A blockchain-based industrial control software crowdsourcing personnel multi-dimensional dynamic evaluation method, device, medium and product

Abstract

The application discloses a kind of based on blockchain industrial control software crowd testing personnel multidimensional dynamic evaluation method, equipment, medium and product, it is related to personnel management field, this method includes: build the industrial control crowd testing blockchain underlying platform based on alliance chain and deploy basic smart contract;Rely on the six-dimension calculation rules of basic smart contract, the integral of each dimension is counted and chain synchronization is completed, and accordingly generation and chain storage ability portrait is generated;Combining industrial control subdivision scene, task risk level and difficulty, adjust the scene dynamic weight, and the whole chain is stored in weight adjustment record;Monitoring tester behavior data, according to the score increasing, score reducing and integral decay mechanism to update the integral, and the whole chain is stored in integral change record;Accounting tester comprehensive ability score, after reaching the standard, execute incentive operation and store record;When integral or personnel level changes, update ability portrait.The application can realize the identification, grading and incentive of crowd testing personnel ability, improve the quality and efficiency of industrial control software crowd testing.

Description

Technical Field

[0001] This application relates to the field of personnel management, and in particular to a method, equipment, medium, and product for multi-dimensional dynamic evaluation of crowdsourced testers of industrial control software based on blockchain. Background Technology

[0002] The current personnel evaluation system in the field of crowdsourced testing for industrial control software security has many core problems: 1. The evaluation dimensions are too simplistic and detached from the characteristics of the industrial control industry: Traditional crowdsourcing testing only uses the number of vulnerabilities and the Common Vulnerability Scoring System (CVSS) level as the core evaluation indicators. It cannot measure the testers' mastery of industrial control logic, industrial protocols (such as IEC 61850, PROFIBUS), and industry process knowledge, and it is difficult to identify professionals with OT+IT combined capabilities. 2. The points data is unreliable and easily tampered with: The evaluation data is stored on a centralized platform, which makes it susceptible to problems such as data being modified by humans, points being falsified, and vulnerability reports being maliciously tampered with, resulting in distorted evaluation results; 3. The evaluation mechanism is static and lacks dynamic adjustment: it only calculates points based on historical fixed data and cannot dynamically update points according to the testers' real-time behavior, task performance, and the effectiveness of vulnerability repair, resulting in insufficient incentive timeliness. 4. Low accuracy in matching capabilities with tasks: The points weights were not customized according to the differentiated needs of the industrial control industry (power, petrochemical, rail transit, etc.), resulting in a mismatch between professional capabilities and testing tasks, and insufficient efficiency and depth in discovering vulnerabilities in crowdsourcing testing. 5. The disconnect between incentives and evaluation makes it difficult to attract professional talent: Simply linking points to cash rewards without combining points with tester promotions, task priorities, industry certification endorsements, etc., fails to effectively attract and retain security talent with in-depth knowledge of industrial control fields.

[0003] In existing technologies, some crowdsourcing platforms have attempted to introduce multi-dimensional scoring, but these only remain at the level of centralized static data statistics. They have not solved core issues such as data credibility, dynamic adaptation, and industry customization. They lack targeted design for industrial control crowdsourcing scenarios and have not combined blockchain technology to achieve credible traceability of the entire evaluation process. Summary of the Invention

[0004] The purpose of this application is to provide a method, device, medium, and product for multi-dimensional dynamic evaluation of crowdsourced testers of industrial control software based on blockchain, which can realize objective identification, accurate classification, and effective incentive of the capabilities of crowdsourced testers, thereby improving the quality and efficiency of crowdsourced testing of industrial control software.

