encrypted credit information includes the homomorphic encryption polynomials of various target indicators.

[0131] S507. The data evaluation end obtains credit evaluation rules based on the credit business information, and configures homomorphic operation rules of the credit evaluation model based on the credit evaluation rules.

[0132] In this embodiment, different credit assessment rules are pre-configured for different types of credit businesses. The type of credit business is determined based on the identification of the party to be credited, the identification of the credit granting party and the identification of the credit business. By configuring different credit assessment rules for different types of credit businesses, the flexibility and real-time performance of credit assessment are improved, and the assessment of the credit limit of different types of credit businesses can be personalized, thereby improving the reliability of the assessment results.

[0133] S508. The data evaluation end calls the HEAAN algorithm library, and based on the credit evaluation model, performs homomorphic operations on the homomorphic encryption polynomials of various target indicators to obtain the ciphertext credit limit of the party to be granted credit.

[0134] In this embodiment, the credit assessment model is used to perform homomorphic operations on homomorphic encrypted polynomials of various target indicators based on preset homomorphic operation rules, and the homomorphic operations include homomorphic multiplication operations and homomorphic addition operations. The homomorphic operation rules are determined based on the assessment rules.

[0135] In this embodiment, by performing homomorphic addition operation on the homomorphic encryption polynomial of the target indicator, the addition operation can be implemented on the ciphertext. By performing homomorphic multiplication operation on the homomorphic encryption polynomial of the target indicator, the multiplication operation can be implemented on the ciphertext.

[0136] S509. The data evaluation terminal calls the HEAAN algorithm library, uses the private key to decrypt the ciphertext credit limit, and obtains the plaintext credit limit of the party to be granted credit.

[0137] In this embodiment, the specific method of using the private key to decrypt the ciphertext credit limit includes:

[0138] 1. Parameter setting: Select the algorithm parameters of the HEAAN algorithm, including polynomial ring parameters, security parameters, and approximate number encoding parameters.

[0139] 2. Cipher text input: Receive cipher text credit limit.

[0140] 3. Decryption operation: Use the private key and homomorphic decryption algorithm to decrypt the ciphertext credit limit to obtain the plaintext credit limit. The homomorphic decryption algorithm involves operations and decryption operations on polynomial rings. In the HEAAN algorithm, the decryption operation is obtained by inversely transforming the coefficients of the encryption polynomial. The decryption process can restore the coefficients of the plaintext polynomial to obtain the final plaintext result. Optionally, the decryption function implements decryption. For example, the input of the decrypt function is (a(x), b(x)), and the returned plaintext is , used to decrypt the ciphertext data into a plaintext using the secret key.

[0141] 4. Result output: Output the credit limit in plain text.

[0142] It should be noted that, since noise is introduced in the encryption operation, when the ciphertext credit limit is decrypted using the private key, the plaintext credit limit needs to be corrected to reduce the calculation error and restore the original plaintext result.

[0143] It can be seen from the above technical solution that a credit limit evaluation method provided in an embodiment of the present application is based on the HEAAN (Homomorphic Encryption for Arithmetic of Approximate Numbers) algorithm library, and uses the HEAAN encryption technology to solve the data security problem and the timeliness problem of evaluation logic operation during data interaction between the data source and the data evaluation end during the credit limit evaluation process, and realizes online real-time evaluation through evaluation rules through a credit evaluation model.

[0144] Figure 6 A specific framework diagram of a credit line evaluation provided in an embodiment of the present application, such as Figure 6 As shown, the historical transactions between the data source end, that is, the enterprise end as the data holder and the customer to be granted credit are stored in the database of the enterprise end in the form of data sets.

[0145] The data assessment end, that is, the financial institution as the data recipient, agrees with the enterprise in advance on the customer data indicators that need to be used (that is, the target indicators in the credit assessment indicators). After the customer data indicators are preprocessed, the plaintext indicators of the target indicators (a, b, c...) are obtained, which are encrypted by the enterprise through the HEAAN algorithm library, and the obtained ciphertext (including the homomorphic encryption polynomials f(a), f(b), f(c), f(...) of each target indicator) is transmitted to the financial institution. Since the customer data indicators are polynomials after encryption, that is, the financial institution does not perform other operations after obtaining the customer data indicators, that is, it decrypts the data, and cannot obtain accurate data before encryption, so that the customer data is protected.

[0146] After receiving the customer data indicators, the financial institution performs homomorphic encryption operations on the encrypted customer data indicators according to the evaluation rules to obtain the ciphertext results. Homomorphic encryption operations include homomorphic addition operations and homomorphic multiplication operations. For example, the homomorphic encryption operation is P=f(a)+f(b)×f(c)×coefficient+C. The result P is the encryption result of the credit line after evaluation. The financial institution decrypts the ciphertext results and finally obtains the credit line after evaluation, that is, the plaintext target value f. The financial institution stores the plaintext target value in the data set. Among them, the evaluation rules can be edited by the rule editing module, and the rule editing module can provide an editing interface for the client to enable the account manager and others to edit the evaluation rules.

