WO2022134760A1

WO2022134760A1 - Data processing method and apparatus, and electronic device and medium

Info

Publication number: WO2022134760A1
Application number: PCT/CN2021/123903
Authority: WO
Inventors: 王梦寒
Original assignee: 深圳壹账通智能科技有限公司
Priority date: 2020-12-21
Filing date: 2021-10-14
Publication date: 2022-06-30
Also published as: CN112651035A

Abstract

A data processing method, a data processing apparatus, an electronic device and a storage medium. The method comprises: acquiring an original service data set, and performing encryption processing on the original service data set, so as to obtain an encrypted service data set and a decryption private key corresponding to the encrypted service data set (S1); storing the encrypted service data set and the decryption private key in different nodes of a blockchain according to information features of the encrypted service data set (S2); when a data calling request is received, performing permission validation on the data calling request (S3); when the permission validation is passed, calling the decryption private key in a blockchain node (S4); and decrypting the encrypted service data set by using the decryption private key, acquiring the original service data set, and performing transaction processing on the original service data set according to a pre-set service rule, so as to obtain a transaction result (S5). The problem of the low accuracy of traditional data processing can be solved.

Description

Data processing method, apparatus, electronic device and medium

This application claims the priority of the Chinese patent application with the application number CN202011519829.4 and the invention titled "Data Processing Method, Device, Electronic Device and Medium", which was filed with the China Patent Office on December 21, 2020, the entire contents of which are by reference Incorporated in this application.

technical field

With the development of the Internet, more and more data are generated on the network. In the prior art, the data in the network is usually used for data processing such as user analysis, data push, or user business processing. The inventor realizes that in the process of data processing, the accuracy of the data processing results is very important, which is related to the effectiveness of further data operations. Therefore, there is an urgent need for a method for improving the accuracy of data processing.

SUMMARY OF THE INVENTION

A data processing method comprising:

Obtaining an original service data set, performing encryption processing on the original service data set, and obtaining an encrypted service data set and a decryption private key corresponding to the encrypted service data set;

According to the information characteristics of the encrypted business data set, the encrypted business data set and the decryption private key are respectively stored in different nodes of the blockchain;

When receiving the data invocation request for the original service data set, perform permission verification on the data invocation request;

When the authority verification is passed, the decryption private key in the blockchain node is called;

Decrypt the encrypted service data set by using the decryption private key to obtain the original service data set, and perform transaction processing on the original service data set according to preset service rules to obtain a transaction result.

A data processing device comprising:

an encryption module, configured to obtain an original service data set, perform encryption processing on the original service data set, and obtain an encrypted service data set and a decryption private key corresponding to the encrypted service data set;

a blockchain storage module, configured to store the encrypted business data set and the decryption private key in different nodes of the blockchain respectively according to the information characteristics of the encrypted business data set;

an authority verification module, configured to perform authority verification on the data invocation request when receiving a data invocation request for the original service data set;

a decryption private key invocation module, configured to perform authority verification on the data invocation request when receiving a data invocation request for the original service data set;

A transaction processing module, configured to decrypt the encrypted business data set by using the decryption private key, obtain the original business data set, and perform transaction processing on the original business data set according to preset business rules to obtain a transaction result .

An electronic device comprising:

at least one processor; and,

a memory communicatively coupled to the at least one processor; wherein,

The memory stores computer program instructions executable by the at least one processor, the computer program instructions being executed by the at least one processor to enable the at least one processor to perform the steps of:

A computer-readable storage medium storing a computer program, the computer program implements the following steps when executed by a processor:

The present application can improve the accuracy of data processing.

Description of drawings

1 is a schematic flowchart of a data processing method provided by an embodiment of the present application;

FIG. 2 is a schematic block diagram of a data processing apparatus provided by an embodiment of the present application;

FIG. 3 is a schematic diagram of an internal structure of an electronic device implementing a data processing method provided by an embodiment of the present application.

The realization, functional characteristics and advantages of the purpose of the present application will be further described with reference to the accompanying drawings in conjunction with the embodiments.

Detailed ways

It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.

