Software development verification system based on large model

Abstract

The invention discloses a software development verification system based on a large model, which relates to the technical field of software development and comprises a data acquisition module, a data processing module, a verification analysis module and an evaluation analysis module. According to the development verification system, comprehensive encryption is carried out by comprehensively considering a plurality of encryption parameters such as the key length and the encryption algorithm type, the security of sensitive information is ensured through the method, multi-level and all-around data integrity verification is achieved by combining a plurality of verification parameters and mechanisms, and the verification efficiency is improved. The method can effectively cope with complex and changeable attack means, a data integrity verification mechanism can also ensure the integrity and authenticity of data and prevent the data from being tampered or damaged, and through comprehensive prediction and analysis of the software development process, the method not only provides comprehensive safety guidance and optimization suggestions, but also improves the safety of the software development process. And dynamic adjustment and optimization can be carried out according to the actual condition of the software development process.

Description

Technical Field

[0001] The present invention relates to the technical field of software development, and in particular to a software development verification system based on a large model. Background Art

[0002] The software development model refers to the structural framework of the entire process, activities and tasks of software development. Software development includes stages such as requirements, design, coding and testing. During the software development process, it is crucial to protect the software development content from illegal acquisition and tampering by external personnel. With the increasing scale and complexity of software, traditional encryption and data integrity verification methods can no longer meet the security needs of modern software development. Especially in the application context of large models such as deep learning models and artificial intelligence algorithms, the software development content includes not only the code itself, but also covers sensitive information such as model parameters and training data. Therefore, a more efficient and comprehensive encryption verification method is needed to ensure the security of software development content.

[0003] The existing development and verification systems currently in place may lack optimization for the encryption and verification needs of developers during the software development process. In the context of large models, software development content contains a large amount of sensitive information and thus has poor security. Existing encryption methods may only rely on a single encryption algorithm, which is difficult to adapt to complex and changing attack environments. Existing data integrity verification mechanisms may be based on a single verification algorithm or parameter, which may make it difficult to cope with complex and changing attack methods, especially in large models with large data volumes and complex structures. They may be damaged by specific types of attacks, and existing technologies may lack a comprehensive evaluation system and are unable to provide developers with comprehensive security guidance and optimization suggestions. Summary of the invention

[0004] The purpose of the present invention is to provide a software development verification system based on a large model, which solves the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a software development verification system based on a large model, comprising:

[0006] Data collection module: The data collection module collects source code, encryption key length, encryption algorithm type, data transmission records and developer operation logs during the software development process;

[0007] Data processing module: The source code, encryption key length, encryption algorithm type, data transmission record and developer operation log are input into the data processing module. The data processing module cleans, de-duplicates and formats the input data, and outputs the total number of encryption parameters, the strength of the i-th encryption parameter and the hash value of the w-th data block;

[0008] Verification analysis module: the total number of encryption parameters, the strength of the i-th encryption parameter and the w-th data block PD w The hash value is input into the verification and analysis module, and the verification and analysis module outputs the encryption strength assessment value MEA, the data integrity check value MPB and the comprehensive prediction analysis value MMS;

[0009] Evaluation and analysis module: The encryption strength assessment value MEA, data integrity check value MPB and comprehensive prediction analysis value MMS are input into the evaluation and analysis module. The evaluation and analysis module analyzes the input values ​​to evaluate the encryption strength and data integrity of software development, and then formulates corresponding encryption strategies and data protection measures based on the analysis and evaluation results. In addition, data is continuously collected during the software development process, and encryption strength and data integrity assessments are regularly performed.

[0010] Optionally, the verification and analysis module includes: an encryption strength submodule, a data integrity submodule and a verification prediction and analysis submodule.

[0011] Optionally, the calculation formula of the encryption strength submodule is as follows:

[0012]

[0013] in:

[0014] MEA refers to the encryption strength assessment value, n refers to the total number of encryption parameters, i refers to the index of the encryption parameter, MA i Refers to the weight of the i-th encryption parameter, MK i refers to the strength of the i-th encryption parameter, m refers to the number of external factors and conditions related to encryption strength assessment, j refers to the index of the external factor condition, MD j Refers to the jth external factor value of the encryption algorithm;

[0015] Refers to the security index of the encryption algorithm itself;

[0016] Refers to the comprehensive impact of external environmental factors on the security of encryption algorithms;

[0017] Refers to the negative impact of the interaction between the internal parameters of the computational encryption algorithm and external factors on the encryption strength;

[0018] log(n+m+1) refers to the encryption strength adjustment factor, which is used to adjust the evaluation value to make it more accurate;

[0019] The processing process of the encryption strength submodule is as follows: the total number of encryption parameters n and the strength MK of the i-th encryption parameter i Input to the encryption strength submodule and based on the weight MA of the i-th encryption parameteri Output the encryption strength assessment value MEA.

