An exclusive software free authorization method based on terminal user capability forensics

Abstract

The application discloses an exclusive software free authorization method based on terminal user ability evidence, and belongs to the technical field of computer software authorization, and comprises the following steps: obtaining software products available for authorization and product application training and product communication channels thereof; determining terminal users according to the product communication channels, and training the terminal users according to the product application training to obtain authentication qualifications and authorization periods of the terminal users; obtaining identity information of the terminal users and MAC addresses of application hardware thereof; authorizing the application hardware with the software products according to the authorization periods, the identity information and the MAC addresses; training terminal users in need of obtaining free authorization, and giving ability authentication, so that the terminal users can obtain free authorization of the software products; and the problem that, when authorization is performed through existing software authorization methods, part of software authorization costs is high, leading to small software authorization quantity and a large quantity of software being idle is solved.

Description

Technical Field

[0001] This invention belongs to the field of computer software licensing technology, specifically relating to an exclusive free software licensing method based on end-user capability verification. Background Technology

[0002] In today's digital age, the widespread use of software has greatly improved efficiency and convenience in business operations, education, and personal life. However, the efficient use of software depends not only on the completeness of its functions but also on the user's correct understanding and use of the software. Therefore, integrated software licensing and training solutions have emerged, aiming to ensure that users can fully utilize the software's functions through reasonable licensing models and systematic training processes, thereby maximizing the software's value.

[0003] Currently, software licensing is mainly divided into two categories: open-source licensing and commercial licensing. While open-source software can be used for free, it usually lacks systematic training support, and users often face high learning costs and technical barriers. On the other hand, although commercial software provides technical support and training services, the licensing cost is high, and the licensing methods are limited and cannot be well applied to different groups of people. This leads to a large number of end users using cracked software, resulting in a small number of genuine software licenses and a large amount of software being idle.

[0004] Therefore, there is a need for an exclusive free software licensing method based on end-user capability authentication to address the problems existing in the current technology. Summary of the Invention

[0005] In view of this, the present invention provides an exclusive free software licensing method based on end-user capability forensics, which solves the problem that existing software licensing methods have high licensing costs for some software, resulting in a small number of licensed software programs and a large number of idle software programs.

[0006] To achieve the above objectives, this invention provides a method for exclusive free software licensing based on end-user capability forensics, comprising the following steps:

[0007] Obtain access to software products that can be used for licensing, as well as product application training and product communication channels;

[0008] Identify end users based on product communication channels, and train end users according to product application training to obtain their certification qualifications and authorization period;

[0009] Obtain the end user's identity information and the MAC address of their application hardware;

[0010] Software products are licensed to application hardware based on the authorization period, identity information, and MAC address.

[0011] As an embodiment of the present invention, product application training includes: training process, training software and hardware environment, training content and assessment standards;

[0012] Training is provided to end users based on product application training, resulting in end-user certification and authorization periods, including:

[0013] The corresponding level of product application training is determined based on the training level of the end user.

[0014] Training end users is conducted according to the training process and the training software and hardware environment.

[0015] After the training is completed, it is determined whether the end user meets the assessment criteria. If so, the end user's certification qualification is generated, and the authorization period is determined according to the end user's training level. The authorization period includes: one-year authorization, two-year authorization, and authorization of more than three years.

[0016] As one embodiment of the present invention, authorizing software products for application hardware based on identity information and MAC address includes:

[0017] Obtain authorization period, identity information, and MAC address;

[0018] Based on a preset encoding algorithm, an authorization code is generated according to the identity information and MAC address encoding; the authorization code is information of the terminal user that is not explicitly stated.

[0019] The software products for end-user application hardware are licensed based on the license code.

[0020] As an embodiment of the present invention, when the end user's software product is within the license period and the software product is updated, the corresponding software function modules of the software product are upgraded free of charge.

[0021] As an embodiment of the present invention, determining whether an end user meets the assessment criteria includes:

[0022] After the training is completed, end users will take an online test to obtain their theoretical assessment scores.

[0023] Acquire daily training data from end users; this data includes: actual operation completion rate and operational proficiency.

