A blockchain-based outsourced trusted computing method, system, and storage medium

Abstract

The present invention provides a blockchain-based outsourced trusted computing method, system, and storage medium, relating to the field of outsourced computing technology. The method includes: constructing an outsourced trusted computing system, wherein the outsourced trusted computing system includes a computing power resource pool, a computing service platform, and a verification platform; sharding the computing task to obtain multiple sharding tasks, generating multiple random numbers, and performing computational redundancy analysis; randomly and redundantly distributing the multiple sharding tasks to multiple outsourced computing nodes based on computational redundancy and multiple random numbers, and performing two-stage delayed verification; after passing the test, calculating the multiple sharding tasks according to the preset calculation rules of the computing task, obtaining multiple sharding calculation results, uploading them to the verification platform for privacy verification according to the preset verification contract, and generating multiple reward and punishment results. The present invention solves the technical problem of low credibility of outsourced computing in the prior art.

Description

Technical Field

[0001] The present invention relates to the field of outsourced computing technology, and in particular to a blockchain-based outsourced trusted computing method, system, and storage medium. Background Art

[0002] Outsourcing computing is a way for enterprises and institutions with limited computing resources to solve computing power problems. By purchasing computing resources from another party and outsourcing resources, users can save computing time and computing costs, and it is promoted and used together with cloud computing.

[0003] The credibility of outsourced computing results is an important guarantee for business operations. In existing technologies, outsourced computing results are generally verified by relying on the credibility of the computing power seller or through computing verification methods. However, there are technical problems such as low credibility of outsourced computing, high verification difficulty and high cost. Summary of the Invention

[0004] The present application provides a blockchain-based outsourced trusted computing method, system, and storage medium, which are used to solve the technical problems in the prior art of low credibility of outsourced computing, high verification difficulty, and high cost.

[0005] In a first aspect, the present application provides a blockchain-based outsourced trusted computing method, the method comprising:

[0006] Constructing an outsourced trusted computing system, wherein the outsourced trusted computing system includes a computing resource pool, a computing service platform, and a verification platform built on blockchain, and the computing resource pool includes multiple outsourced computing nodes for computing power registration;

[0007] For the computing tasks to be outsourced uploaded to the computing service platform, task sharding is performed to obtain multiple shard tasks, multiple random numbers are generated, and computing redundancy analysis is performed;

[0008] Randomly and redundantly distribute the multiple sharding tasks to the multiple outsourced computing nodes according to computational redundancy and multiple random numbers, and perform two-stage delayed verification on the multiple sharding tasks and the multiple random numbers;

[0009] After passing the two-stage delayed verification, the multiple outsourced computing nodes calculate the multiple sharding tasks according to the preset calculation rules of the computing tasks, obtain multiple sharding calculation results, upload them to the verification platform for privacy verification according to the preset verification contract, and generate multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results.

[0010] A second aspect of the present application provides an outsourced trusted computing system based on blockchain, the system comprising:

[0011] An outsourcing system construction module, used to construct an outsourced trusted computing system, wherein the outsourced trusted computing system includes a computing resource pool, a computing service platform, and a verification platform built on blockchain, and the computing resource pool includes multiple outsourced computing nodes for computing power registration;

[0012] A computing task slicing module is used to slice the computing tasks to be outsourced uploaded to the computing service platform, obtain multiple slicing tasks, generate multiple random numbers, and perform computing redundancy analysis;

[0013] A task redundancy distribution module is used to randomly and redundantly distribute the multiple sharding tasks to the multiple outsourced computing nodes according to the computing redundancy and the multiple random numbers, and perform two-stage delayed verification on the multiple sharding tasks and the multiple random numbers;

[0014] The computing verification module is used to, after the two-stage delayed verification is qualified, enable the multiple outsourced computing nodes to calculate the multiple sharding tasks according to the preset computing rules of the computing tasks, obtain multiple sharding computing results, upload them to the verification platform for privacy verification according to the preset verification contract, and generate multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results.

[0015] According to a third aspect of the present application, a computer device is provided, comprising a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method in the first aspect are implemented.

[0016] According to a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method in the first aspect are implemented.