[0020] Optionally, the calculation formula of the data integrity submodule is as follows:

[0021]

[0022] in:

[0023] MPB refers to the data integrity check value, p refers to the total number of data blocks, w refers to the index of the data block, H w (PD w ) refers to the wth data block PD w The hash value of q refers to the total number of check codes, s refers to the index of the check code, MS s Reference and data block PD w The associated sth data integrity check code;

[0024] Refers to the percentage value of the encryption strength impact factor;

[0025] Refers to the overall picture of data integrity;

[0026] Refers to the degree of loss of data integrity;

[0027] The processing process of the data integrity submodule is as follows: the wth data block PD w The hash value H w (PD w ) and the encryption strength assessment value MEA are input to the data integrity sub-module, and a data integrity check value MPB is output based on the total number of data blocks p and the total number of check codes q.

[0028] Optionally, the calculation formula of the verification prediction analysis submodule is as follows:

[0029]

[0030] in:

[0031] MMS refers to the comprehensive forecast analysis value, SAA refers to the adjustment weight of MEA, SAB refers to the adjustment weight of MPB, SAC refers to the adjustment coefficient of the key forecast parameter, t refers to the number of key forecast parameters, g refers to the index of the key forecast parameter, MMC g Refers to MMX g Weight coefficient of MMX g Refers to the gth key prediction parameter;

[0032] The processing process of the verification prediction analysis submodule is as follows: the encryption strength assessment value MEA and the data integrity check value MPB are input into the verification prediction analysis submodule, and the verification prediction analysis submodule outputs the comprehensive prediction analysis value MMS.

[0033] Optionally, the strength MK of the i-th encryption parameter in the encryption strength submodule i The encryption parameters i in include: key type, encryption algorithm type, encryption mode type, and security feature type.

[0034] Optionally, the key type refers to the parameter type in the key, including the key length. The longer the key length, the higher the encryption strength, because more computing resources are required to crack a longer key.

[0035] The encryption algorithm type refers to the different security features of different encryption algorithms. The big data protection algorithm is suitable for the encryption protection of big data, and the sensitive data protection algorithm is used for the encryption protection of sensitive information.

[0036] Optionally, the jth external factor value MD of the encryption algorithm in the encryption strength submodule j The external factors j in include: the attacker's computing power type, key management type, and encryption algorithm implementation type.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] 1. The present invention outputs an encryption strength evaluation value through an encryption strength submodule. This submodule can select an algorithm with higher encryption strength according to the calculation result of the encryption strength evaluation value, thereby effectively protecting the software development content from being stolen by outsiders. By adjusting encryption algorithm parameters such as key length, data block size, etc., developers can observe changes in encryption strength evaluation values ​​and then optimize encryption strategies to improve overall security. The higher the encryption strength evaluation value, the better the protection effect of the encryption algorithm. This helps developers to intuitively understand the performance of the encryption algorithm. By comparing the encryption strength evaluation values ​​of different encryption schemes, developers can select the optimal encryption scheme to improve the security of the software. In the software development process, the encryption strength evaluation value can be used as an important indicator for security compliance checks to ensure that the software meets relevant security standards and requirements.

[0039] 2. The present invention outputs a data integrity check value MPB through a data integrity submodule, and calculates the data integrity check value to ensure that the data in the software development process remains consistent during transmission, storage and processing to prevent data tampering or damage. Data integrity is the basis of software reliability. The data integrity check value can reflect the integrity status of the data. When the data is tampered with or damaged, the data integrity check value will change, thereby triggering a warning or error prompt. During the software development process, data errors may cause software crashes or functional abnormalities. Through the changes in the data integrity check value, developers can quickly locate and repair data errors to improve troubleshooting efficiency. Data integrity is an important manifestation of software quality. By providing reliable data integrity check results, users' trust and satisfaction with the software can be enhanced.