[0024] Based on a pre-defined calculation method, the end-user's competence index is calculated using daily training data and theoretical assessment scores.

[0025] Determine if the end user's capability index is greater than the preset capability value; if it is, determine if the end user meets the assessment criteria; if it is not, determine if the end user does not meet the assessment criteria.

[0026] As one embodiment of the present invention, it also includes:

[0027] The order in which training content is customized for end users;

[0028] Specifically:

[0029] Multiple training metadata are obtained based on the training content; the training content includes basic training and multiple independent training units, each training unit corresponding to a training metadata; the training metadata includes: course difficulty, estimated duration, knowledge point tags, and prerequisites;

[0030] The demand sequence is obtained by sorting the differences between end users and each training unit based on multiple training contents; the demand sequence is obtained by sorting each training unit in descending order of difference.

[0031] Obtain the merchant sequence of the training units in the training content, and determine the matching parameter for each training unit in the merchant sequence and the demand sequence; where the matching parameter is equal to the ranking of the training unit in the corresponding sequence, the higher the ranking, the lower the matching parameter;

[0032] Introduce a bias control factor g and set the threshold for the matching parameters of the manufacturer ranking. The optimization objective is defined as follows:

[0033] Y = min(A) x，Q +A x，W )

[0034] In the formula, Y is the minimum matching total energy, and A x，Q Matching parameters A for training unit x in the merchant sequence x，W Matching parameters for training unit x in the demand sequence;

[0035] Set the constraints as follows:

[0036]

[0037] Among them, the smaller the bias control factor, the lower the upper limit of the energy threshold for the manufacturer sequence, and the more favorable the matching result is for the manufacturer ranking.

[0038] Dynamically adjust the bias control factor to determine the bias in recommending training units to end users;

[0039] Select the most suitable training unit for end users based on their preferences.

[0040] 7. The method for exclusive software free licensing based on end-user capability forensics as described in claim 6, characterized in that,

[0041] Based on the differences between end users and each training unit obtained from multiple training contents, and sorted them, a demand sequence is obtained, including:

[0042] After the end users complete the basic training, a basic assessment is conducted on them to obtain target data. The target data includes: the level of various operational skills and the duration of training.

[0043] The difference between multiple training units and end users is calculated based on multiple training metadata and target data. The calculation formula is as follows:

[0044]

[0045] Among them, D x k represents the degree of difference between the terminal and the training unit x. i For the i-th prerequisite, s i t represents the operational capability level of the end user corresponding to the i-th prerequisite requirement. x Let t0 be the estimated duration of a single training session for training unit x, t0 be the duration of a single training session for an end user, K be the number of operational skills that the end user will know, n be the number of prerequisite skills required for a training unit, and α+β+ρ=1.

[0046] All training units are sorted from low to high according to their degree of difference to obtain the demand sequence.

[0047] The beneficial effects of this invention are as follows: by training and certifying end users who need to obtain free licenses, end users can obtain free licenses for software products; it solves the problem that when licensing through existing software licensing methods, the cost of licensing some software is high, resulting in a small number of licenses and a large number of software programs being idle.

[0048] Other advantages, objectives, and features of the invention will be set forth in the following description and will be apparent to those skilled in the art in some respects, or may be learned by practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0049] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the following figures are provided for illustration:

[0050] Figure 1 This is a schematic diagram of the process of the present invention;

[0051] Figure 2 This is a schematic diagram of the process for authenticating end-user capabilities according to the present invention. Detailed Implementation

[0052] like Figures 1-2 As shown, this invention provides a method for exclusive software free licensing based on end-user capability forensics, comprising:

[0053] Obtain access to software products that can be used for licensing, as well as product application training and product communication channels;

[0054] Identify end users based on product communication channels, and train end users according to product application training to obtain their certification qualifications and authorization period;

[0055] Obtain the end user's identity information and the MAC address of their application hardware;

[0056] Software products are licensed to application hardware based on the authorization period, identity information, and MAC address.

[0057] When an end-user's software product is within its license period and is updated, the corresponding software function modules of the software product will be upgraded free of charge.