[0005] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software based on blockchain, including: Build an industrial control crowdsourcing testing blockchain underlying platform based on a consortium blockchain, and deploy basic smart contracts on the industrial control crowdsourcing testing blockchain underlying platform; Based on the aforementioned basic smart contract, according to the basic information uploaded by the testers, the scores for each dimension are calculated according to the preset basic calculation rules of six dimensions, and the scores for each dimension are synchronized on the blockchain; the six dimensions include: reputation dimension, education dimension, professional dimension, industrial control field knowledge dimension, achievement dimension, and activity dimension. Based on the aforementioned basic smart contract, a capability profile is generated according to the scores of each dimension, and the capability profile is stored on the blockchain for evidence. Based on the aforementioned basic smart contract, the scenario-based dynamic weights of each dimension are automatically updated according to the subdivided industrial control scenarios, task risk levels, and task difficulty. The weight adjustment records are recorded on the blockchain for evidence storage throughout the entire process. Based on the aforementioned basic smart contract, the behavior data of testers during the crowd testing process is monitored in real time to see if they meet the scoring trigger rules, scoring trigger rules, or points decay mechanism. If they do, the points in the corresponding dimension are updated, and the points change record is recorded on the blockchain for evidence storage. Based on the aforementioned basic smart contract, a comprehensive capability score is calculated according to the updated scores of each dimension and the updated scenario-based dynamic weights. When the comprehensive capability score reaches the corresponding score threshold, an incentive operation is executed based on the basic smart contract, and the incentive record is stored on the blockchain. When the scores in each dimension are updated or the tester's level is promoted, the capability profile is automatically updated based on the basic smart contract to complete the multi-dimensional dynamic evaluation of the industrial control software crowdsourcing testers.

[0006] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned multi-dimensional dynamic evaluation method for crowdsourced testing of blockchain-based industrial control software.

[0007] Thirdly, this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the aforementioned blockchain-based multi-dimensional dynamic evaluation method for crowdsourced testers of industrial control software.

[0008] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned multi-dimensional dynamic evaluation method for crowdsourced testing of blockchain-based industrial control software.

[0009] According to the specific embodiments provided in this application, this application has the following technical effects: (1) This application introduces six dimensions: reputation, education, professionalism, knowledge in the field of industrial control, achievements, and activity, which realizes the comprehensiveness and industry customization of evaluation dimensions. It can accurately quantify the testers' mastery of industrial protocols, control logic and industry process knowledge, and identify professional talents with OT+IT composite capabilities. Through the scenario-based dynamic weight adjustment of each dimension, the evaluation results can reflect the testers' adaptability in specific industrial control sub-scenarios in real time, which solves the problem that general evaluation indicators cannot reflect industry differences. (2) This application has built an underlying platform based on consortium blockchain, and all subsequent point calculations, weight adjustments, behavior records, etc. are executed through basic smart contracts and uploaded to the blockchain, ensuring the immutability and credibility of the evaluation data and realizing full-process traceability; (3) This application establishes a score increase / decrease / attenuation trigger mechanism. The basic smart contract monitors behavioral data in real time and automatically updates the score. The score is no longer a static value calculated once, but an indicator that changes dynamically with the tester's real-time behavior (such as vulnerability implementation and repair, and violation of regulations). The automated trigger mechanism eliminates the lag and subjectivity of manual intervention and ensures that the capability profile is always synchronized with the tester's current actual level. (4) This application binds the comprehensive ability score to the incentive operation certificate and executes it automatically by the basic smart contract, realizing the automation and transparency of the incentive mechanism, meeting the needs of professional talents for career growth and industry status, and effectively attracting and retaining security talents with profound industrial control knowledge. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software based on blockchain, provided as an embodiment of this application. Detailed Implementation

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0013] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0014] In one exemplary embodiment, such as Figure 1 As shown, a multi-dimensional dynamic evaluation method for crowdsourcing testers of industrial control software based on blockchain is provided, including the following steps S1 to S7.

[0015] S1: Build an industrial control crowdsourcing blockchain underlying platform based on a consortium blockchain, and deploy basic smart contracts on the industrial control crowdsourcing blockchain underlying platform.