[0147] In summary, the HEAAN algorithm library supports data encryption, post-encryption operations, decryption and other operations. The system is constructed by this algorithm library, and the functional classification of the system can be roughly divided into two categories: system configuration and rule editing. System configuration is mainly used to configure system-level parameters. This part requires advance agreement between the financial, corporate and customer parties to reach an agreement on relevant parameters, such as dictionaries, parameters, etc. Rule editing is mainly for system users, providing financial institution users with the credit rule entry function stipulated by financial institutions, which can support addition, subtraction, multiplication, division and complex polynomial operations.

[0148] In addition, most existing evaluation methods are based on pre-set models for real-time evaluation and calculation, and cannot be adjusted in real time with market changes. This application uses a dynamically editable evaluation model to implement credit line evaluation with complex operation rules. Therefore, this application can take into account both data privacy protection and the credit line evaluation with complex operation rules of various financial institutions' credit models. Improve the reliability and flexibility of the evaluation.

[0149] The above describes a credit line evaluation method provided by an embodiment of the present application. The following describes a system for executing the credit line evaluation method.

[0150] See also Figure 7 , Figure 7 This is a schematic diagram of a credit line evaluation system provided in an embodiment of the present application. Figure 7 As shown, the credit line evaluation system 700 includes a data source end and a data evaluation end:

[0151] The data source end is used to: obtain target credit information of the party to be granted credit, wherein the target credit information includes target indicators and corresponding indicator values; use the public key to homomorphically encrypt each of the target indicators to obtain the homomorphically encrypted polynomials of each of the target indicators; send the encrypted credit information to the data evaluation end, wherein the encrypted credit information includes the homomorphically encrypted polynomials of each of the target indicators;

[0152] The data evaluation end is used to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted credit; use a private key to decrypt the ciphertext credit limit of the party to be granted credit to obtain the plaintext credit limit of the party to be granted credit.

[0153] In a possible implementation, the credit limit assessment system further includes: a pre-configured HEAAN algorithm library, wherein the HEAAN algorithm library is pre-configured with a homomorphic encryption function, a homomorphic operation function, and a homomorphic decryption function;

[0154] The data source end is specifically used to use the public key to perform homomorphic encryption on each of the target indicators, and when the homomorphic encryption polynomials of the target indicators are obtained, it is specifically used to call the HEAAN algorithm library to use the public key to perform homomorphic encryption on each of the target indicators, and obtain the homomorphic encryption polynomials of the target indicators;

[0155] The data evaluation end is used to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted; when using a private key to decrypt the ciphertext credit limit of the party to be granted to obtain the plaintext credit limit of the party to be granted, it is specifically used to call the HEAAN algorithm library to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted; and use a private key to decrypt the ciphertext credit limit of the party to be granted to obtain the plaintext credit limit of the party to be granted.

[0156] The present application also provides an electronic device in an embodiment. Figure 8 As shown, it shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiment of the present application. The electronic device in the embodiment of the present application may include but is not limited to fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 8The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0157] like Figure 8 As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage device 808 to a random access memory (RAM) 803. When the electronic device is powered on, various programs and data required for the operation of the electronic device are also stored in the RAM 803. The processing device 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0158] Typically, the following devices may be connected to the I / O interface 805: input devices 806 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 807 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 808 including, for example, a memory card, a hard disk, etc.; and communication devices 809. The communication device 809 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Although Figure 8 An electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0159] An embodiment of the present application also provides a computer program product including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any credit limit assessment method provided in the embodiment of the present application.

[0160] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any credit limit assessment method provided in the embodiment of the present application.

[0161] It should also be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present application, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.

[0162] Through the description of the above implementation mode, the technicians in the field can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course, it can also be implemented by special hardware including special integrated circuits, special CPUs, special memories, special components, etc. In general, all functions completed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be various, such as analog circuits, digital circuits or special circuits. However, for the present application, software program implementation is a better implementation mode in more cases. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer floppy disk, a U disk, a mobile hard disk, a ROM, a RAM, a disk or an optical disk, etc., including a number of instructions to enable a computer device (which can be a personal computer, a training device, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0163] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0164] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, a computer, a training device, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, training device, or data center. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium may be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)), etc.