[0058] The working principle of the above technical solution is as follows: In the actual licensing process, software products that can be licensed, along with their application training and communication channels, are acquired. Software products that can be licensed include those with complete architectural functions (front-end, back-end, underlying algorithms, and deployment software and hardware environment), and clear application scenarios, complete application cases, and data. Communication channels include those with fixed and clear channels for promotion, feature trials, end-user contact, feedback, and information acquisition (user communities, etc.). End-users can obtain product information about licensed software products through these communication channels. When an end-user wants to obtain a free license, they are trained according to the product application training. After completing the required training within the specified time... The process involves obtaining the end-user's certification qualifications and authorization period; acquiring the MAC address of the end-user's application hardware; and, based on a voluntary principle, obtaining the end-user's identity information; finally, authorizing the application hardware with software products based on the authorization period, identity information, and MAC address. Specifically, for users who have obtained training and certification qualifications, the end-user voluntarily provides identity information, such as email, telephone, or other types of information, along with the final software application hardware MAC address, and these various pieces of information are combined to form the authorization for the end-user. Simultaneously, during the authorization period, continuous free upgrades of the corresponding software functional modules are provided. It is worth noting that providing free authorization for commercial software through training and certification achieves exclusivity compared to cracked versions of commercial software.

[0059] The beneficial effects of the above technical solution are as follows: By training and certifying end users who need free licenses, end users can obtain free licenses for software products; this solves the problem that when licensing software through existing methods, the cost of licensing some software is high, resulting in a small number of licenses and a large amount of software being idle.

[0060] At the same time, by providing free licenses to end users, we can sustainably expand our end-user base; provide ongoing training and licenses to end users; offer free licenses (at the lowest cost) to users who want to use, are willing to use, and are capable of using the software; provide continuous software updates and upgrades based on user experience and requests; sustainably promote user experience-based innovation and integration; and for commercial customers with existing end-user licenses, we can minimize risks in their projects implementing large-scale, highly integrated systems.

[0061] The licensing method for this technical solution will be explained from four aspects: end users, market, licensed operators, and the shared ecosystem.

[0062] I. For various types of valuable software, especially software with high engineering application value, from the perspective of end users, there are the following problems: (1) A large number of end users cannot obtain legal usage licenses, which leads to the production of a large number of cracked software. (2) Software licenses mainly provide after-sales user training. Due to insufficient training time, number of licenses, and training preparation, end users cannot effectively use the relevant software, making it difficult to continuously and completely generate engineering application value. (3) Under the existing software sales model, once the contract is completed, it is difficult to provide systematic and continuous training, especially due to various reasons such as job changes and students leaving school, which makes it difficult to understand and use the software. (4) Regarding software upgrades, the existing model provides a maximum of one year of free upgrades.

[0063] Therefore, the licensing method of this technical solution adopts continuous training and qualification certification, and the use authorization is delegated to end customers who want to use it, are able to use it, and can directly solve engineering applications. End users obtain application training and authorization through legal channels, and receive continuous upgrades to the application's functional modules.

[0064] II. From a market perspective, the following problems exist in the software market: (1) The software market based on the traditional licensing model is chaotic in terms of versions, with a large number of products cracked through unreasonable channels and carrying various viruses. (2) End users cannot obtain effective licenses at low cost, while commercial users need to obtain effective licenses at high cost, but the number of licenses is extremely limited, resulting in the coexistence of effective and unreasonable licenses. (3) Software environment upgrades and software upgrades cannot effectively promote the stability and growth of the user group due to issues such as additional purchase costs and user training. (4) Open source software driven by personal interests is immature and training is lacking.

[0065] Therefore, the licensing method of this technical solution can standardize the version status of software application markets, provide continuous upgrade services and software security testing, upgrade, improve and expand software functions through continuous cooperation and interaction with end users, and maintain the stability and growth of the number of end users through continuous training and licensing.