[0040] 3. The present invention outputs a comprehensive prediction and analysis value MMS through the verification prediction and analysis submodule. Through the comprehensive prediction and analysis value, developers can predict the possible security risks in the software development process and take corresponding preventive measures. The calculation result of the comprehensive prediction and analysis value can provide data support for developers to formulate security strategies to ensure the security of software in various stages such as development, testing, and deployment. By comparing the comprehensive prediction and analysis values ​​of different stages, developers can find weak links in security and take corresponding improvement measures. In the software development process, the comprehensive prediction and analysis value can be used as an important basis for security decision-making. When deciding whether to release a new version of software, developers can refer to the comprehensive prediction and analysis value to evaluate the security risks of the software.

[0041] 4. The weight MA of the i-th encryption parameter in the encryption strength submodule based on the data integrity check value MPB of the present invention i By iteratively adjusting these weights, the encryption process can be more adapted to the requirements of data integrity. When the data integrity check value indicates low data integrity, the weights of encryption parameters related to data integrity protection can be increased to improve the overall encryption strength. Conversely, when the data integrity check value is high, we can appropriately reduce these weights to balance encryption strength and other possible performance requirements. This iterative form can flexibly adjust the encryption strategy according to the actual situation and data integrity requirements in the software development process by iteratively adjusting the weights, which helps to ensure that the encryption verification process can protect the software development content from being seen by outsiders and can adapt to different development environments and requirements. By iteratively adjusting the weights in response to changes in the data integrity check value, the protection of data integrity can be enhanced and the risk of data being tampered with or damaged during the encryption process can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flowchart of the method steps for the software development and verification system based on the big model;

[0043] Figure 2 This is the overall structural diagram of the software development and verification system based on the big model;

[0044] Figure 3 This is a structural diagram of the verification and analysis module in this large model-based software development and verification system. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Regarding this software development verification system based on a large model, it is different from the existing development verification system. The existing development verification system may lack optimization for the special needs of developers for encryption verification during the software development process. In the context of large models, the software development content contains a large amount of sensitive information and thus has poor security. In addition, the existing encryption method may only rely on a single encryption algorithm, which is difficult to adapt to complex and changeable attack environments. The existing data integrity verification mechanism may be based on a single verification algorithm or parameter, which is difficult to cope with complex and changeable attack methods. Especially in the case of large models with large data volumes and complex structures, it may be damaged by specific types of attacks. In addition, the existing technology may lack a comprehensive evaluation system and cannot provide developers with comprehensive security guidance and optimization suggestions.

[0047] This development and verification system performs comprehensive encryption by comprehensively considering multiple encryption parameters, such as key length and encryption algorithm type. This method ensures the security of sensitive information. The present invention combines multiple verification parameters and mechanisms to achieve multi-level and comprehensive data integrity verification. This method can effectively respond to complex and changeable attack methods, and the data integrity verification mechanism can also ensure the integrity and authenticity of the data to prevent data from being tampered with or destroyed. The present invention comprehensively predicts and analyzes the software development process. This method not only provides comprehensive security guidance and optimization suggestions, but also can dynamically adjust and optimize according to the actual situation of the software development process.

[0048] Example: See Figures 1 to 3 ,This implementation provides a software development verification system based on a large model, including:

[0049] The data collection module collects source code, encryption key length, encryption algorithm type, data transmission records and developer operation logs during the software development process.

[0050] The source code, encryption key length, encryption algorithm type, data transmission record and developer operation log are input into the data processing module, which cleans, deduplicates and formats the input data and outputs the total number of encryption parameters, the strength of the i-th encryption parameter and the hash value of the w-th data block.

[0051] The total number of encryption parameters, the strength of the i-th encryption parameter, and the w-th data block PD w The hash value is input into the verification and analysis module, and the verification and analysis module outputs the encryption strength assessment value MEA, the data integrity check value MPB and the comprehensive prediction analysis value MMS.

[0052] The encryption strength assessment value MEA, data integrity check value MPB and comprehensive prediction analysis value MMS are input into the evaluation and analysis module, which analyzes the input values ​​to evaluate the encryption strength and data integrity of software development, and then formulates corresponding encryption strategies and data protection measures based on the analysis and evaluation results. In addition, data is continuously collected during the software development process, and encryption strength and data integrity assessments are performed regularly.