[0016] Specifically, a blockchain underlying platform for industrial control crowdsourcing testing is built based on a consortium blockchain. The nodes include the operator of the industrial control crowdsourcing testing platform (operator), manufacturers in industries such as power / petrochemical or industrial control industry associations (clients), and third-party auditing institutions (auditors). The PBFT consensus algorithm is adopted to ensure data credibility and consensus efficiency.

[0017] Deploy basic smart contracts on the industrial control crowdsourcing blockchain underlying platform, including: data storage contract, points calculation contract, weight adjustment contract, level promotion contract, incentive distribution contract, task matching contract, and ability profile generation contract. All contract code is open source and verifiable. Security audits are conducted before deployment, and audit reports are hashed and uploaded to the blockchain.

[0018] S2: Based on the aforementioned basic smart contract, according to the basic information uploaded by the testers to the blockchain, calculate the scores for each dimension according to the preset basic calculation rules for the six dimensions, and synchronize the scores for each dimension to the blockchain; the six dimensions include: reputation dimension, education dimension, professional dimension, industrial control field knowledge dimension, achievement dimension, and activity dimension.

[0019] Specifically, testers (testing parties) complete real-name authentication by entering their username, email, mobile phone number, and password through the industrial control system crowdsourcing testing platform terminal. The platform then assigns them a unique blockchain DID identity, and the registration information is hashed and stored on the blockchain for evidence. Based on their assigned DID identity, testers submit basic personal information, including: identity information, educational background, professional certificates, online assessment scores in industrial control system knowledge, and performance in industrial control system test range tests. All original documents are filed offline, and the hash values ​​are stored on the blockchain in real time to ensure immutability.

[0020] The platform operator reviews the information submitted by testers and stores the review results (pass / fail) on the blockchain. After the review is passed, the basic smart contract automatically calculates the tester's scores in each dimension based on the tester's basic information and the basic calculation rules in six dimensions, and the score results are synchronized on the blockchain.

[0021] In this embodiment, the six dimensions include: reputation dimension, education dimension, professional dimension, industrial control knowledge dimension, achievement dimension, and activity dimension. The original data of each dimension is stored on the blockchain for evidence, the calculation process is automatically executed through smart contracts, and the results are synchronized on the blockchain to ensure immutability.

[0022] (1) Reputation dimension score.

[0023] Credit score = Basic credit score + Behavioral credit score - Points deducted for violations.

[0024] Basic credit score: (Education points + Professional points + Industrial control knowledge points) × 0.2; Behavioral reputation score: Vulnerability report effectiveness rate × 50 + report acceptance rate × 30 + task response timeliness × 20; Points deduction for violations: 50-200 points will be deducted for each violation (depending on the severity of the violation). Forging a report will result in an immediate deduction of 200 points and permanent marking. There is no lower limit to the points deducted.

[0025] (2) Education dimension score.

[0026] Education points = (degree points × full-time coefficient) + academic qualifications + additional points for industrial control majors.

[0027] Degree points: None 0, Bachelor's 10, Master's 20, Doctoral 30; Full-time coefficient: 1 for full-time, 0.5 for part-time; Education level score: None 0, Associate's degree 10, Bachelor's degree 20, Master's degree 30, Doctoral degree 40; Additional points for Industrial Control Engineering majors: Majors related to Automation / Industrial Control / Power Systems / Petrochemical Processes, etc., will receive an additional 20% on top of the calculated results.

[0028] (3) Professional dimension score.

[0029] Professional points = (certificate points × industrial control certificate coefficient) + industry experience points + training points + additional points for composite abilities.

[0030] Certificate points: 5 points for a general cybersecurity certificate, and 10 points for an industrial control system security-related certificate (such as IEC61850 certification, industrial control system security expert certification) (industrial control certificate coefficient = 2); Industry experience points: Industrial control related work / testing experience, 2 points for 1 year, maximum 20 points; Training points: Industrial control system security related training, 3 points per session, maximum 15 points; Bonus points for combined skills: 10 extra points for having both OT and IT certifications.