[0066] III. From the perspective of the authorized operator, as the authorized operator, the following problems can be solved through reasonable and continuous operation: (1) The existing authorization and operation model, due to its direct facing of commercial customers, requires high market operation costs for new or professional software. That is, from the end customer's acceptance of the application to the formation of the decision to purchase, and finally to the completion of the project bidding, delivery, training, maintenance, etc., the long process generates expensive human and financial costs. (2) Due to the limited number of effective authorizations delivered to commercial customers, and the lack of motivation and financial support for continuous training and services, the size of the end user group has shrunk or even disappeared completely, resulting in a large number of idle software and causing irreparable damage to both the supply and demand sides: the supplier cannot form continuous business opportunities and orders, and the demand side's existing projects are shelved, which cannot promote the application of engineering and results, resulting in a lose-lose situation. (3) Relying on the traditional authorization model, it is impossible to effectively form incremental end users. The new end users are basically forced to join, and the lack of continuous training leads to a major deviation in the evaluation of the software application results. (4) The operational value shifts from sales to service, development, market operations and overall company operations, no longer relying on the "sales operation" model, thus creating a driving force for software upgrades, end-user experience upgrades and continuous end-user growth. (5) This model can effectively form a good interaction between the authorized operator and the authorized user, and continuously upgrade, improve and progress the software ecosystem.

[0067] IV. From software development to end users, and then from end users to software improvement and refinement, a complete, interactive, and cyclical ecosystem is needed. The key actions driving this ecosystem are: (1) The direction and purpose of software development need to be driven by end users. (2) End users need continuous training and certification for using the software. (3) End users who have obtained qualified certification need continuous, updated, and low-cost licensing. (4) Software application results (public results) based on continuous, updated, and low-cost licensing, as well as user experience and user suggestions, will continuously drive software updates and upgrades. (5) Software based on user experience, suggestions, and continuous improvement and updates can attract more users to participate in training and certification (user group issues and expansion). In the entire cycle, licensing providers, software developers, and end users jointly form a low-cost and sustainable software ecosystem model.

[0068] In one embodiment, product application training includes: training process, training software and hardware environment, training content and assessment standards;

[0069] Training is provided to end users based on product application training, resulting in end-user certification and authorization periods, including:

[0070] The corresponding level of product application training is determined based on the training level of the end user.

[0071] Training end users is conducted according to the training process and the training software and hardware environment.

[0072] After the training is completed, it is determined whether the end user meets the assessment criteria. If so, the end user's certification qualification is generated, and the authorization period is determined according to the end user's training level. The authorization period includes: one-year authorization, two-year authorization, and authorization of more than three years.

[0073] In one embodiment, authorizing software products for application hardware based on identity information and MAC address includes:

[0074] Obtain authorization period, identity information, and MAC address;

[0075] Based on a preset encoding algorithm, an authorization code is generated according to the identity information and MAC address encoding; the authorization code is information of the terminal user that is not explicitly stated.

[0076] The software products for end-user application hardware are licensed based on the license code.

[0077] The working principle and beneficial effects of the above technical solution are as follows: During the generation of the authorization code, the authorization code must contain some of the end user's identity information and the end user's application hardware information; at the same time, the final generated authorization code does not contain explicit end user information.

[0078] In one embodiment, determining whether an end user meets the assessment criteria includes:

[0079] After the training is completed, end users will take an online test to obtain their theoretical assessment scores.

[0080] Acquire daily training data from end users; this data includes: actual operation completion rate and operational proficiency.

[0081] Based on a pre-defined calculation method, the end-user's competence index is calculated using daily training data and theoretical assessment scores.

[0082] Determine if the end user's capability index is greater than the preset capability value; if it is, determine if the end user meets the assessment criteria; if it is not, determine if the end user does not meet the assessment criteria.

[0083] The working principle and beneficial effects of the above technical solution are as follows: In actual use, in order to quickly certify user capabilities and ensure that end-users can quickly use authorized software after completing training, the solution automatically licenses the software to end-users and automates the capability certification process. Specifically, after monitoring that an end-user has completed the training course, an online test is conducted to obtain the end-user's theoretical assessment score. The content and difficulty of the online test are determined according to the training level selected by the user, and the test methods include, but are not limited to, written tests or telephone Q&A. Then, daily training data of the end-user during daily training is obtained. This daily training data includes: actual operation completion rate and operation proficiency. Actual operation completion rate includes, for example, the number and accuracy of tasks completed during daily training. Operation proficiency includes, for example, the accuracy of operation steps and average operation time. All of these data are collected through monitoring and recording during daily training. The collected daily training data and theoretical assessment scores are then cleaned to remove outliers and duplicates to ensure data quality. Different types of data are standardized and converted to the same unit of measurement (e.g., converting all data to a percentage score) for comprehensive analysis. The preset calculation method uses a weighted fusion approach, assigning different weights to the importance of user capabilities based on different data types to calculate the end-user's capability index. The system then determines whether the end-user's capability index is greater than a preset capability value. If it is, the end-user is deemed to meet the assessment standards; otherwise, they are deemed not to meet the standards. The system automatically certifies and authorizes end-users who have completed training to ensure they can use the software immediately after completing the training.

