Electronic signature secure issuance and processing system and method based on blockchain

Abstract

The present invention discloses a blockchain-based electronic signature security issuance processing system and method, which relates to the technical field of blockchain. The private key is divided into several shared parts by using blockchain technology through a key processing module. This division method ensures that the private key will not be obtained by a single entity, thereby effectively reducing the risk of private key leakage. The signed document and its signature information are stored on the blockchain, and the integrity and reliability of the signature data are further guaranteed by the immutability and transparency of the blockchain. The authorization threshold module constructs a balanced evaluation prediction model through a convolutional neural network, combines the performance factor Nnyz and the security requirement factor Qxyz, and intelligently adjusts the threshold value. This method can effectively balance the security and performance of the system, and further avoids the performance bottleneck caused by an excessively high threshold and the security risks of an excessively low threshold; the electronic signature verification module calculates the first checksum Xyh1 and the second checksum Xyh2 before sending and receiving the signed document.

Description

Technical Field

[0001] The present invention relates to the technical field of blockchain, and specifically to a system and method for securely issuing and processing electronic signatures based on blockchain. Background Art

[0002] In the wide field of information technology, blockchain technology is gradually becoming a cutting-edge technology for data storage and management due to its unique decentralized characteristics and high security. Blockchain has not only achieved success in cryptocurrency transactions, but also demonstrated great potential in areas such as digital identity authentication and smart contracts. In the application of blockchain technology, electronic signatures, as an important means to ensure the authenticity of digital transactions and documents, have received increasing attention. The secure issuance process of electronic signatures covers multiple aspects such as private key management, signature generation and verification.

[0003] Traditional electronic signature systems face several challenges in terms of security and performance. First, the secure storage and management of private keys is a major issue. Key leakage or tampering may cause the signature to be invalid or forged. Second, the computational overhead and performance issues in the signature generation and verification process, especially in the case of high-frequency operations, may reduce the efficiency of the system. Therefore, how to reasonably configure the threshold in the process of secure issuance is an issue that needs further exploration. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a blockchain-based electronic signature secure issuance and processing system and method, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a blockchain-based electronic signature security issuance and processing system, including an electronic signature generation module, a key processing module, an authorization threshold module and an electronic signature verification module;

[0006] The electronic signature generation module is used to allow the signer to sign the document to be signed by using the private key to generate a digital signature, and store the signed document on the blockchain to generate signature information;

[0007] The key processing module is used to use blockchain technology to divide the private key into several groups of shared parts to obtain the total number of shares Fzs, and analyze the performance status of the system under different threshold values ​​Ms in combination with the total number of shares Fzs, and record relevant performance status data information, and construct the performance factor Nnyz in the corresponding situation based on the relevant performance status data information, and monitor the relevant security status data information in the corresponding situation, and construct the security requirement factor Qxyz in the corresponding situation based on the relevant security status data information;

[0008] The authorization threshold module is used to construct a balance assessment prediction model using a convolutional neural network, and to fit the comprehensive assessment coefficient Zpxs in combination with the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case, and to determine the adapted threshold value Ms according to the comprehensive assessment coefficient Zpxs;

[0009] The electronic signature verification module is used to calculate and obtain a number checksum Xyh before sending the signed document and after receiving the signed document. 1 And the second checksum Xyh 2 , and the number one checksum Xyh 1 With the second checksum Xyh 2 Perform a size comparison to determine whether there is any abnormal state in the public key during transmission.

[0010] Preferably, the electronic signature generation module includes a signing unit and a storage unit;

[0011] The signing unit is used to allow the user to log in to the system with a user name and password, and obtain a one-time verification password through a mobile phone text message, and allows the signatory to upload and convert the format of the document to be signed, including but not limited to PDF and Word, and to perform hash processing on the document to be signed by selecting a hash algorithm to generate a unique hash value, and provide the signatory with an algorithm selection drop-down menu, generate a digital signature according to the selected algorithm, and display the signature result;

[0012] The storage unit is used to store the signed document on the blockchain to create signature information, which includes the identity of the signatory, the signing timestamp, the algorithm used, the document hash and the digital signature.

[0013] Preferably, the key processing module includes a segmentation unit, a data monitoring unit and a test analysis unit;

[0014] The splitting unit is used to split the signer's private key into several groups of shared parts using blockchain technology to obtain the total number of shares Fzs, wherein each shared part will be distributed to each participant in turn.