[0031] (4) Knowledge dimension integration in the field of industrial control.

[0032] Industrial control knowledge points = online assessment points + test range practical points + sub-field experience points.

[0033] Online assessment score: Industrial control knowledge online assessment (customized question bank according to subdivided scenarios), full score is 100 points, converted to 0-50 points based on actual score; Target range practical score: Performance in industrial control security target range testing, with a full score of 100 points, converted to 0-30 points based on the actual score; Sub-field experience points: Testing experience in a specific sub-field of industrial control, 5 points per field, maximum 20 points.

[0034] (5) Results dimension integration.

[0035] Achievement score = (vulnerability score × industrial control vulnerability coefficient) + use case innovation score + report standardization score + remediation implementation score.

[0036] Vulnerability points: Points are awarded based on the industrial impact level of industrial control system vulnerabilities: 5 points for low-level vulnerabilities, 15 points for mid-level vulnerabilities, 30 points for high-level vulnerabilities, and 50 points for core vulnerabilities (industrial control system core vulnerability coefficient = 2). Test case innovation score: Original industrial control test cases, 3 points for each, maximum 30 points; Report Standard Score: Scored according to the Industrial Control System Crowdsourcing Report Standard, with a maximum score of 100 points, converted to 0-20 points based on the actual score; Points for successful patching: 10 points are awarded for each vulnerability patched and implemented by the vendor, with no upper limit.

[0037] (6) Activity dimension score.

[0038] Active Points = (Login Points in the Last 90 Days + Project Participation Points + Knowledge Sharing Points + Response Timeliness Points) - Point Decay Points.

[0039] Login points in the past 90 days: 1 point per day for each unique login, up to a maximum of 90 points; Project participation points: 5 points for participating in 1 industrial control system crowdsourcing test project, with a maximum of 50 points; Knowledge sharing points: 3 points for sharing industrial control system security knowledge on the platform once, up to a maximum of 30 points; Response timeliness score: 20 points for average task response time ≤ 2 hours, 10 points for 2-4 hours, and 0 points for > 4 hours; Points decay: Points decay by 0.5% per day if no participation is made for 90 consecutive days.

[0040] S3: Based on the aforementioned basic smart contract, generate a capability profile according to the scores of each dimension, and store the capability profile on the blockchain for evidence.

[0041] After testers complete the registration and verification process and obtain points in various dimensions, the smart contract automatically generates a capability profile based on the six dimensions of on-chain point data, including a radar chart, level, and basic tags. The profile data is then stored on the blockchain for evidence.

[0042] S4: Based on the aforementioned basic smart contract, automatically update the scenario-based dynamic weights for each dimension according to the sub-scenarios of industrial control, task risk level, and task difficulty. Weight adjustment records are stored on the blockchain throughout the entire process. Specifically, this includes: S41: Preset scenario-based dynamic weights for each dimension of industrial control sub-scenarios.

[0043] For the five core sub-sectors of the industrial control industry—power, petrochemical, rail transit, steel metallurgy, and equipment manufacturing—dynamic weights are preset based on the industry characteristics, process requirements, and risk levels of each scenario. In the power sector, the weights of the knowledge dimension (30%) and outcome dimension (25%) in the industrial control field are increased. In the rail transit sector, the weights of the reputation dimension (30%) and the knowledge dimension (25%) in the industrial control field are increased.

[0044] S42: Determine dynamic adjustment rules based on the task risk level and the task difficulty.

[0045] Specifically, the dynamic adjustment rules are as follows: high-risk tasks increase the weight of reputation and industrial control knowledge; high-difficulty tasks increase the weight of professionalism and results; and urgent tasks increase the weight of activity and response time.

[0046] S43: Automatically update the scenario-based dynamic weights of each dimension based on the aforementioned dynamic adjustment rules.