[0017] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0018] The technical solution provided by this application constructs an outsourced trusted computing system including a computing power resource pool, a computing service platform, and a verification platform built on blockchain. When a user needs to perform outsourced computing, the computing task is sharded, a random number is generated, and computing redundancy analysis is performed. By randomly allocating sharding tasks through redundancy, the outsourced computing nodes are prevented from colluding to forge computing results, thereby ensuring the reliability and stability of the outsourced computing. The accuracy of the sharding task distribution and the redundant probability distribution are verified by random numbers. After the outsourced computing is completed, the computing results are verified by blockchain consensus, thereby reducing the difficulty and cost of verification, and being able to avoid the outsourced computing nodes from forging or tampering with the computing results to the greatest extent, thereby ensuring the credibility of the outsourced computing power. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flowchart of a blockchain-based outsourced trusted computing method provided in this application;

[0020] Figure 2 A schematic diagram of the architecture of a blockchain-based outsourced trusted computing method provided in this application;

[0021] Figure 3 A schematic diagram of the structure of a blockchain-based outsourced trusted computing system provided in this application.

[0022] Figure 4 This is a schematic diagram of the structure of an exemplary computer device according to an embodiment of the present application.

[0023] Explanation of the accompanying drawings: outsourcing system construction module 11, computing task slicing module 12, task redundancy distribution module 13, computing verification module 14, computer device 300, memory 301, processor 302, communication interface 303, bus architecture 304. DETAILED DESCRIPTION

[0024] This application provides a blockchain-based outsourced trusted computing method, system and storage medium to solve the technical problems in the existing technology of low credibility of outsourced computing, high verification difficulty and high cost.

[0025] Example 1

[0026] like Figure 1 As shown, the present application provides a blockchain-based outsourced trusted computing method, which includes:

[0027] S101: Constructing an outsourced trusted computing system, wherein the outsourced trusted computing system includes a computing resource pool, a computing service platform, and a verification platform built on blockchain, wherein the computing resource pool includes multiple outsourced computing nodes for computing power registration;

[0028] In the embodiment of this application, Figure 2 As shown, we first build an outsourced trusted computing system for outsourced computing and verification of outsourced computing results. In existing technologies, outsourced computing typically involves users directly interacting with the outsourcing party to exchange task data and computing results. There is no platform for outsourced computing verification, resulting in low trustworthiness and high verification difficulty.

[0029] The outsourced trusted computing system includes a computing resource pool, a computing service platform, and a verification platform built on blockchain.

[0030] The computing power resource pool includes multiple outsourced computing nodes that register computing power, which are used to accept outsourced computing tasks distributed by the computing service platform and perform outsourced computing.

[0031] The computing service platform is used to accept outsourced computing tasks submitted by users who need to perform outsourced computing and distribute the tasks.

[0032] The verification platform is built on blockchain and is used to verify the results of outsourced calculations. It uses the consensus mechanism and tamper-proof characteristics of blockchain technology to conduct public verification of outsourced calculations, which can prevent the outsourcing party from colluding to tamper with the outsourced calculation results and forge the calculation results, thereby improving the credibility of outsourced calculations.

[0033] Step S101 of the method provided in the embodiment of the present application includes:

[0034] Building a computing power resource pool, wherein the plurality of outsourced computing nodes are registered for computing power evaluation in the computing power resource pool, wherein the computing power evaluation includes computing evaluation of computing resources, storage resources, and network resources;

[0035] Building a computing service platform to connect to the computing resource pool; and

[0036] Based on the blockchain, a verification platform is constructed, wherein the verification platform includes the preset verification contract.

[0037] In the embodiments of the present application, a computing resource pool is constructed, and multiple outsourced computing nodes can evaluate and register their computing power within the computing resource pool to perform outsourced computing tasks. Outsourced computing nodes can evaluate and register their computing power within the computing resource pool to accept outsourced computing tasks of different sizes or quantities.

[0038] Exemplarily, computing power assessment includes computing evaluation of computing resources, storage resources, and network resources. Based on the size of computing resources, storage resources, and network resources of different outsourced computing nodes, the computing power of different outsourced computing nodes is converted into standardized computing power units of the same dimension through weighted calculation or expert analysis to reflect the computing capabilities of different outsourced computing nodes and record registration information.

[0039] Due to the method provided in the embodiment of the present application, the credibility of outsourced computing can be guaranteed by verifying the outsourced computing results. Since the computing power resource pool does not need to perform newcomer verification on the outsourced computing nodes, the number of outsourced computing nodes in the computing power resource pool can be expanded, thereby improving the scale of outsourced computing.