[0053] The verification and analysis module includes an encryption strength submodule, a data integrity submodule and a verification prediction and analysis submodule.

[0054] In this embodiment, according to the calculation results of MEA, developers can choose an algorithm with higher encryption strength to encrypt the software development content. During the software development process, developers can use MEA to evaluate the encryption effect regularly to ensure that the encryption algorithm always maintains a high level of protection. During the software development process, developers can use MPB to verify the integrity of the data to ensure that the data is not tampered with or damaged during transmission, storage and processing. In order to prevent the loss or damage of data from causing the leakage of software development content, developers can establish a data backup mechanism and regularly use MPB to verify the integrity of the backup data. At different stages of software development, developers can use MMS to comprehensively evaluate the security status of the software, including encryption strength, data integrity and other aspects. According to the calculation results of MMS, developers can formulate targeted security strategies to strengthen the security protection of the software. For example, for modules with low encryption strength, the encryption algorithm can be strengthened or additional security measures can be added. For modules that fail the data integrity check, data errors can be repaired or the data verification mechanism can be strengthened.

[0055] See also Figures 1 to 3 , the encryption strength submodule processing process is as follows:

[0056]

[0057] in:

[0058] MEA refers to the encryption strength assessment value, which comprehensively evaluates the protection strength of the encryption algorithm for the software development content. This value is a quantitative indicator that reflects the effectiveness of the encryption algorithm in protecting the software content from unauthorized access or tampering. Calculating MEA helps developers understand the effectiveness of the current encryption strategy and make corresponding adjustments. A high MEA value means that the encryption algorithm provides stronger protection, while a low value may indicate the need to improve the encryption strategy or add additional encryption measures.

[0059] n refers to the total number of encryption parameters, i refers to the index of encryption parameters, MA i Refers to the weight of the i-th encryption parameter, MK i refers to the strength of the i-th encryption parameter, m refers to the number of external factors and conditions related to encryption strength assessment, j refers to the index of the external factor condition, MD j Refers to the jth external factor value of the encryption algorithm.

[0060] Refers to the security index of the encryption algorithm itself, which is calculated by the weighted sum of the squares of the encryption algorithm key length and encryption strength.

[0061] Refers to the combined impact of external environmental factors on the security of encryption algorithms, that is, the product of the impact of external factors on encryption strength.

[0062] Refers to the negative impact of the interaction between the internal parameters of the computational encryption algorithm and external factors on the encryption strength.

[0063] log(n+m+1) refers to the encryption strength adjustment factor, which is used to adjust the evaluation value to make it more accurate.

[0064] The total number of encryption parameters n and the strength of the i-th encryption parameter MK i Input to the encryption strength submodule and based on the weight MA of the i-th encryption parameter i Output the encryption strength assessment value MEA.

[0065] In this embodiment, this submodule converts various encryption algorithm parameters into encryption strength evaluation values ​​through calculation, so that developers can intuitively understand the protection effect of the encryption algorithm. During the software development process, developers can select an algorithm with higher encryption strength based on the calculation results of MEA, thereby more effectively protecting the software development content from being stolen by outsiders. By adjusting the encryption algorithm parameters, such as key length, data block size, etc., developers can observe the changes in MEA values, and then optimize the encryption strategy to improve overall security. The calculation results of MEA have a significant role and effect on the software development verification method of large models. The higher the MEA value, the better the protection effect of the encryption algorithm. This helps developers intuitively understand the performance of the encryption algorithm. By comparing the MEA values ​​of different encryption schemes, developers can select the optimal encryption scheme to improve the security of the software. During the software development process, the MEA value can be used as one of the important indicators for security compliance checks to ensure that the software meets relevant security standards and requirements.

[0066] See also Figures 1 to 3 , the data integrity submodule processing process is as follows:

[0067]

[0068] in:

[0069] MPB refers to the data integrity check value, which comprehensively verifies the integrity of data during the software development process. This value is also a quantitative indicator used to evaluate whether the data maintains its originality and accuracy during transmission, storage or processing. MPB helps developers monitor and maintain data integrity. A high MPB value indicates that the data maintains a high level of integrity during the software development process, while a low value may mean that the data has been damaged or tampered with at some point, and appropriate measures need to be taken to repair or prevent it.