[0015] Preferably, the data monitoring unit is used to monitor the performance status and security requirements of the system in real time under different threshold values ​​Ms, so as to record relevant performance status data information and relevant security status data information in real time, wherein the relevant performance status data information includes the packet loss rate Dbl, bandwidth utilization rate Kdsl, retransmission rate Csl and data transmission rate Scl under various threshold conditions;

[0016] The relevant security status data information includes the total number of shares Fzs and the threshold value Ms under various threshold conditions, the key length Mycd and the sharing length Mzjs.

[0017] Preferably, the test analysis unit comprises a first analysis subunit and a second analysis subunit;

[0018] The first analysis subunit is used to associate the data transmission rate Scl and the bandwidth utilization rate Kdsl according to the relevant performance status data information, and map the corresponding data values ​​in the interval [0, 1], and then obtain the performance factor Nnyz in the corresponding case according to the following formula:

[0019]

[0020] In the formula, Nnyz i Denoted as the performance factor for the i-th threshold case, Dbl i Expressed as the packet loss rate under the i-th threshold, Csl i Expressed as the retransmission rate under the i-th threshold, Kdsl i It is expressed as the bandwidth utilization rate under the i-th threshold condition, Scl i It is represented as the data transmission rate under the i-th threshold condition, C is represented as the first correction constant, α and β are both weight values, and their specific values ​​are adjusted and set by the user.

[0021] Preferably, the second analysis subunit is used to combine the threshold value Ms and the total number of shares Fzs in the corresponding situation to generate the calculation complexity Jfd, and construct the security requirement factor Qxyz in the corresponding situation according to the relevant security status data information, which is specifically obtained in the following manner:

[0022]

[0023] In the formula, Jfd i It is expressed as the computational complexity of the i-th threshold case, Ms i It is expressed as the threshold value under the i-th threshold condition, a 1 and a 2 They are respectively represented as the total number of shares Fzs and the threshold value Ms under the i-th threshold condition i The specific value is set by the user.

[0024]

[0025] In the formula, Mycd i It is expressed as the key length under the i-th threshold condition, Mzjs i It represents the sharing length under the i-th threshold condition, P represents the second correction constant, χ and δ are weight values, and their specific values ​​are adjusted and set by the user.

[0026] Preferably, the authorization threshold module includes a comprehensive analysis unit and a configuration acquisition unit;

[0027] The comprehensive analysis unit is used to construct a balance assessment prediction model using a convolutional neural network, and input the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case into the balance assessment prediction model. After dimensionless processing, the comprehensive assessment coefficient Zpxs in the corresponding case is obtained, which is specifically obtained in the following manner:

[0028]

[0029] Where Zpxs i It is expressed as the comprehensive evaluation coefficient under the i-th threshold condition, F 1 and F 2 All are weight values.

[0030] Preferably, the configuration acquisition unit is used to pre-set a first evaluation threshold W1 and a second evaluation threshold W2, and the first evaluation threshold W1 is greater than the second evaluation threshold W2, and according to the calculation method of obtaining the comprehensive evaluation coefficient Zpxs in the comprehensive analysis unit, several groups of comprehensive evaluation coefficients Zpxs under different situations are obtained, and several groups of comprehensive evaluation coefficients Zpxs are respectively compared and analyzed with the first evaluation threshold W1 and the second evaluation threshold W2 to determine the adapted threshold value Ms, and the specific comparison content is as follows:

[0031] If the comprehensive evaluation coefficient Zpxs in the corresponding case is less than or equal to the second evaluation threshold W2, it means that the threshold value Ms in the current threshold case cannot achieve a balance between the system security requirements and the system performance;

[0032] If the second evaluation threshold W2 < the comprehensive evaluation coefficient Zpxs in the corresponding case ≤ the first evaluation threshold W1, it means that the threshold value Ms in the current threshold case can make the system achieve a balance between security requirements and system performance, and the threshold value Ms in the threshold case will be adapted at this time;

[0033] If the comprehensive evaluation coefficient Zpxs in the corresponding situation is greater than the first evaluation threshold W1, it means that the threshold value Ms in the current threshold situation cannot enable the system to achieve a balance between security requirements and system performance.