[0040] Build a computing service platform and connect it to the computing resource pool. The computing service platform is used to distribute the outsourced computing tasks entrusted by users to multiple outsourced computing nodes registered in the computing resource pool.

[0041] Based on the blockchain, a verification platform is constructed, wherein the verification platform includes a preset verification contract for verifying the outsourced calculation results. The specific verification calculation process is set and verified according to the calculation rules of the outsourced calculation task. The preset verification contract also includes a mechanism for rewarding or punishing the outsourced calculation nodes after verification. The outsourced calculation nodes that calculate correctly are rewarded as outsourced calculation remuneration, and the outsourced calculation nodes that calculate incorrectly are punished as punishment for falsifying calculation results or calculation errors.

[0042] Specifically, multiple outsourced computing nodes are used as network nodes, and data blocks are constructed by uploading outsourced computing results to form a blockchain, and then a verification platform is formed. Based on the public and tamper-proof characteristics of the blockchain, the reliability of verification is guaranteed.

[0043] S102: Slicing the computing task to be outsourced uploaded to the computing service platform to obtain multiple slicing tasks, generating multiple random numbers, and performing computing redundancy analysis;

[0044] In the embodiment of the present application, the computing task is an outsourced computing task uploaded to the computing service platform by a user who entrusts outsourced computing.

[0045] In the embodiment of the present application, in order to ensure the reliability of outsourced computing and prevent multiple outsourced computing nodes from colluding to forge computing results, the credibility of outsourced computing can be guaranteed by sharding the computing tasks, generating random numbers for verification, and redundantly distributing computing tasks.

[0046] Step S102 of the method provided in the embodiment of the present application includes:

[0047] For the computing tasks to be outsourced that are uploaded to the computing service platform, task slicing is performed according to the task slicing rules to obtain multiple slicing tasks, wherein the task slicing rules include size slicing rules and time-consuming slicing rules;

[0048] The multiple random numbers are randomly generated based on a public data source of the blockchain.

[0049] In the embodiment of the present application, a computing task uploaded to the computing service platform for outsourcing is sharded according to the task sharding rules to obtain multiple sharded tasks. Through task sharding and computational redundancy analysis, multiple outsourced computing nodes are allowed to perform redundant computations of the computing task, ensuring the accuracy of the outsourced computation while avoiding wasted computing power.

[0050] Among them, the task sharding rules include size sharding rules and time-consuming sharding rules. Generally, a large computing task includes multiple small computing tasks, which can be sharded according to the size or computing time of different specific computing tasks or other methods. The sharding process does not limit the size specifications of the sharded tasks after sharding, nor does it limit the redundancy after sharding. The sizes of different sharded tasks can be the same or different, and the data in different sharded tasks can partially overlap.

[0051] Furthermore, based on the public data sources of the blockchain, such as block hash, multiple random numbers are randomly generated, corresponding one-to-one to multiple sharding tasks. The random numbers can subsequently be used to verify the distribution of sharding tasks and control the redundancy probability density distribution of redundant distribution of sharding tasks, thereby improving the credibility of outsourced computing.

[0052] In the embodiment of the present application, step S102 further includes:

[0053] Obtain the remaining computing power resources of multiple outsourced computing nodes in the current computing power resource pool;

[0054] Obtaining a computational quality requirement for the computational task;

[0055] Based on the remaining computing power resources and computing quality requirements, computing redundancy analysis is performed to obtain computing redundancy, wherein the size of computing redundancy is positively correlated with the size of the remaining computing power resources and the computing quality requirements.

[0056] In an embodiment of the present application, the remaining computing power resources of multiple outsourced computing nodes in the current computing power resource pool are obtained, that is, the computing power resources currently remaining for computing of the multiple outsourced computing nodes. The larger the computing power resources, the more computing power that can currently be used for redundant computing, and the maximum redundant computing can be performed to ensure credibility. Conversely, the smaller the computing power that can be used for redundant computing, the more redundant computing power needs to be reduced to ensure the calculation of outsourced tasks.

[0057] Obtain the computational quality requirements of the computing task. The higher the computational quality requirements, the more redundant computations are required to ensure computational accuracy and reliability. Conversely, fewer redundant computations are required to reduce computational costs.

[0058] Optionally, you can set upper and lower limits for computational redundancy to ensure accuracy of redundant computations while avoiding wasted computing power.