The embodiments of the present application provide a data processing method, and the execution subject of the data processing method includes but is not limited to at least one of electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiments of the present application. In other words, the data processing method can be executed by software or hardware installed in a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.

The embodiments of the present application may acquire and process related data based on artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. .

The basic technologies of artificial intelligence generally include technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation/interaction systems, and mechatronics. Artificial intelligence software technology mainly includes computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning/deep learning.

Referring to FIG. 1 , it is a schematic flowchart of a data processing method provided by an embodiment of the present application. In this embodiment, the data processing method includes:

S1. Obtain an original service data set, perform encryption processing on the original service data set, and obtain an encrypted service data set and a decryption private key corresponding to the encrypted service data set.

In an embodiment of the present application, the original business data set is a car-related data set. Specifically, the original business data set includes but is not limited to car driving data, operation data, and mileage data.

In an optional embodiment of the present application, the existing On Board Diagnostics (OBD, on-board diagnostic system) equipment of the Internet of Vehicles can be used to collect data through an interface to obtain the original service data set.

Specifically, performing encryption processing on the original service data set to obtain the encrypted service data set and the decryption private key corresponding to the encrypted service data set, including:

Obtain any two different prime numbers, perform asymmetric calculation processing on the prime numbers, and obtain a first encryption key and a first decryption private key;

The original service data set is encrypted by using the first encryption key to obtain an encrypted service data set, and the first decryption private key is determined as the decryption private key corresponding to the encrypted service data set.

Preferably, the prime number is a prime number whose value is greater than a preset value.

Further, obtaining any two different prime numbers, performing asymmetric calculation processing on the prime numbers, and obtaining a first encryption key and a first decryption private key, including:

For any two different prime numbers p and q, calculate the product n=pq,

An integer e is arbitrarily selected such that the integer e satisfies

The e is the first encryption key;

An integer d is arbitrarily selected, such that the integer d satisfies

The d is the first decryption private key.

In detail, after encrypting the original service data set by using the asymmetric algorithm, an encrypted service data set (that is, an encrypted service data set) and a corresponding decryption private key are generated. Only by decrypting the private key can the encrypted business data set be decrypted, which improves the security of data storage and also improves the authenticity and reliability of the obtained business data.

The embodiment of the present application encrypts the original service data, so that even if a third party illegally obtains the data without authorization, the real original service data cannot be parsed from the illegally obtained data, thereby increasing the security of the data.

S2. Store the encrypted service data set and the decryption private key in different nodes of the blockchain respectively according to the information characteristics of the encrypted service data set.

Preferably, in the embodiment of the present application, the blockchain includes a first blockchain node, a second blockchain node, a third blockchain node, an N-1th blockchain node, and an Nth blockchain node. node, where N is a positive integer, and the value of N can be preset. Each blockchain node is connected to each other to form a cross-chain network together, and each blockchain node can transmit information to each other and update at the same time.

Preferably, in the embodiment of the present application, the node of the blockchain includes an automobile device that generates the automobile-related data set.

For example, when the blockchain contains multiple nodes, each different node corresponds to the same or different car units on different cars.

In the embodiment of the present application, the business data stored in each blockchain node is encrypted with an independent key, so as to realize the authorization management of personal data on the blockchain.

In the embodiment of the present application, the data stored in each blockchain node is encrypted by using a symmetric key method. The advantage of the symmetric key encryption method is that the encryption speed and decryption speed are fast, which can improve the efficiency of encrypting a large amount of data. .

For example, the data stored in each blockchain node is encrypted with an independent key, so as to realize the authorization management of personal data on the blockchain and solve the refined management and control of personal data.

In the embodiment of the present application, the storage of the encrypted service data and the decrypted private key in different nodes of the blockchain according to the information characteristics includes:

Step a, extracting the information features of the encrypted service data set, and classifying the encrypted service data set according to the information features;

Step b. Store the classified encrypted service data set and the decryption private key corresponding to the encrypted service data set in different nodes of the blockchain, respectively.