[0070] p refers to the total number of data blocks, and w refers to the index of the data block.

[0071] H w (PD w ) refers to the wth data block PD w The hash value, H w (PD w ) is used to generate data integrity check values. The choice of hash function should ensure the uniqueness and non-tamperability of the data.

[0072] q refers to the total number of check codes, s refers to the index of the check code, MS s Reference and data block PD w The associated sth data integrity check code.

[0073] Refers to the percentage value of the encryption strength impact factor. The impact of MEA is added to the weighted sum of data integrity verification in the form of a percentage. This ensures that the value of MPB affects the verification result within a reasonable range without causing the value to be too large or too small.

[0074] Refers to the overall situation of data integrity, and calculates the sum of the value of the data set after being processed by the hash function and the product of the check value.

[0075] Refers to the degree of loss of data integrity. It is calculated by taking the square root of the sum of the squares of the differences between the value of the data set after being processed by the hash function and the checksum and taking the negative value.

[0076] The wth data block PD w The hash value H w (PD w ) and the encryption strength assessment value MEA are input to the data integrity sub-module, and a data integrity check value MPB is output based on the total number of data blocks p and the total number of check codes q.

[0077] In this embodiment, this submodule ensures that the data in the software development process remains consistent during transmission, storage and processing by calculating the data integrity check value, thereby preventing the data from being tampered with or damaged. Data integrity is the basis of software reliability. The application of MPB helps developers to promptly discover and repair data errors and improve the stability and reliability of the software. The MPB algorithm can be embedded in the software development process to achieve automated data integrity verification, reduce manual intervention, and improve verification efficiency. The MPB value can reflect the integrity status of the data. When the data is tampered with or damaged, the MPB value will change, thereby triggering a warning or error prompt. During the software development process, data errors may cause software crashes or functional abnormalities. Through changes in the MPB value, developers can quickly locate and repair data errors and improve troubleshooting efficiency. Data integrity is one of the important manifestations of software quality. By providing reliable data integrity verification results, users' trust and satisfaction with the software can be enhanced.

[0078] See also Figures 1 to 3 , the processing process of the verification prediction analysis submodule is as follows:

[0079]

[0080] in:

[0081] MMS refers to the comprehensive predictive analysis value. MMS combines the results of encryption strength MEA and data integrity check value MPB to perform predictive analysis of the software development process. MMS helps developers to have a more comprehensive understanding of the security and integrity status of the software development process. This value can be used as a decision support tool to help developers evaluate the effectiveness of current encryption and data integrity measures and predict possible risks and challenges in the future.

[0082] SAA refers to the adjustment weight of MEA, SAB refers to the adjustment weight of MPB, SAC refers to the adjustment coefficient of key prediction parameters, t refers to the number of key prediction parameters, g refers to the index of key prediction parameters, MMC g Refers to MMX g The weight coefficient of MMX g Refers to the g-th key prediction parameter.

[0083] The encryption strength assessment value MEA and the data integrity check value MPB are input into the verification prediction analysis submodule, and the verification prediction analysis submodule outputs the comprehensive prediction analysis value MMS.

[0084] In this embodiment, this submodule combines the encryption strength assessment value MEA and the data integrity check value MPB with key prediction parameters to provide developers with a comprehensive security assessment indicator. Through the calculation results of MMS, developers can predict the security risks that may exist in the software development process and take corresponding preventive measures. The calculation results of MMS can provide data support for developers to formulate security strategies to ensure the security of software in various stages such as development, testing, and deployment. MMS combines the results of encryption strength and data integrity check to provide developers with a comprehensive security assessment indicator, which helps developers to fully understand the security status of the software. By comparing the MMS values ​​at different stages, developers can discover weak links in security and take corresponding improvement measures. In the software development process, the MMS value can be used as one of the important bases for security decision-making. For example, when deciding whether to release a new version of the software, developers can refer to the MMS value to evaluate the security risks of the software.

[0085] It is worth noting that the weight MA of the i-th encryption parameter in the encryption strength submodule is based on the data integrity check value MPB. i The encryption strength assessment value MEA, the data integrity check value MPB and the comprehensive prediction analysis value MMS are iterated in a loop. The specific processing process is as follows:

[0086] First: MA i，k+1 =MA i，k +SSQ×(MMS k -MMS k-1 ).