[0059] Based on the remaining computing power resources and computing quality requirements, computing redundancy analysis is performed. The size of computing redundancy is positively correlated with the size of the remaining computing power resources and the computing quality requirements. It can be analyzed and obtained based on redundant computing experience values, or by obtaining sample data to build a computing redundancy classification model and classify the computing redundancy.

[0060] For example, computing redundancy refers to the number of redundancies when distributing the same shard task to different outsourced computing nodes for calculation. By distributing the same shard task to multiple different outsourced computing nodes for calculation, the accuracy and credibility of the calculation are guaranteed. The higher the redundancy, the more difficult it is for the outsourced computing nodes to collude to forge the calculation results, and the blockchain is used to ensure that the calculation results are credible.

[0061] S103: Randomly and redundantly distribute the multiple sharding tasks to the multiple outsourced computing nodes according to the computational redundancy and the multiple random numbers, and perform two-stage delayed verification on the multiple sharding tasks and the multiple random numbers;

[0062] In an embodiment of the present application, based on the computational redundancy and multiple random numbers, multiple sharding tasks are randomly and redundantly distributed to the multiple outsourced computing nodes, and after distribution, two-stage delayed verification is performed based on the multiple sharding tasks and multiple random numbers to determine the correctness of the distribution.

[0063] During the distribution process, the redundant probability density distribution can be guaranteed based on multiple random numbers to achieve the unpredictability of the distribution task, avoid the falsification of calculation results, and ensure that redundant calculations are performed by multiple different outsourced computing nodes.

[0064] Step S103 of the method provided in the embodiment of the present application includes:

[0065] Randomly and redundantly distribute the multiple sharding tasks to the multiple outsourced computing nodes according to the computational redundancy and the multiple random numbers, wherein privacy protection processing is performed on the same sharding tasks redundantly distributed to different outsourced computing nodes;

[0066] Perform irreversible mapping on multiple random numbers and perform one-stage verification based on the multiple irreversible mapping values;

[0067] Perform two-stage verification based on the calculation data in multiple sharding tasks to obtain the two-stage verification results.

[0068] In an embodiment of the present application, multiple sharding tasks are randomly and redundantly distributed to multiple outsourced computing nodes based on computational redundancy and multiple random numbers. During the distribution process, the redundant distribution probability density distribution is controlled based on multiple random numbers to ensure that different outsourced computing nodes perform the calculation of redundant sharding tasks.

[0069] Among them, privacy protection processing is performed on the same sharding tasks that are redundantly distributed to different outsourced computing nodes. For example, the privacy protection processing includes different obfuscation, encryption, and blinding processing, so that different outsourced computing nodes cannot predict that they have obtained the same sharding tasks, thereby preventing them from falsifying the computing results together.

[0070] After the distribution is completed, based on the distributed random numbers and sharding tasks, multiple random numbers are irreversibly mapped, and a one-stage verification is performed based on multiple irreversible mapping values ​​to determine whether the computational redundancy and distribution requirements are met.

[0071] After the first phase of verification is completed, the second phase of verification is performed based on the calculation data in multiple sharding tasks to achieve delayed verification. Specifically, verification is performed based on the public and secret data in the sharding tasks to determine whether the calculation redundancy and distribution requirements are met, and to obtain the second phase verification results.

[0072] S104: After the two-stage delayed verification is passed, the multiple outsourced computing nodes calculate the multiple sharding tasks according to the preset calculation rules of the computing tasks, obtain multiple sharding calculation results, upload them to the verification platform for privacy verification according to the preset verification contract, and generate multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results.

[0073] Step S104 of the method provided in the embodiment of the present application includes:

[0074] Perform privacy verification according to a preset verification contract, and generate multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results, including:

[0075] Perform irreversible mapping processing on the plurality of shard calculation results to obtain a plurality of irreversible mapping values ​​of the calculation results, and upload the values ​​to the verification platform;

[0076] Perform privacy verification according to the preset verification conditions of the computing task in the preset verification contract to obtain a privacy verification result;

[0077] Based on the privacy verification results, multiple reward and punishment results for the multiple outsourced computing nodes are generated.

[0078] In an embodiment of the present application, after the second-stage verification results are qualified, multiple outsourced computing nodes calculate multiple shard tasks according to the preset computing rules of the computing tasks. Specifically, the shard tasks are calculated according to the computing rules of the multiple shard tasks to obtain multiple shard stage results of the multiple shard tasks, including redundant shard calculation results.