Wherein, in the embodiment of the present application, the information feature refers to the property of the original business data set, or the category of the original business data set, for example, the property of the driving data of the car, or the mileage data of the car.

The encrypted business data set is stored in different nodes of the blockchain according to its information characteristics, so that the data in the blockchain can be called directly according to the nature of the original business data set or the original business data. The category-selective call of the set improves the efficiency of data acquisition.

Further, before extracting the information features of the encrypted service data set, the method further includes: training an information feature extraction model with an information feature extraction function.

In the embodiment of the present application, the information feature extraction model can identify the information feature of the encrypted service data set.

Specifically, the training process of the information feature extraction model includes:

Step A: obtaining the training data set and the standard result corresponding to the training data set;

Step B: inputting the training data set into a pre-built information feature extraction model for information feature extraction to obtain a training result;

Step C: using a preset loss function to calculate the loss value of the training result and the standard result to obtain the loss value;

Step D: when the loss value is greater than or equal to a preset loss threshold, adjust the parameters of the information feature extraction model until the loss value is less than the loss threshold, and obtain a standard information feature extraction model;

Step E: Extract the information features of the encrypted data by using the standard information feature extraction model.

In detail, the embodiment of the present application uses the following loss function to calculate the loss value of the training result and the preset target result to obtain the loss value:

in,

is the loss value,

is the training result, Y is the standard result, and α is the error factor, which is a preset constant.

In the embodiment of the present application, the information feature extraction is performed on the encrypted service data set by training the information feature extraction model, and the training model can improve the accuracy of data extraction and avoid errors in manual data extraction.

S3. When a data invocation request for the original service data set is received, perform permission verification on the data invocation request.

In this embodiment of the present application, the data invocation request for the original service data set refers to a request sent by a third party for invoking the original service data set.

Specifically, the performing permission verification on the data call request includes:

Obtain the requester name of the data call request, and a preset authority verification table, wherein the preset authority verification table includes a set of trusted names;

Judging whether the requester name is in the set of trusted names;

If it exists, confirm that the authorization verification is passed;

If it does not exist, it is determined that the authorization verification has not passed.

In this embodiment of the present application, the name of the requester may be the name of an organization that sends a data call request, and the preset authority verification table stores one or more names of organizations that allow data call.

S4. When the authority verification is passed, the decryption private key in the blockchain node is called.

Specifically, when the authority verification is passed, the decryption private key corresponding to the encrypted service data set is called, that is, if the original service data set is encrypted by the first encryption key, the first decryption private key is called at this time. .

In the embodiment of this application, the decryption private key in the blockchain node is called only when the authority verification is passed, so that the requester who can call the decryption private key is authorized, not any requester can call, which improves the data call process security.

In detail, the authority verification of the requesting party can either verify that it is generally used once, that is, verify it every time a data call request is received; it can also be checked for an unlimited number of times within a period of time after passing the verification once. , that is, when the data request sent by the same requester is received again after the verification is passed within a period of time, the requester will not be verified again.

For example, during specific implementation, different requesting parties can be authorized to access business data through a transaction authorization operation in advance, and the transaction authorization operation includes writing the data location, authority scope, and authority period user's key into the blockchain. in the cloud storage system.

S5. Decrypt the encrypted service data set by using the decryption private key to obtain the original service data set, and perform transaction processing on the original service data set according to preset service rules to obtain a transaction result.

For example, the data contained in the original business data set is the mileage data of the car and the point data of the car, and the preset business rule is the exchange relationship between the mileage data and the point data, for example, the exchange relationship is "Mileage data: point data = 1:3", when the handover process is performed, the mileage data is exchanged and calculated according to the exchange relationship of 1:3, and the point data is obtained.

In the embodiment of the present application, storing the original business data set in the blockchain according to its information characteristics can not only improve the security and confidentiality of the original business data set, but also prevent the data from being easily leaked during centralized storage. In addition, through authority verification, it avoids the situation that anyone can call the data. At the same time, after decrypting the encrypted business data set with the decryption private key, the obtained original business data set can be processed for transaction processing. , to ensure the accuracy of data transactions.