[0087] Second: Set the iteration termination condition:

[0088] Termination condition 1: The number of iterations is 100.

[0089] Termination condition 2: |MA i，k+1 -MA i，k |<0.001.

[0090] in:

[0091] MA i，k+1 Refers to the weight of the i-th encryption parameter after k+1 iterations, MA i，k Refers to the weight of the i-th encryption parameter after k iterations, SSQ refers to the learning rate, which is used to control the amplitude of weight update, MMS k Refers to the comprehensive prediction analysis value after k iterations, MMS k-1 Refers to the comprehensive prediction analysis value after k-1 iterations.

[0092] In this embodiment: the encryption strength submodule is a multi-parameter encryption strength evaluation algorithm, and its weight MA i Determines the impact of different encryption parameters on the overall encryption strength. By iteratively adjusting these weights, we can make the encryption process more adaptable to the requirements of data integrity. Specifically, when the data integrity check value MPB indicates low data integrity, we can increase the weights of encryption parameters related to data integrity protection, thereby improving the overall encryption strength. Conversely, when the data integrity check value MPB is high, we can appropriately reduce these weights to balance encryption strength and other possible performance requirements.

[0093] This iterative form adjusts the weight MA by iteratively i , the encryption strategy can be flexibly adjusted according to the actual situation and data integrity requirements of the software development process, which helps to ensure that the encryption verification process can not only protect the software development content from being seen by outsiders, but also adapt to different development environments and requirements. In this iterative method, the data integrity check value MPB is used as a quantitative indicator of data integrity, which can reflect the integrity status of the software development content during the encryption process. By iteratively adjusting the weight MA i In response to changes in the data integrity check value MPB, we can enhance the protection of data integrity and reduce the risk of data being tampered with or damaged during the encryption process. The iterative process allows us to optimize encryption performance by adjusting weights without changing the encryption algorithm itself, which helps reduce unnecessary encryption overhead and improve software development efficiency.

[0094] After the iteration, the encryption strength submodule is iThe encryption strength assessment value MEA will more accurately reflect the actual encryption strength of the software development content during the encryption process, which will help developers more accurately evaluate the effectiveness of encryption strategies and make corresponding adjustments. The data integrity check value MPB in the data integrity submodule will act as a feedback signal to affect the weight MA. i Therefore, the value of the data integrity check value MPB after iteration will more directly reflect the impact of the encryption strategy on data integrity, which will help developers better monitor and maintain data integrity. The check prediction analysis submodule will improve the prediction accuracy of the comprehensive prediction analysis value MMS after iteration, making it more able to reflect the overall security and integrity status of the software development content during the encryption process. This will help developers more comprehensively evaluate the effectiveness of encryption strategies and make more informed decisions.

[0095] In the specific implementation process, multiple sub-modules in this method are used to form a software development verification system based on a large model. By combining the total number of encryption parameters n and the strength MK of the i-th encryption parameter i Input to the encryption strength submodule and based on the weight MA of the i-th encryption parameter i Output encryption strength assessment value MEA, according to the calculation result of MEA, select the algorithm with higher encryption strength, so as to more effectively protect the software development content from being stolen by outsiders. By adjusting the encryption algorithm parameters, such as key length, data block size, etc., developers can observe the changes in MEA value, and then optimize the encryption strategy to improve the overall security. The higher the MEA value, the better the protection effect of the encryption algorithm, which helps developers to intuitively understand the performance of the encryption algorithm. By comparing the MEA values ​​of different encryption schemes, developers can select the optimal encryption scheme to improve the security of the software. In the software development process, MEA value can be used as one of the important indicators for security compliance checking to ensure that the software meets the relevant security standards and requirements.

[0096] By taking the wth data block PD w The hash value H w (PD w) and encryption strength assessment value MEA are input to the data integrity sub-module, and the data integrity check value MPB is output based on the total number of data blocks p and the total number of check codes q. This sub-module ensures that the data in the software development process remains consistent during transmission, storage and processing by calculating the data integrity check value to prevent the data from being tampered with or damaged. Data integrity is the basis of software reliability. The MPB value can reflect the integrity status of the data. When the data is tampered with or damaged, the MPB value will change, thereby triggering a warning or error prompt. During the software development process, data errors may cause software crashes or functional abnormalities. Through the change of MPB value, developers can quickly locate and fix data errors and improve troubleshooting efficiency. Data integrity is one of the important manifestations of software quality. By providing reliable data integrity check results, users' trust and satisfaction with the software can be enhanced.