[0079] The calculation results of multiple shards are irreversibly mapped. For example, hash mapping is performed to obtain hash values, and multiple irreversible mapping values ​​of the calculation results are obtained and uploaded to the verification platform.

[0080] According to the preset verification conditions of the computation task within the preset verification contract within the verification platform, privacy verification is performed on the irreversibly mapped values ​​of multiple computation results to obtain a privacy verification result. Through irreversibly mapped privacy verification, public verification is performed without disclosing the computation results, protecting the privacy of the computation results and completing the outsourced computation. The preset verification conditions can be pre-set based on the computation task's calculation rules to complete automated verification.

[0081] Based on the privacy verification result, multiple reward and punishment results for multiple outsourced computing nodes are generated.

[0082] Step S104 of the method provided in the embodiment of the present application includes:

[0083] Based on the privacy verification results, multiple reward calculation nodes and multiple penalty calculation nodes are screened and obtained;

[0084] A plurality of reward and punishment results are generated for the plurality of reward calculation nodes and the plurality of punishment calculation nodes.

[0085] In an embodiment of the present application, based on the privacy verification results, the outsourced computing nodes with correct calculations and the outsourced computing nodes with incorrect calculations are screened and verified, and are respectively screened into multiple reward computing nodes and multiple penalty computing nodes as objects to be rewarded or punished.

[0086] Multiple reward and punishment results are generated for multiple reward calculation nodes and multiple penalty calculation nodes. The multiple reward and punishment results can be monetary rewards or credit score rewards. They are generated specifically based on the outsourced amount of the computing task and related requirements. Technical personnel in this field can set them by themselves.

[0087] In summary, the embodiments of the present application have at least the following technical effects:

[0088] The technical solution provided by this application constructs an outsourced trusted computing system including a computing power resource pool, a computing service platform, and a verification platform built on blockchain. When a user needs to perform outsourced computing, the computing task is sharded, a random number is generated, and computing redundancy analysis is performed. By randomly allocating sharding tasks through redundancy, the outsourced computing nodes are prevented from colluding to forge computing results, thereby ensuring the reliability and stability of the outsourced computing. The accuracy of the sharding task distribution and the redundant probability distribution are verified by random numbers. After the outsourced computing is completed, the computing results are verified by blockchain consensus, thereby reducing the difficulty and cost of verification, and being able to avoid the outsourced computing nodes from forging or tampering with the computing results to the greatest extent, thereby ensuring the credibility of the outsourced computing power.

[0089] Example 2

[0090] Based on the same inventive concept as the blockchain-based outsourced trusted computing method in the aforementioned embodiment, Figure 3As shown, the present application provides an outsourced trusted computing system based on blockchain. The specific description of the outsourced trusted computing method based on blockchain in the first embodiment is also applicable to the outsourced trusted computing system based on blockchain, wherein the system includes:

[0091] An outsourcing system construction module 11 is used to construct an outsourced trusted computing system, wherein the outsourced trusted computing system includes a computing resource pool, a computing service platform, and a verification platform built on blockchain. The computing resource pool includes multiple outsourced computing nodes for computing power registration.

[0092] The computing task slicing module 12 is used to slice the computing task to be outsourced uploaded to the computing service platform, obtain multiple slicing tasks, generate multiple random numbers, and perform computing redundancy analysis;

[0093] The task redundancy distribution module 13 is used to randomly and redundantly distribute the multiple shard tasks to the multiple outsourced computing nodes according to the computing redundancy and the multiple random numbers, and perform two-stage delayed verification on the multiple shard tasks and the multiple random numbers;

[0094] The computing verification module 14 is used to, after the two-stage delayed verification is qualified, the multiple outsourced computing nodes calculate the multiple sharding tasks according to the preset computing rules of the computing tasks, obtain multiple sharding computing results, upload them to the verification platform for privacy verification according to the preset verification contract, and generate multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results.

[0095] Furthermore, the outsourcing system construction module 11 is also used to implement the following functions:

[0096] Building a computing power resource pool, wherein the plurality of outsourced computing nodes are registered for computing power evaluation in the computing power resource pool, wherein the computing power evaluation includes computing evaluation of computing resources, storage resources, and network resources;

[0097] Building a computing service platform to connect to the computing resource pool; and

[0098] Based on the blockchain, a verification platform is constructed, wherein the verification platform includes the preset verification contract.