As shown in FIG. 2 , it is a schematic diagram of a module of a data processing apparatus provided by an embodiment of the present application.

The data processing apparatus 100 described in this application may be installed in an electronic device. According to the realized functions, the data processing apparatus 100 may include an encryption module 101 , a blockchain storage module 102 , an authority verification module 103 , a decryption private key invocation module 104 and a transaction processing module 105 . The modules described in this application may also be referred to as units, which refer to a series of computer program segments that can be executed by the processor of an electronic device and can perform fixed functions, and are stored in the memory of the electronic device.

In this embodiment, the functions of each module/unit are as follows:

The encryption module 101 is configured to obtain an original service data set, perform encryption processing on the original service data set, and obtain an encrypted service data set and a decryption private key corresponding to the encrypted service data set;

The blockchain storage module 102 is configured to store the encrypted service data set and the decryption private key in different nodes of the blockchain respectively according to the information characteristics of the encrypted service data set;

The authority verification module 103 is configured to perform authority verification on the data invocation request when receiving a data invocation request for the original service data set;

The decryption private key invocation module 104 is configured to perform authority verification on the data invocation request when receiving a data invocation request for the original service data set;

The transaction processing module 105 is configured to decrypt the encrypted business data set by using the decryption private key, obtain the original business data set, and perform transaction processing on the original business data set according to preset business rules, Get the transaction result.

In detail, the specific implementation of each module of the data processing apparatus 100 is as follows:

The encryption module 101 is configured to obtain an original service data set, perform encryption processing on the original service data set, and obtain an encrypted service data set and a decryption private key corresponding to the encrypted service data set.

Further, described obtaining any two different prime numbers, carry out asymmetric calculation processing to the described prime numbers, obtain the first encryption key and the first decryption private key, including:

For any two different prime numbers p and q, calculate the product n=pq,

An integer e is arbitrarily selected such that the integer e satisfies

The e is the first encryption key;

An integer d is arbitrarily selected, such that the integer d satisfies

The d is the first decryption private key.

The blockchain storage module 102 is configured to store the encrypted service data set and the decryption private key respectively in different nodes of the blockchain according to the information characteristics of the encrypted service data set.

In this embodiment of the present application, the blockchain storage module 102 is specifically used for:

extracting information features of the encrypted service data set, and classifying the encrypted service data set according to the information features;

The classified encrypted service data set and the decryption private key corresponding to the encrypted service data set are respectively stored in different nodes of the blockchain.

Further, the apparatus further includes a training module configured to train an information feature extraction model with an information feature extraction function before extracting the information feature of the encrypted service data set.

Optionally, the training module is specifically used for:

Obtain the training data set and the standard result corresponding to the training data set;

Inputting the training data set into a pre-built information feature extraction model for information feature extraction to obtain a training result;

Using a preset loss function to calculate the loss value of the training result and the standard result to obtain the loss value;

When the loss value is greater than or equal to a preset loss threshold, adjust the parameters of the information feature extraction model until the loss value is less than the loss threshold, and obtain a standard information feature extraction model;

The information features of the encrypted data are extracted by using the standard information feature extraction model.

in,

is the loss value,

The authority verification module 103 is configured to perform authority verification on the data invocation request when a data invocation request for the original service data set is received.

Judging whether the requester name is in the set of trusted names;

If it exists, confirm that the authorization verification is passed;

The decryption private key calling module 104 is configured to call the decryption private key in the blockchain node when the authority verification is passed.

Specifically, when the authority verification is passed, the decryption private key corresponding to the encrypted service data set is called, that is, if the original service data set is encrypted by the first encryption key, the first decryption key is called at this time. private key.

As shown in FIG. 3 , it is a schematic structural diagram of an electronic device implementing the data processing method of the present application.

The electronic device 1 may include a processor 10, a memory 11 and a bus, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a data processing program 12.

Wherein, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, magnetic disk, CD etc. The memory 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1 . In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a pluggable mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital) equipped on the electronic device 1. , SD) card, flash memory card (Flash Card), etc. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software installed in the electronic device 1 and various types of data, such as codes of the data processing program 12, etc., but also can be used to temporarily store data that has been output or will be output.