[0047] The platform operator initiates a weight adjustment application, which is then reviewed and approved by the blockchain nodes. The smart contract automatically updates the scenario-based dynamic weights for each dimension, and the adjustment is recorded throughout the process.

[0048] S5: Based on the aforementioned basic smart contract, monitor in real time whether the behavior data of testers during the crowd testing process meets the scoring trigger rules, scoring trigger rules, or points decay mechanism. If it does, update the points in the corresponding dimension and record the points change on the blockchain for evidence storage.

[0049] (1) Score increase triggering rules.

[0050] When a vulnerability in the core industrial control system (such as a control logic vulnerability or an industrial protocol vulnerability) is submitted and confirmed, the vulnerability score will be doubled. When a vulnerability report is fixed and implemented by the vendor, points are awarded for the fix implementation. Sharing industrial control security testing knowledge or original test cases on the platform, and having them approved, will increase your knowledge sharing score. When participating in and completing industrial control crowdsourcing testing tasks marked as high-risk or high-difficulty, bonus points will be added to the scores in each dimension according to a preset additional ratio or additional value. When a student achieves a score no lower than the preset excellent score in the online assessment of industrial control knowledge or the practical test of industrial control security, the online assessment score or the practical test score will be increased.

[0051] (2) Deduction trigger rules.

[0052] When the false positive rate of vulnerability reports exceeds the preset false positive rate thresholds (basic: 70%, intermediate: 85%, advanced and expert: 95%), the behavior reputation score will be reduced. When violations occur (such as unauthorized testing of industrial control production systems or falsification of vulnerability reports), points will be deducted or added for violations, and points will be deducted from the reputation score; and violation records will be permanently uploaded to the blockchain. If the submitted vulnerability report is not prepared in accordance with the Industrial Control System Crowdsourcing Test Report Writing Specification, points will be deducted from the report's compliance score. Points will be deducted for failure to respond on time or abandonment of a task midway after it has been accepted.

[0053] (3) Integral decay mechanism.

[0054] If a tester does not participate in any industrial control crowdsourcing testing projects for 90 consecutive days, their activity points will decrease by 0.5% per day. If a tester does not participate in any industrial control crowdsourcing testing projects for 180 consecutive days, their professional points and industrial control knowledge points will decrease by 0.3% per day.

[0055] S6: Based on the aforementioned basic smart contract, calculate the comprehensive capability score according to the updated scores and updated scenario-based dynamic weights for each dimension; when the comprehensive capability score reaches the corresponding score threshold, execute the incentive operation based on the basic smart contract, and record the incentive on the blockchain for evidence storage.

[0056] Comprehensive ability score = Σ (indicators of each dimension × dynamic weight of each scenario).

[0057] The scenario-based dynamic weights are automatically loaded by the basic smart contract based on the sub-scenarios of industrial control, task difficulty, and task risk level. The sum of the scenario-based dynamic weights across the six dimensions is 100%. The comprehensive ability score serves as the core basis for tester level promotion, task matching, and incentive distribution.

[0058] When the overall ability score reaches the corresponding threshold, incentive operations are executed based on the basic smart contract. These incentive operations include automated level promotion, automated task priority allocation, automated adjustment of bounty distribution ratio, and automated industry certification endorsement.

[0059] (1) Automated promotion of levels.

[0060] The system pre-defines four levels of industrial control system (ICS) crowdsourcing testers: beginner, intermediate, advanced, and expert. Each level corresponds to a specific on-chain score threshold and dimensional requirements: beginner (overall ability score ≥ 200), intermediate (≥ 400), advanced (≥ 600), and expert (≥ 800). Furthermore, the score for each dimension must not be lower than 20% of the corresponding threshold. When the overall ability score reaches the corresponding threshold, the smart contract automatically completes the level promotion, the level change record is uploaded to the blockchain, and the level is bound to the tester's blockchain DID identity, making it tamper-proof.