[0097] By inputting the encryption strength assessment value MEA and the data integrity check value MPB into the verification prediction analysis submodule, the verification prediction analysis submodule outputs the comprehensive prediction analysis value MMS. Through the calculation results of MMS, developers can predict the possible security risks in the software development process and take corresponding preventive measures. The calculation results of MMS can provide data support for developers to formulate security strategies to ensure the security of software in various stages such as development, testing, and deployment. By comparing the MMS values ​​at different stages, developers can discover weak links in security and take corresponding improvement measures. In the software development process, the MMS value can be used as one of the important bases for security decision-making. For example, when deciding whether to release a new version of the software, developers can refer to the MMS value to evaluate the security risks of the software.

[0098] The weight MA of the i-th encryption parameter in the encryption strength submodule based on the data integrity check value MPB i By iteratively adjusting these weights, we can make the encryption process more adaptable to the requirements of data integrity. When the data integrity check value MPB indicates that the data integrity is low, we can increase the weights of encryption parameters related to data integrity protection, thereby improving the overall encryption strength. Conversely, when the data integrity check value MPB is high, we can appropriately reduce these weights to balance the encryption strength and other possible performance requirements. This iteration form iteratively adjusts the weight MA i , the encryption strategy can be flexibly adjusted according to the actual situation and data integrity requirements of the software development process, which helps to ensure that the encryption verification process can not only protect the software development content from being seen by outsiders, but also adapt to different development environments and requirements. iIn response to the change of the data integrity check value MPB, we can enhance the protection of data integrity and reduce the risk of data being tampered with or damaged during the encryption process.

[0099] This allows the various sub-modules to cooperate with each other in calculations, and to perform overall cycles and iterations, so that the overall system has the effect of automatic optimization and updating, and thus better adaptability.

[0100] Also, see Figure 1 , Figure 2 and Figure 3 , the strength MK of the i-th encryption parameter in the encryption strength submodule i The encryption parameters i in include key type, encryption algorithm type, encryption mode type, and security feature type.

[0101] The key type refers to the type of parameters in the key, including the key length. The longer the key length, the higher the encryption strength, because cracking a longer key requires more computing resources.

[0102] The encryption algorithm type refers to the different security characteristics of different encryption algorithms. The big data protection algorithm is suitable for the encryption protection of big data, and the sensitive data protection algorithm is used for the encryption protection of sensitive information.

[0103] In this embodiment, the encryption mode type specifically refers to the encryption mode that determines how the encryption algorithm is applied to data, and different modes may provide different security and performance characteristics.

[0104] The security feature type specifically refers to the ability to resist brute force cracking and the ability to resist differential cryptanalysis.

[0105] The jth external factor value MD of the encryption algorithm in the encryption strength submodule j The external factors j in include: the attacker's computing power type, key management type, and encryption algorithm implementation type.

[0106] In this embodiment: the attacker's computing capability type specifically refers to the type and quantity of computing resources used by the attacker, such as CPU, GPU, and FPGA, etc., as well as the dedicated cracking hardware or software tools that the attacker may have.

[0107] The key management type specifically refers to the key storage method, such as hardware security module HSM, key distribution center KDC, key update frequency, effectiveness of key revocation mechanism, etc.

[0108] The implementation type of the encryption algorithm specifically refers to the implementation efficiency of the encryption algorithm on the specific hardware and software platforms, the use of optimized algorithms, such as the fast encryption mode of the AES algorithm, and implementation errors or vulnerabilities, such as buffer overflows and format string vulnerabilities.