In some embodiments, the processor 10 may be composed of integrated circuits, for example, may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits packaged with the same function or different functions, including one or more integrated circuits. Central Processing Unit (CPU), microprocessor, digital processing chip, graphics processor and combination of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect the various components of the entire electronic device, by running or executing the program or module (for example, executing the program) stored in the memory 11. data processing programs, etc.), and call data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

The bus may be a peripheral component interconnect (PCI for short) bus or an extended industry standard architecture (Extended industry standard architecture, EISA for short) bus or the like. The bus can be divided into address bus, data bus, control bus and so on. The bus is configured to implement connection communication between the memory 11 and at least one processor 10 and the like.

FIG. 3 only shows an electronic device with components. Those skilled in the art can understand that the structure shown in FIG. 3 does not constitute a limitation on the electronic device 1, and may include fewer or more components than those shown in the figure. components, or a combination of certain components, or a different arrangement of components.

For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) for powering the various components, preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that the power management The device implements functions such as charge management, discharge management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and any other components. The electronic device 1 may further include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

Further, the electronic device 1 may also include a network interface, optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used in the electronic device 1 Establish a communication connection with other electronic devices.

Optionally, the electronic device 1 may further include a user interface, and the user interface may be a display (Display), an input unit (eg, a keyboard (Keyboard)), optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, and the like. The display may also be appropriately called a display screen or a display unit, which is used for displaying information processed in the electronic device 1 and for displaying a visualized user interface.

It should be understood that the embodiments are only used for illustration, and are not limited by this structure in the scope of the patent application.

The data processing program 12 stored in the memory 11 in the electronic device 1 is a combination of multiple instructions, and when running in the processor 10, it can realize:

Further, if the modules/units integrated in the electronic device 1 are implemented in the form of software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. The computer-readable storage medium may be volatile or non-volatile, and the computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, removable hard disk , disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory).

Further, the computer-usable storage medium may mainly include a stored program area and a stored data area, wherein the stored program area may store an operating system, an application program required by at least one function, and the like; Using the created data, etc., the application program implements the following steps when executed by the processor:

In the several embodiments provided in this application, it should be understood that the disclosed apparatus, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other division manners in actual implementation.

The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional module in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware, or can be implemented in the form of hardware plus software function modules.

It will be apparent to those skilled in the art that the present application is not limited to the details of the above-described exemplary embodiments, but that the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application.

Accordingly, the embodiments are to be regarded in all respects as illustrative and not restrictive, and the scope of the application is to be defined by the appended claims rather than the foregoing description, which is therefore intended to fall within the scope of the claims. All changes within the meaning and scope of the equivalents of , are included in this application. Any accompanying reference signs in the claims should not be construed as limiting the involved claims.

Furthermore, it is clear that the word "comprising" does not exclude other units or steps and the singular does not exclude the plural. A plurality of units or means recited in the system claims can also be implemented by one unit or means by software or hardware. Second-class terms are used to denote names and do not denote any particular order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and not to limit them. Although the present application has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present application can be Modifications or equivalent substitutions can be made without departing from the spirit and scope of the technical solutions of the present application.

Claims

A data processing method, wherein the method comprises:

Obtaining an original service data set, performing encryption processing on the original service data set, and obtaining an encrypted service data set and a decryption private key corresponding to the encrypted service data set;

According to the information characteristics of the encrypted business data set, the encrypted business data set and the decryption private key are respectively stored in different nodes of the blockchain;

When receiving the data invocation request for the original service data set, perform permission verification on the data invocation request;

When the authority verification is passed, the decryption private key in the blockchain node is called;

Decrypt the encrypted service data set by using the decryption private key to obtain the original service data set, and perform transaction processing on the original service data set according to preset service rules to obtain a transaction result.
The data processing method according to claim 1, wherein, performing encryption processing on the original service data set to obtain an encrypted service data set and a decryption private key corresponding to the encrypted service data set, comprising:

Obtain any two different prime numbers, perform asymmetric calculation processing on the prime numbers, and obtain a first encryption key and a first decryption private key;

The original service data set is encrypted by using the first encryption key to obtain an encrypted service data set, and the first decryption private key is determined as the decryption private key corresponding to the encrypted service data set.
The data processing method according to claim 2, wherein the original business data set is a car-related data set, and the node of the blockchain comprises an automobile device that generates the car-related data set.
The data processing method according to claim 1, wherein, according to the information characteristics of the encrypted service data set, the encrypted service data set and the decryption private key are respectively stored in different nodes of the blockchain, including :

extracting information features of the encrypted service data set, and classifying the encrypted service data set according to the information features;

The classified encrypted service data set and the decryption private key corresponding to the encrypted service data set are respectively stored in different nodes of the blockchain.
The data processing method according to claim 4, wherein, before extracting the information features of the encrypted data, training an information feature extraction model with an information feature extraction function, comprising:

Obtain the training data set and the standard result corresponding to the training data set;

Inputting the training data set into a pre-built information feature extraction model for information feature extraction to obtain a training result;

Using a preset loss function to calculate the loss value of the training result and the standard result to obtain the loss value;

When the loss value is greater than or equal to a preset loss threshold, the parameters of the information feature extraction model are adjusted until the loss value is less than the loss threshold, and a standard information feature extraction model is obtained.
The data processing method according to claim 5, wherein the loss value calculation is performed on the training result and the standard result by using a preset loss function to obtain the loss value, comprising:

in,
is the loss value,
is the training result, Y is the standard result, and α is the error factor, which is a preset constant.
The data processing method according to any one of claims 1 to 6, wherein the performing permission verification on the data calling request comprises:

Obtain the requester name of the data call request, and a preset authority verification table, wherein the preset authority verification table includes a set of trusted names;

Judging whether the requester name is in the set of trusted names;

If it exists, confirm that the authorization verification is passed;

If it does not exist, it is determined that the authorization verification has not passed.
A data processing device, wherein the device comprises:

an encryption module, configured to obtain an original service data set, perform encryption processing on the original service data set, and obtain an encrypted service data set and a decryption private key corresponding to the encrypted service data set;

a blockchain storage module, configured to store the encrypted business data set and the decryption private key in different nodes of the blockchain respectively according to the information characteristics of the encrypted business data set;

an authority verification module, configured to perform authority verification on the data invocation request when receiving a data invocation request for the original service data set;

a decryption private key invocation module, configured to perform authority verification on the data invocation request when receiving a data invocation request for the original service data set;

A transaction processing module, configured to decrypt the encrypted business data set by using the decryption private key, obtain the original business data set, and perform transaction processing on the original business data set according to preset business rules to obtain a transaction result .
An electronic device, wherein the electronic device comprises:

at least one processor; and,

a memory communicatively coupled to the at least one processor; wherein,

The memory stores computer program instructions executable by the at least one processor, the computer program instructions being executed by the at least one processor to enable the at least one processor to perform the steps of:

Obtaining an original service data set, performing encryption processing on the original service data set, and obtaining an encrypted service data set and a decryption private key corresponding to the encrypted service data set;

According to the information characteristics of the encrypted business data set, the encrypted business data set and the decryption private key are respectively stored in different nodes of the blockchain;

When receiving the data invocation request for the original service data set, perform permission verification on the data invocation request;

When the authority verification is passed, the decryption private key in the blockchain node is called;

Decrypt the encrypted service data set by using the decryption private key to obtain the original service data set, and perform transaction processing on the original service data set according to preset service rules to obtain a transaction result.
The electronic device according to claim 9, wherein, performing encryption processing on the original service data set to obtain the encrypted service data set and the decryption private key corresponding to the encrypted service data set, comprising:

Obtain any two different prime numbers, perform asymmetric calculation processing on the prime numbers, and obtain a first encryption key and a first decryption private key;