Claims

1. A credit line assessment method, characterized in that: include: The data source end obtains the target credit information of the party to be granted credit, wherein the target credit information includes a target indicator and a corresponding indicator value; The data source uses a public key to homomorphically encrypt each target indicator to obtain a homomorphic encryption polynomial of each target indicator; The data source sends the encrypted credit information to the data evaluation end, wherein the encrypted credit information includes the homomorphic encryption polynomials of each target indicator; The data evaluation terminal performs homomorphic operations on homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain a ciphertext credit limit of the party to be granted credit; The data evaluation terminal uses a private key to decrypt the ciphertext credit limit of the party to be granted credit, and obtains the plaintext credit limit of the party to be granted credit.

2. The credit line evaluation method according to claim 1, characterized in that: The data source obtains target credit information of the party to be credited, including: The data source end obtains the original data of the party to be granted credit in response to the credit business application of the party to be granted credit, and performs data preprocessing on the original data to obtain the credit information to be evaluated of the party to be granted credit; wherein the original data includes a preset credit evaluation index and a corresponding index value, and the data preprocessing includes a data cleaning operation, a data conversion operation, and a data encoding operation The data source extracts features of the credit information to be evaluated of the party to be granted credit, determines target indicators in the credit information to be evaluated, and obtains the target credit information.

3. The credit line evaluation method according to claim 1, characterized in that: The data source uses a public key to homomorphically encrypt each target indicator to obtain a homomorphic encryption polynomial of each target indicator, including: The data source end calls the HEAAN algorithm library to generate a key, wherein the key includes the private key and the public key; the HEAAN algorithm library is pre-configured with a homomorphic encryption function, a homomorphic operation function, and a homomorphic decryption function; The data source end calls the HEAAN algorithm library to convert each target indicator into a polynomial; The data source calls the HEAAN algorithm library and uses the public key to homomorphically encrypt the polynomials of each target indicator to obtain the homomorphic encrypted polynomials of each target indicator.

4. The credit line evaluation method according to claim 3, characterized in that: The data source sends the encrypted credit information to the data evaluation end, including: The data source sends the encrypted credit information and credit business information to the data evaluation end, and the credit business information includes the identification of the party to be credited, the identification of the crediting party and the identification of the credit business.

5. The credit line evaluation method according to claim 4, characterized in that: The data evaluation terminal performs homomorphic operations on the homomorphic encryption polynomials of the target indicators based on the pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be credited, including: The data evaluation terminal obtains a credit evaluation rule based on the credit business information, and configures a homomorphic operation rule of the credit evaluation model based on the credit evaluation rule; The data evaluation end calls the HEAAN algorithm library, and based on the credit evaluation model, performs homomorphic operations on the homomorphic encryption polynomials of each target indicator to obtain the ciphertext credit limit of the party to be credited.

6. A credit line evaluation system, characterized in that: include: Data source side and data evaluation side; The data source end is used to: obtain target credit information of the party to be granted credit, wherein the target credit information includes target indicators and corresponding indicator values; use the public key to homomorphically encrypt each of the target indicators to obtain the homomorphically encrypted polynomials of each of the target indicators; send the encrypted credit information to the data evaluation end, wherein the encrypted credit information includes the homomorphically encrypted polynomials of each of the target indicators; The data evaluation end is used to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted credit; use a private key to decrypt the ciphertext credit limit of the party to be granted credit to obtain the plaintext credit limit of the party to be granted credit.

7. The credit line evaluation system according to claim 6, characterized in that: The credit line evaluation system further includes: a pre-configured HEAAN algorithm library, wherein the HEAAN algorithm library is pre-configured with a homomorphic encryption function, a homomorphic operation function, and a homomorphic decryption function; The data source end is specifically used to use the public key to perform homomorphic encryption on each of the target indicators, and when the homomorphic encryption polynomials of the target indicators are obtained, it is specifically used to call the HEAAN algorithm library to use the public key to perform homomorphic encryption on each of the target indicators, and obtain the homomorphic encryption polynomials of the target indicators; The data evaluation end is used to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted; when using a private key to decrypt the ciphertext credit limit of the party to be granted to obtain the plaintext credit limit of the party to be granted, it is specifically used to call the HEAAN algorithm library to perform homomorphic operations on the homomorphic encrypted polynomials of each target indicator based on a pre-configured credit evaluation model to obtain the ciphertext credit limit of the party to be granted; and use a private key to decrypt the ciphertext credit limit of the party to be granted to obtain the plaintext credit limit of the party to be granted.

8. A computer program product, characterized in that It includes computer-readable instructions, and when the computer-readable instructions are executed on an electronic device, the electronic device implements the credit limit evaluation method as described in any one of claims 1 to 5.

9. An electronic device, characterized in that: The method comprises at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the credit limit evaluation method as described in any one of claims 1 to 5.

10. A computer storage medium, characterized in that: The storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the credit limit assessment method as described in any one of claims 1 to 5.

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