[0109] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A software development verification system based on a large model, characterized by: include: Data collection module: The data collection module collects source code, encryption key length, encryption algorithm type, data transmission records and developer operation logs during the software development process; Data processing module: The source code, encryption key length, encryption algorithm type, data transmission record and developer operation log are input into the data processing module. The data processing module cleans, de-duplicates and formats the input data, and outputs the total number of encryption parameters, the strength of the i-th encryption parameter and the hash value of the w-th data block; Verification analysis module: the total number of encryption parameters, the strength of the i-th encryption parameter and the w-th data block PD w The hash value is input into the verification and analysis module, and the verification and analysis module outputs the encryption strength assessment value MEA, the data integrity check value MPB and the comprehensive prediction analysis value MMS; Evaluation and analysis module: The encryption strength assessment value MEA, data integrity check value MPB and comprehensive prediction analysis value MMS are input into the evaluation and analysis module. The evaluation and analysis module analyzes the input values ​​to evaluate the encryption strength and data integrity of software development, and then formulates corresponding encryption strategies and data protection measures based on the analysis and evaluation results. In addition, data is continuously collected during the software development process, and encryption strength and data integrity assessments are regularly performed.

2. The software development verification system based on a large model according to claim 1, characterized in that: The verification analysis module includes an encryption strength submodule, a data integrity submodule and a verification prediction analysis submodule.

3. The software development verification system based on a large model according to claim 2 is characterized in that: The calculation formula of the encryption strength submodule is as follows: in: MEA refers to the encryption strength assessment value, n refers to the total number of encryption parameters, i refers to the index of the encryption parameter, MA i Refers to the weight of the i-th encryption parameter, MK i refers to the strength of the i-th encryption parameter, m refers to the number of external factors and conditions related to encryption strength assessment, j refers to the index of the external factor condition, MD j Refers to the jth external factor value of the encryption algorithm; Refers to the security index of the encryption algorithm itself; Refers to the comprehensive impact of external environmental factors on the security of encryption algorithms; Refers to the negative impact of the interaction between the internal parameters of the computational encryption algorithm and external factors on the encryption strength; log(n+m+1) refers to the encryption strength adjustment factor, which is used to adjust the evaluation value to make it more accurate; The processing process of the encryption strength submodule is as follows: The total number of encryption parameters n and the strength of the i-th encryption parameter MK i Input to the encryption strength submodule and based on the weight MA of the i-th encryption parameter i The encryption strength assessment value MEA is output.

4. The software development verification system based on a large model according to claim 3 is characterized in that: The calculation formula of the data integrity submodule is as follows: in: MPB refers to the data integrity check value, p refers to the total number of data blocks, w refers to the index of the data block, H w (PD w ) refers to the wth data block PD w The hash value of q refers to the total number of check codes, s refers to the index of the check code, MS s Reference and data block PD w The associated sth data integrity check code; Refers to the percentage value of the encryption strength impact factor; Refers to the overall picture of data integrity; Refers to the degree of loss of data integrity; The processing process of the data integrity submodule is as follows: The wth data block PD w The hash value H w (PD w ) and the encryption strength assessment value MEA are input to the data integrity sub-module, and a data integrity check value MPB is output based on the total number of data blocks p and the total number of check codes q.

5. The software development verification system based on a large model according to claim 4 is characterized in that: The calculation formula of the verification prediction analysis submodule is as follows: in: MMS refers to the comprehensive forecast analysis value, SAA refers to the adjustment weight of MEA, SAB refers to the adjustment weight of MPB, SAC refers to the adjustment coefficient of the key forecast parameter, t refers to the number of key forecast parameters, g refers to the index of the key forecast parameter, MMC g Refers to MMX g Weight coefficient of MMX g Refers to the gth key prediction parameter; The processing process of the verification prediction analysis submodule is as follows: The encryption strength assessment value MEA and the data integrity check value MPB are input into the verification prediction analysis submodule, and the verification prediction analysis submodule outputs the comprehensive prediction analysis value MMS.

6. The software development verification system based on a large model according to claim 3 is characterized in that: The strength MK of the i-th encryption parameter in the encryption strength submodule i The encryption parameters i in include: key type, encryption algorithm type, encryption mode type, and security feature type.

7. The software development verification system based on a large model according to claim 6 is characterized in that: The key type refers to the type of parameters in the key, including the key length. The longer the key length, the higher the encryption strength, because more computing resources are required to crack a longer key; The encryption algorithm type refers to the different security features of different encryption algorithms. The big data protection algorithm is suitable for the encryption protection of big data, and the sensitive data protection algorithm is used for the encryption protection of sensitive information.

8. The software development verification system based on a large model according to claim 3 is characterized in that: The jth external factor value MD of the encryption algorithm in the encryption strength submodule j The external factors in j include: The type of computing power of the attacker, the type of key management, and the type of implementation of the encryption algorithm.

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