The original service data set is encrypted by using the first encryption key to obtain an encrypted service data set, and the first decryption private key is determined as the decryption private key corresponding to the encrypted service data set.
The electronic device according to claim 10, wherein the original business data set is a car-related data set, and the node of the blockchain comprises a car device that generates the car-related data set.
The electronic device according to claim 9, wherein storing the encrypted service data set and the decryption private key in different nodes of the blockchain according to the information characteristics of the encrypted service data set, comprising:

extracting information features of the encrypted service data set, and classifying the encrypted service data set according to the information features;

The classified encrypted service data set and the decryption private key corresponding to the encrypted service data set are respectively stored in different nodes of the blockchain.
The electronic device according to claim 12, wherein, before the information feature extraction of the encrypted data, the at least one processor further performs the step of training an information feature extraction model with an information feature extraction function, comprising:

Obtain the training data set and the standard result corresponding to the training data set;

Inputting the training data set into a pre-built information feature extraction model for information feature extraction to obtain a training result;

Using a preset loss function to calculate the loss value of the training result and the standard result to obtain the loss value;

When the loss value is greater than or equal to a preset loss threshold, the parameters of the information feature extraction model are adjusted until the loss value is less than the loss threshold, and a standard information feature extraction model is obtained.
The electronic device according to claim 13, wherein the loss value calculation is performed on the training result and the standard result by using a preset loss function, and the loss value is obtained, comprising:

in,
is the loss value,
is the training result, Y is the standard result, and α is the error factor, which is a preset constant.
The electronic device according to any one of claims 9 to 14, wherein the performing permission verification on the data calling request comprises:

Obtain the requester name of the data call request, and a preset authority verification table, wherein the preset authority verification table includes a set of trusted names;

Judging whether the requester name is in the set of trusted names;

If it exists, confirm that the authorization verification is passed;

If it does not exist, it is determined that the authorization verification has not passed.
A computer-readable storage medium storing a computer program, wherein the computer program implements the following steps when executed by a processor:

Obtaining an original service data set, performing encryption processing on the original service data set, and obtaining an encrypted service data set and a decryption private key corresponding to the encrypted service data set;

According to the information characteristics of the encrypted business data set, the encrypted business data set and the decryption private key are respectively stored in different nodes of the blockchain;

When receiving the data invocation request for the original service data set, perform permission verification on the data invocation request;

When the authority verification is passed, the decryption private key in the blockchain node is called;

Decrypt the encrypted service data set by using the decryption private key to obtain the original service data set, and perform transaction processing on the original service data set according to preset service rules to obtain a transaction result.
The computer-readable storage medium according to claim 16, wherein the performing encryption processing on the original service data set to obtain the encrypted service data set and the decryption private key corresponding to the encrypted service data set, comprising:

Obtain any two different prime numbers, perform asymmetric calculation processing on the prime numbers, and obtain a first encryption key and a first decryption private key;

The original service data set is encrypted by using the first encryption key to obtain an encrypted service data set, and the first decryption private key is determined as the decryption private key corresponding to the encrypted service data set.
The computer-readable storage medium of claim 17, wherein the original business data set is a car-related data set, and the nodes of the blockchain comprise car devices that generate the car-related data set.
The computer-readable storage medium according to claim 16, wherein the encrypted service data set and the decryption private key are respectively stored in different nodes of the blockchain according to the information characteristics of the encrypted service data set ,include:

extracting information features of the encrypted service data set, and classifying the encrypted service data set according to the information features;

The classified encrypted service data set and the decryption private key corresponding to the encrypted service data set are respectively stored in different nodes of the blockchain.
The computer-readable storage medium according to claim 19, wherein, before the extracting the information feature of the encrypted data, when the computer program is executed by the processor, the computer program further realizes the training of the information feature extraction model with the information feature extraction function. steps, including:

Obtain the training data set and the standard result corresponding to the training data set;

Inputting the training data set into a pre-built information feature extraction model for information feature extraction to obtain a training result;

Using a preset loss function to calculate the loss value of the training result and the standard result to obtain the loss value;

When the loss value is greater than or equal to a preset loss threshold, the parameters of the information feature extraction model are adjusted until the loss value is less than the loss threshold, and a standard information feature extraction model is obtained.