[0061] (2) Automatic allocation of task priorities.

[0062] High-level (advanced / expert) testers automatically receive priority access to high-risk, high-difficulty, and high-reward industrial control crowdsourcing testing tasks. The basic smart contract achieves intelligent matching of tasks and talents based on the tester's level and ability profile.

[0063] (3) The bounty distribution ratio is automatically adjusted.

[0064] The basic smart contract has a preset bounty distribution ratio: 100% for beginners, 110% for intermediates, 120% for advanceds, and 130% for experts. The basic smart contract automatically calculates the bounty according to the ratio and distributes it to the account bound to the tester's DID identity through the platform, and the distribution record is recorded on the blockchain.

[0065] (4) Industry certification automation endorsement.

[0066] Once a tester is promoted to expert level, the basic smart contract automatically initiates a certification application to the industrial control industry association. After the association approves the application, it issues a blockchain trusted industrial control security crowdsourcing expert certification through the basic smart contract. The certification information is bound to the tester's DID identity, stored on the blockchain, and supports cross-platform querying.

[0067] S7: When the scores in each dimension are updated or the tester's level is promoted, the capability profile is automatically updated based on the basic smart contract to complete the multi-dimensional dynamic evaluation of the industrial control software crowdsourcing testers.

[0068] Ability profiles possess the following characteristics: Immutable: The portrait data is all derived from on-chain evidence storage data and cannot be manually modified; Dimensional Visualization: The tester's scores, levels, and areas of strength are visualized in the form of blockchain radar charts and bar charts. Contextualized tags: Based on the tester's score weight (referring to the proportion of the tester's participation in various types of projects, for example, if the tester participates in 10 power-related projects out of a total of 20 projects, the weight of the power project is 50%) and task performance, contextualized tags such as power industrial control, petrochemical industrial control, and rail transit industrial control are automatically generated to accurately reflect their industry adaptability. Cross-platform sharing: The ability profile is bound to the blockchain DID identity of the tester, which supports cross-platform sharing within the industrial control crowdsourcing testing industry, providing the industry with a standardized and credible basis for talent evaluation; Real-time updates: When the scores of testers in various dimensions are dynamically adjusted, the basic smart contract automatically updates the capability profile to ensure that the capability profile is synchronized with the actual capabilities of the testers.

[0069] This application enables end-to-end traceability and auditing of the blockchain process: Data traceability: All basic information, scores, behavior records, evaluation results, and incentive records of all testers are stored on the blockchain for evidence, supporting precise traceability queries by DID identity, time, task number, and other dimensions; Process auditing: Third-party auditing agencies and regulators in industries such as power / petrochemicals can use the blockchain traceability audit layer to conduct real-time audits of the entire process of evaluating industrial control system crowdsourcing testers (point calculation, weight adjustment, level promotion, incentive distribution), ensuring the compliance and credibility of the evaluation process; Log retention: All tracing and auditing operations generate operation logs, which are stored on the blockchain to ensure that the audit process is traceable.

[0070] Application scenario example: Power Scenarios: This application is used in the power industry for software security assessment of critical facilities such as power grid dispatching systems and substation automation systems. Through multi-dimensional integral calculations, testers who possess both cybersecurity expertise and familiarity with power monitoring protocols (such as IEC 61850) can be accurately selected, effectively identifying deep-seated risks such as control logic vulnerabilities and communication protocol defects. This is of great significance for preventing power grid paralysis and ensuring energy supply security, especially against the backdrop of accelerated smart grid construction, providing proactive defense capabilities for power industrial control systems.

[0071] In the steel metallurgy sector, this application assesses the security of core software such as blast furnace control systems and continuous casting machine monitoring platforms. By employing multi-dimensional integral calculations to prioritize and select testers familiar with PLC programming, industrial bus protocols (such as PROFIBUS), and possessing process knowledge, vulnerabilities that could lead to production interruptions or equipment failures can be identified. Its application directly impacts the stability of continuous production and is crucial for preventing safety accidents under high-temperature and high-pressure environments and improving the reliability of intelligent manufacturing.