[0084] In one embodiment, it also includes:

[0085] The order in which training content is customized for end users;

[0086] Specifically:

[0087] Multiple training metadata are obtained based on the training content; the training content includes basic training and multiple independent training units, each training unit corresponding to a training metadata; the training metadata includes: course difficulty, estimated duration, knowledge point tags, and prerequisites;

[0088] The demand sequence is obtained by sorting the differences between end users and each training unit based on multiple training contents; the demand sequence is obtained by sorting each training unit in descending order of difference.

[0089] Obtain the merchant sequence of the training units in the training content, and determine the matching parameter for each training unit in the merchant sequence and the demand sequence; where the matching parameter is equal to the ranking of the training unit in the corresponding sequence, the higher the ranking, the lower the matching parameter;

[0090] Introduce a bias control factor g and set the threshold for the matching parameters of the manufacturer ranking. The optimization objective is defined as follows:

[0091] Y = min(A) x，Q +A x，W )

[0092] In the formula, Y is the minimum matching total energy, and A x，Q Matching parameters A for training unit x in the merchant sequence x，W Matching parameters for training unit x in the demand sequence;

[0093] Set the constraints as follows:

[0094]

[0095] Among them, the smaller the bias control factor, the lower the upper limit of the energy threshold for the manufacturer sequence, and the more favorable the matching result is for the manufacturer ranking.

[0096] Dynamically adjust the bias control factor to determine the bias in recommending training units to end users;

[0097] Select the most suitable training unit for end users based on their preferences.

[0098] Based on the differences between end users and each training unit obtained from multiple training contents, and sorted them, a demand sequence is obtained, including:

[0099] After the end users complete the basic training, a basic assessment is conducted on them to obtain target data. The target data includes: the level of various operational skills and the duration of training.

[0100] The difference between multiple training units and end users is calculated based on multiple training metadata and target data. The calculation formula is as follows:

[0101]

[0102] Among them, D x k represents the degree of difference between the terminal and the training unit x. i For the i-th prerequisite, s i t represents the operational capability level of the end user corresponding to the i-th prerequisite requirement. x Let t0 be the estimated duration of a single training session for training unit x, t0 be the duration of a single training session for an end user, K be the number of operational skills that the end user will know, n be the number of prerequisite skills required for a training unit, and α+β+ρ=1.

[0103] All training units are sorted from low to high according to their degree of difference to obtain the demand sequence.

[0104] The working principle of the above technical solution is as follows: During the process of providing free licenses for commercial software to end users through training, the training content is uniformly provided by the manufacturer. The manufacturer divides the entire software usage into basic training and multiple training units. The operations required for each training unit are independent, resulting in little correlation between different training units for end users. Therefore, the issue of sequencing these training units arises. To increase the number of licenses granted and facilitate promotion, manufacturers often place training content related to the most popular industry-specific operations using the software at the beginning, and adjust the order based on the popularity of online course terms to attract end users and increase license numbers. However, the varying skill levels of end users participating in the training mean that some end users may find the training too difficult when following the manufacturer's predetermined sequence. Or it might be too simplistic; therefore, we obtain the training content provided by the manufacturer and determine the training metadata for each training unit. This training metadata includes: course difficulty (generally tiered, such as level one, level two, etc.), estimated duration, knowledge point tags, and prerequisites (the user needs to master the operation of a specific software and the corresponding skill level; skill level includes: only understanding, knowing some simple operations, being able to apply it proficiently, etc.). After the end-user completes the basic training, they fill out an assessment report, which includes the level of each prerequisite required for each training unit, etc. Then, based on multiple training metadata and target data, we calculate the degree of difference between multiple training units and the end-user, and sort all training units from low to high degree of difference to obtain a demand sequence. This gives us a demand sequence of training units based on the end-user's actual situation, ensuring maximum benefit from the end-user training.