[0099] Furthermore, the computing task slicing module 12 is also used to implement the following functions:

[0100] For the computing tasks to be outsourced that are uploaded to the computing service platform, task slicing is performed according to the task slicing rules to obtain multiple slicing tasks, wherein the task slicing rules include size slicing rules and time-consuming slicing rules;

[0101] The multiple random numbers are randomly generated based on a public data source of the blockchain.

[0102] Furthermore, the computing task slicing module 12 is also used to implement the following functions:

[0103] Obtain the remaining computing power resources of multiple outsourced computing nodes in the current computing power resource pool;

[0104] Obtaining a computational quality requirement for the computational task;

[0105] Based on the remaining computing power resources and computing quality requirements, computing redundancy analysis is performed to obtain computing redundancy, wherein the size of computing redundancy is positively correlated with the size of the remaining computing power resources and the computing quality requirements.

[0106] Furthermore, the task redundancy distribution module 13 is also used to implement the following functions:

[0107] Randomly and redundantly distribute the multiple sharding tasks to the multiple outsourced computing nodes according to the computational redundancy and the multiple random numbers, wherein privacy protection processing is performed on the same sharding tasks redundantly distributed to different outsourced computing nodes;

[0108] Perform irreversible mapping on multiple random numbers and perform one-stage verification based on the multiple irreversible mapping values;

[0109] Perform two-stage verification based on the calculation data in multiple sharding tasks to obtain the two-stage verification results.

[0110] Furthermore, the calculation verification module 14 is also used to implement the following functions:

[0111] Perform irreversible mapping processing on the plurality of shard calculation results to obtain a plurality of irreversible mapping values ​​of the calculation results, and upload the values ​​to the verification platform;

[0112] Perform privacy verification according to the preset verification conditions of the computing task in the preset verification contract to obtain a privacy verification result;

[0113] Based on the privacy verification results, multiple reward and punishment results for the multiple outsourced computing nodes are generated.

[0114] According to the privacy verification results, multiple reward and punishment results for the multiple outsourced computing nodes are generated, including:

[0115] Based on the privacy verification results, multiple reward calculation nodes and multiple penalty calculation nodes are screened and obtained;

[0116] A plurality of reward and punishment results are generated for the plurality of reward calculation nodes and the plurality of punishment calculation nodes.

[0117] Example 3

[0118] like Figure 4 As shown, based on the same inventive concept as the blockchain-based outsourced trusted computing method in the aforementioned embodiment, the present application also provides a computer device 300, which includes a memory 301 and a processor 302, and a computer program is stored in the memory 301. When the computer program is executed by the processor 302, the steps of a method in an embodiment are implemented.

[0119] The computer device 300 includes: a processor 302, a communication interface 303, and a memory 301. Optionally, the computer device 300 may further include a bus architecture 304. The communication interface 303, the processor 302, and the memory 301 may be interconnected via the bus architecture 304; the bus architecture 304 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0120] The processor 302 may be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of the program of the present application.

[0121] The communication interface 303 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), wired access network, etc.

[0122] The memory 301 can be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read only memory (EEPROM), a compact disc (CD ROM) or other optical disc storage, an optical disc storage (including a compact disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory can exist independently and be connected to the processor via the bus architecture 304. The memory can also be integrated with the processor.

[0123] The memory 301 is used to store computer-executable instructions for executing the solution of the present application, and the execution is controlled by the processor 302. The processor 302 is used to execute the computer-executable instructions stored in the memory 301, thereby implementing a blockchain-based outsourced trusted computing method provided in the above embodiment of the present application.

[0124] Example 4

[0125] Based on the same inventive concept as the blockchain-based outsourced trusted computing method in the aforementioned embodiment, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the method in embodiment one are implemented.

[0126] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A blockchain-based outsourced trusted computing method, characterized in that: The method comprises: Constructing an outsourced trusted computing system, wherein the outsourced trusted computing system includes a computing resource pool, a computing service platform, and a verification platform built on blockchain, and the computing resource pool includes multiple outsourced computing nodes for computing power registration; For the computing tasks to be outsourced uploaded to the computing service platform, task sharding is performed to obtain multiple shard tasks, multiple random numbers are generated, and computing redundancy analysis is performed; Randomly and redundantly distribute the multiple sharding tasks to the multiple outsourced computing nodes according to computational redundancy and multiple random numbers, and perform two-stage delayed verification on the multiple sharding tasks and the multiple random numbers; After passing the two-stage delayed verification, the multiple outsourced computing nodes calculate the multiple sharding tasks according to the preset calculation rules of the computing tasks, obtain multiple sharding calculation results, upload them to the verification platform for privacy verification according to the preset verification contract, and generate multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results.