[0072] In the oil and petrochemical industry: This application focuses on evaluating the capabilities of crowdsourced testing personnel for distributed control systems (DCS) and safety instrumented systems (SIS). By quantifying the testing personnel's mastery of functional safety standards (such as IEC 61511) and industrial protocols (such as OPC UA), it ensures that vulnerability detection covers all aspects of the process control chain. This has irreplaceable value in preventing control failure risks in flammable and explosive environments and ensuring safe production across the entire industry chain.

[0073] In the rail transit sector, high reliability of software such as signaling systems (CBTC) and train control networks is crucial. This application emphasizes the requirements for security certification standards (such as EN 50128) and real-time communication protocols (such as TRDP) by adjusting scenario-based dynamic weights, precisely recruiting experts with embedded system testing experience. Its application is directly related to train operation safety and efficiency, providing core technical support for urban rail transit networks to resist cyberattacks.

[0074] Equipment Manufacturing Scenario: This application is used for testing and evaluating software such as CNC systems and industrial robot control platforms. Through multi-dimensional integral calculations, it strengthens the assessment of professional capabilities in motion control algorithms and fieldbus technologies (such as EtherCAT), ensuring that testers can identify vulnerabilities that may lead to loss of machining accuracy or equipment collisions. This plays a crucial role in improving the reliability of intelligent manufacturing equipment and ensuring continuous production in digital factories.

[0075] This application utilizes a multi-dimensional scoring system to accurately match the capabilities of testers with industry needs across various industrial scenarios. This not only improves the efficiency and depth of vulnerability discovery in industrial control software but also constructs a dynamic and professional assessment barrier for the cybersecurity of core infrastructure, holding broad and significant importance for promoting the development of an industrial internet security ecosystem.

[0076] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments. The computer device can be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, memory, and I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device stores data to be processed. The I / O interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with an external terminal via a network connection. When the computer program is executed by the processor, it implements the steps in the above-described method embodiments.

[0077] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0078] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0079] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0080] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0081] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0082] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0083] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software based on blockchain, characterized in that, include: Build an industrial control crowdsourcing testing blockchain underlying platform based on a consortium blockchain, and deploy basic smart contracts on the industrial control crowdsourcing testing blockchain underlying platform; Based on the aforementioned basic smart contract, according to the basic information uploaded by the testers, the scores for each dimension are calculated according to the preset basic calculation rules of six dimensions, and the scores for each dimension are synchronized on the blockchain; the six dimensions include: reputation dimension, education dimension, professional dimension, industrial control field knowledge dimension, achievement dimension, and activity dimension. Based on the aforementioned basic smart contract, a capability profile is generated according to the scores of each dimension, and the capability profile is stored on the blockchain for evidence. Based on the aforementioned basic smart contract, the scenario-based dynamic weights of each dimension are automatically updated according to the subdivided industrial control scenarios, task risk levels, and task difficulty. The weight adjustment records are recorded on the blockchain for evidence storage throughout the entire process. Based on the aforementioned basic smart contract, the behavior data of testers during the crowd testing process is monitored in real time to see if they meet the scoring trigger rules, scoring trigger rules, or points decay mechanism. If they do, the points in the corresponding dimension are updated, and the points change record is recorded on the blockchain for evidence storage. Based on the aforementioned basic smart contract, a comprehensive capability score is calculated according to the updated scores of each dimension and the updated scenario-based dynamic weights. When the comprehensive capability score reaches the corresponding score threshold, an incentive operation is executed based on the basic smart contract, and the incentive record is stored on the blockchain. When the scores in each dimension are updated or the tester's level is promoted, the capability profile is automatically updated based on the basic smart contract to complete the multi-dimensional dynamic evaluation of the industrial control software crowdsourcing testers.