[0105] However, since manufacturers provide training, simply maximizing the benefits for end-users might harm their interests. Conversely, training based solely on the manufacturer's predetermined order might not be suitable for end-users with varying skill levels. Therefore, when selecting training units for end-users, both sequences should be considered to ensure mutual benefit. However, due to differing costs, a bias can be applied to the two sequences at different stages to maximize the benefit of one side. Specifically, matching parameters for each training unit in the merchant and demand sequences are determined. The matching parameter equals the training unit's ranking within its corresponding sequence; the higher the ranking, the lower the matching parameter. The matching parameter values ​​are {1, 2, 3, ..., N}, where N equals the number of training units. A matching bias model is then constructed to identify the degree of bias for both sides. A bias control factor g is introduced to control the degree of bias; that is, the smaller the bias control factor g, the lower the upper limit of the matching parameter threshold set for the manufacturer sequence. When selecting training units, the selection process prioritizes the manufacturer sequence. During the selection process, if the matching parameter of the manufacturer sequence is less than the matching parameter threshold m, the selection proceeds normally. Otherwise, training units that would cause the matching parameter of the manufacturer sequence to exceed m are removed, ensuring that the matching parameter of the manufacturer sequence remains within the matching parameter threshold. Then, a fairness index is constructed to determine the degree of fairness in matching the manufacturer sequence and the demand sequence. For example, given a manufacturer sequence (d,c,m,a,h,l,e) with matching parameters (1,2,3,4,5,6,7) and a demand sequence (l,h,m,e,c,a,d) with matching parameters (1,2,3,4,5,6,7), in the absence of bias, training unit m best matches the interests of both parties (the total matching energy of the selected training unit is minimized). When biased towards manufacturers, the matching parameter threshold is set to 2, resulting in only two training units (d,c) within the options for the manufacturer sequence; therefore, training unit c is selected.

[0106] The beneficial effects of the above technical solution are as follows: By ranking training units based on the difference calculated from end-user evaluation reports and training metadata, the training content can be better matched to the user's own knowledge level and ability. For example, for users with low proficiency in software prerequisites after basic training, training units with lower difficulty levels that match their prerequisite knowledge will be arranged first, avoiding frustration caused by overly difficult content. This allows users to gradually improve their software operation skills at a relatively comfortable difficulty level. Simultaneously, when the difficulty and pace of the training content match the user's ability, users are more likely to gain a sense of accomplishment. After completing training tasks that are appropriate to their abilities, users' confidence will increase, leading to more proactive engagement in subsequent training, forming a virtuous cycle and improving the overall training completion rate and quality. By favoring specific manufacturers and their needs, when prioritizing manufacturers, training units with high popularity and significant contribution to software licensing can be highlighted. This strategy helps manufacturers more accurately present attractive training content to end users, encouraging them to learn and use the software in depth, thereby increasing its application and licensing across different industries and expanding its market share. By introducing bias control factors, manufacturers can flexibly adjust the ranking bias of training units according to different market stages and strategic objectives. For example, at appropriate times, manufacturers can appropriately increase the bias towards their own product sequence to quickly improve software awareness and licensing volume; while in a relatively mature stage of software development, they can consider user needs more to improve user loyalty and satisfaction. This flexible adjustment mechanism allows manufacturers to better adapt to dynamic market environments and changes in user needs.

[0107] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made to it in form and detail without departing from the scope defined by the claims of the present invention.

Claims

1. A method for exclusive free software licensing based on end-user capability forensics, characterized in that, Includes the following steps: Obtain access to software products that can be used for licensing, as well as product application training and product communication channels; Identify end users based on product communication channels, and train end users according to product application training to obtain their certification qualifications and authorization period; Obtain the end user's identity information and the MAC address of their application hardware; Software products are licensed to application hardware based on the authorization period, identity information, and MAC address.