2. The method according to claim 1, characterized in that Build an outsourced trusted computing system, including: Building a computing power resource pool, wherein the plurality of outsourced computing nodes are registered for computing power evaluation in the computing power resource pool, wherein the computing power evaluation includes computing evaluation of computing resources, storage resources, and network resources; Building a computing service platform to connect to the computing resource pool; and Based on the blockchain, a verification platform is constructed, wherein the verification platform includes the preset verification contract.

3. The method according to claim 1, characterized in that The computing task to be outsourced uploaded to the computing service platform is split into task slices to obtain multiple slice tasks and generate multiple random numbers, including: For the computing tasks to be outsourced that are uploaded to the computing service platform, task slicing is performed according to the task slicing rules to obtain multiple slicing tasks, wherein the task slicing rules include size slicing rules and time-consuming slicing rules; The multiple random numbers are randomly generated based on a public data source of the blockchain.

4. The method according to claim 1, wherein Perform computational redundancy analysis, including: Obtain the remaining computing power resources of multiple outsourced computing nodes in the current computing power resource pool; Obtaining a computational quality requirement for the computational task; Based on the remaining computing power resources and computing quality requirements, computing redundancy analysis is performed to obtain computing redundancy, wherein the size of computing redundancy is positively correlated with the size of the remaining computing power resources and the computing quality requirements.

5. The method according to claim 1, wherein According to the computational redundancy and the multiple random numbers, the multiple sharding tasks are randomly and redundantly distributed to the multiple outsourced computing nodes, and two-stage delayed verification is performed on the multiple sharding tasks and the multiple random numbers, including: Randomly and redundantly distribute the multiple sharding tasks to the multiple outsourced computing nodes according to the computational redundancy and the multiple random numbers, wherein privacy protection processing is performed on the same sharding tasks redundantly distributed to different outsourced computing nodes; Perform irreversible mapping on multiple random numbers and perform one-stage verification based on the multiple irreversible mapping values; Perform two-stage verification based on the calculation data in multiple sharding tasks to obtain the two-stage verification results.

6. The method according to claim 1, characterized in that The multiple outsourced computing nodes calculate the multiple sharding tasks according to the preset computing rules of the computing tasks, obtain multiple sharding computing results, upload them to the verification platform for privacy verification according to the preset verification contract, and generate multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results, including: Perform irreversible mapping processing on the plurality of shard calculation results to obtain a plurality of irreversible mapping values ​​of the calculation results, and upload the values ​​to the verification platform; Perform privacy verification according to the preset verification conditions of the computing task in the preset verification contract to obtain a privacy verification result; Based on the privacy verification results, multiple reward and punishment results for the multiple outsourced computing nodes are generated.

7. The method according to claim 6, characterized in that Generating multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results, including: Based on the privacy verification results, multiple reward calculation nodes and multiple penalty calculation nodes are screened and obtained; A plurality of reward and punishment results are generated for the plurality of reward calculation nodes and the plurality of punishment calculation nodes.

8. A blockchain-based outsourced trusted computing system, characterized in that: The system comprises: An outsourcing system construction module, used to construct an outsourced trusted computing system, wherein the outsourced trusted computing system includes a computing resource pool, a computing service platform, and a verification platform built on blockchain, and the computing resource pool includes multiple outsourced computing nodes for computing power registration; A computing task slicing module is used to slice the computing tasks to be outsourced uploaded to the computing service platform, obtain multiple slicing tasks, generate multiple random numbers, and perform computing redundancy analysis; A task redundancy distribution module is used to randomly and redundantly distribute the multiple sharding tasks to the multiple outsourced computing nodes according to the computing redundancy and the multiple random numbers, and perform two-stage delayed verification on the multiple sharding tasks and the multiple random numbers; The computing verification module is used to, after the two-stage delayed verification is qualified, enable the multiple outsourced computing nodes to calculate the multiple sharding tasks according to the preset computing rules of the computing tasks, obtain multiple sharding computing results, upload them to the verification platform for privacy verification according to the preset verification contract, and generate multiple reward and punishment results for the multiple outsourced computing nodes based on the privacy verification results.

9. A computer device, characterized in that: The computer device includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

Images