2. The multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software based on blockchain as described in claim 1, characterized in that, The formula for calculating the credit score is: Credit Score = Basic Credit Score + Behavioral Credit Score - Violation Deduction Points; The formula for calculating the points in the education dimension is: Education Points = (Degree Points × Full-time Coefficient) + Academic Qualification Points + Additional Points for Industrial Control Major; The formula for calculating the professional dimension score is: Professional Score = (Certificate Score × Industrial Control Certificate Coefficient) + Industry Experience Score + Training Score + Additional Score for Composite Ability; The formula for calculating the score of the knowledge dimension in the industrial control field is: Industrial control field knowledge score = online assessment score + target range practical operation score + subdivided field experience score; The formula for calculating the score of the achievement dimension is: Achievement Score = (Vulnerability Score × Industrial Control System Vulnerability Coefficient) + Use Case Innovation Score + Report Standardization Score + Remediation Implementation Score; The formula for calculating the activity level score is: Activity Score = Login Score in the last 90 days + Project Participation Score + Knowledge Sharing Score + Response Timeliness Score - Score Decay Score.

3. The multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software based on blockchain as described in claim 1, characterized in that, The system automatically updates the scenario-based dynamic weights for each dimension based on the subdivided industrial control scenarios, task risk levels, and task difficulty. Specifically, this includes: Contextualized dynamic weights are preset for each dimension of industrial control sub-scenarios; Dynamic adjustment rules are determined based on the task risk level and the task difficulty. The dynamic weights of each dimension are automatically updated based on the aforementioned dynamic adjustment rules.

4. The multi-dimensional dynamic evaluation method for crowdsourced testers of industrial control software based on blockchain as described in claim 3, characterized in that, The scoring triggering rule is as follows: When a core industrial control system vulnerability is submitted and confirmed, the vulnerability score will be doubled. When a vulnerability report is fixed and implemented by the vendor, points are awarded for the fix implementation. Sharing industrial control security testing knowledge or original test cases on the platform, and having them approved, will increase your knowledge sharing score. When participating in and completing industrial control crowdsourcing testing tasks marked as high-risk or high-difficulty, bonus points will be added to the scores in each dimension according to a preset additional ratio or additional value. When a student achieves a score no lower than the preset excellent score in the online assessment of industrial control knowledge or the practical test of industrial control security, the online assessment score or the practical test score will be increased.

5. The multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software based on blockchain as described in claim 2, characterized in that, The deduction trigger rules include: When the false positive rate of vulnerability reports exceeds the preset false positive rate threshold, the behavior reputation score will be reduced. When violations are found, points will be deducted or added for violations, and points will be deducted from the credit score. If the submitted vulnerability report is not prepared in accordance with the Industrial Control System Crowdsourcing Test Report Writing Specification, points will be deducted from the report's compliance score. Points will be deducted for failure to respond on time or abandonment of a task midway after it has been accepted.

6. The multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software based on blockchain as described in claim 2, characterized in that, The integral decay mechanism includes: If a tester does not participate in any industrial control crowdsourcing testing projects for 90 consecutive days, their activity points will decrease by 0.5% per day. If a tester does not participate in any industrial control crowdsourcing testing projects for 180 consecutive days, their professional points and industrial control knowledge points will decrease by 0.3% per day.

7. The multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software based on blockchain as described in claim 1, characterized in that, The incentive operations include automated promotion of levels, automated allocation of task priorities, automated adjustment of reward distribution ratios, and automated endorsement of industry certifications.

8. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that the processor executes the computer program to implement the blockchain-based multi-dimensional dynamic evaluation method for crowdsourced testing of industrial control software as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the multi-dimensional dynamic evaluation method for crowdsourced testers of industrial control software based on blockchain, as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the multi-dimensional dynamic evaluation method for crowdsourced testers of industrial control software based on blockchain, as described in any one of claims 1-7.

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