2. The method for exclusive software free licensing based on end-user capability forensics as described in claim 1, characterized in that, Product application training includes: training process, training software and hardware environment, training content and assessment standards; Training is provided to end users based on product application training, resulting in end-user certification and authorization periods, including: The corresponding level of product application training is determined based on the training level of the end user. Training end users is conducted according to the training process and the training software and hardware environment. After the training is completed, it is determined whether the end user meets the assessment criteria. If so, the end user's certification qualification is generated, and the authorization period is determined according to the end user's training level. The authorization period includes: one-year authorization, two-year authorization, and authorization of more than three years.

3. The method for exclusive software free licensing based on end-user capability forensics according to claim 1, characterized in that, Authorize software products for application hardware based on identity information and MAC address, including: Obtain authorization period, identity information, and MAC address; Based on a preset encoding algorithm, an authorization code is generated according to the identity information and MAC address encoding; the authorization code is information of the terminal user that is not explicitly stated. The software products for end-user application hardware are licensed based on the license code.

4. The method for exclusive software free licensing based on end-user capability forensics according to claim 1, characterized in that, When the end user's software product is within the license period and the software product is updated, the corresponding software function modules of the software product can be upgraded free of charge.

5. The method for exclusive software free licensing based on end-user capability forensics according to claim 1, characterized in that, Determining whether end users meet the assessment criteria includes: After the training is completed, end users will take an online test to obtain their theoretical assessment scores. Acquire daily training data from end users; this data includes: actual operation completion rate and operational proficiency. Based on a pre-defined calculation method, the end-user's competence index is calculated using daily training data and theoretical assessment scores. Determine if the end user's capability index is greater than the preset capability value; if it is, determine if the end user meets the assessment criteria; if it is not, determine if the end user does not meet the assessment criteria.

6. The method for exclusive software free licensing based on end-user capability forensics according to claim 1, characterized in that, Also includes: The order in which training content is customized for end users; Specifically: Multiple training metadata are obtained based on the training content; the training content includes basic training and multiple independent training units, each training unit corresponding to a training metadata; the training metadata includes: course difficulty, estimated duration, knowledge point tags, and prerequisites; The demand sequence is obtained by sorting the differences between end users and each training unit based on multiple training contents; the demand sequence is obtained by sorting each training unit in descending order of difference. Obtain the merchant sequence of the training units in the training content, and determine the matching parameters for each training unit in the merchant sequence and the demand sequence; where the matching parameter is equal to the ranking of the training unit in the corresponding sequence, the higher the ranking, the lower the matching parameter; Introduce a bias control factor g and set the threshold for the matching parameters of the manufacturer ranking. The optimization objective is defined as follows: Y=min(A x，Q +A x，W ) In the formula, Y is the minimum matching total energy, and A x，Q Matching parameters A for training unit x in the merchant sequence x，W Matching parameters for training unit x in the demand sequence; Set the constraints as follows: Among them, the smaller the bias control factor, the lower the upper limit of the energy threshold for the manufacturer sequence, and the more favorable the matching result is for the manufacturer ranking. Dynamically adjust the bias control factor to determine the bias in recommending training units to end users; Select the most suitable training unit for end users based on their preferences.

7. The method for exclusive software free licensing based on end-user capability forensics according to claim 6, characterized in that, Based on the differences between end users and each training unit obtained from multiple training contents, and sorted them, a demand sequence is obtained, including: After the end users complete the basic training, a basic assessment is conducted on them to obtain target data. The target data includes: the level of various operational skills and the duration of training. The difference between multiple training units and end users is calculated based on multiple training metadata and target data. The calculation formula is as follows: Among them, D x k represents the degree of difference between the terminal and the training unit x. i For the i-th prerequisite, s i t represents the operational capability level of the end user corresponding to the i-th prerequisite requirement. x Let t0 be the estimated duration of a single training session for training unit x, t0 be the duration of a single training session for an end user, K be the number of operational skills that the end user will know, n be the number of prerequisite skills required for a training unit, and α+β+ρ=1. All training units are sorted from low to high according to their degree of difference to obtain the demand sequence.

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