[0034] Preferably, the electronic signature verification module includes a calculation unit and a comparison unit;

[0035] The calculation unit is used to calculate a checksum Xyh before sending the public key 1 After receiving the public key, the receiver calculates the second checksum Xyh of the received public key 2 , where the checksum for number one is Xyh 1and checksum No.2Xyh 2 The calculation content is: divide the public key to be calculated for checksum into blocks of fixed size, add each byte of each block together, accumulate the calculation results and perform modulus operation, and the final calculated value is the checksum;

[0036] The comparison unit is used to compare the number one checksum Xyh 1 With the second checksum Xyh 2 Compare and if the values ​​are equal, then there is no abnormal state in the transmission of the public key; if the values ​​are not equal, then there is an abnormal state in the transmission of the public key.

[0037] The method for secure issuance of electronic signatures based on blockchain includes the following steps:

[0038] Step 1: Have the signer sign the document to be signed using the private key in advance to generate a digital signature, and store the signed document on the blockchain to generate signature information;

[0039] Step 2: Use blockchain technology to divide the private key into several groups of different sharing parts to obtain the total number of shares Fzs. Combined with the total number of shares Fzs, analyze the performance status of the system under different threshold values ​​Ms, and record relevant performance status data information. Based on the relevant performance status data information, construct the performance factor Nnyz under the corresponding situation. Meanwhile, monitor the relevant security status data information under the corresponding situation. Based on the relevant security status data information, construct the security requirement factor Qxyz under the corresponding situation.

[0040] Step 3: Use the convolutional neural network to build a balance assessment prediction model, and combine the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case to fit and obtain the comprehensive assessment coefficient Zpxs. According to the comprehensive assessment coefficient Zpxs, determine the adaptive threshold value Ms;

[0041] Step 4: Before sending the signed document and after receiving the signed document, calculate and obtain the first checksum Xyh 1 And the second checksum Xyh 2 , and the number one checksum Xyh 1 With the second checksum Xyh 2 Perform a size comparison to determine whether there is any abnormal state in the public key during transmission.

[0042] The present invention provides a blockchain-based electronic signature security issuance processing system and method, which has the following beneficial effects:

[0043] (1) The private key is divided into several shared parts by using blockchain technology through the key processing module. This division method ensures that the private key will not be obtained by a single entity, thereby effectively reducing the risk of private key leakage. The signed document and its signature information are stored on the blockchain. The integrity and reliability of the signature data are further guaranteed by the immutability and transparency of the blockchain. The authorization threshold module constructs a balanced evaluation prediction model through a convolutional neural network, combines the performance factor Nnyz and the security requirement factor Qxyz, and intelligently adjusts the threshold value. This method can effectively balance the security and performance of the system, further avoiding the performance bottleneck caused by too high a threshold and the security risks of too low a threshold; the electronic signature verification module calculates the number one checksum Xyh before sending and receiving the signed document. 1 And the second checksum Xyh 2 , and make comparisons. This method can detect abnormal states of public keys during transmission in real time, further ensuring that the public keys have not been tampered with or forged, and thus improving the overall security of the system. The key processing module records system performance status data and security status data, and constructs corresponding performance factors and security requirement factors. These data support the system to conduct comprehensive evaluations to optimize threshold settings and further achieve a state of relative balance between performance and security. In short, the system provides an effective way to balance the security and performance of the electronic signature system through comprehensive analysis and precise configuration. This optimization mechanism can ensure the efficient and secure operation of the system under different conditions, and provides system administrators with flexible configuration adjustment tools to meet various practical needs.

[0044] (2) The data monitoring unit records the performance status data at various thresholds in real time to help identify and resolve potential network transmission problems, such as packet loss or bandwidth bottlenecks, thereby improving the overall operating efficiency of the system. The data monitoring unit also records security status data. This information helps ensure the security of key segmentation and management, and facilitates further analysis of the stability and security of the system at different thresholds.

[0045] (3) By comparing the checksum before and after sending the public key, it is possible to quickly detect whether there is any abnormality in the transmission of the public key. If the values ​​of the two checksums are equal, it means that the public key has not been changed during the transmission process, ensuring the reliability and security of the public key. On the contrary, if the checksums do not match, it means that the public key may have been tampered with or damaged. The system can issue a timely warning and take necessary security measures. This mechanism effectively prevents security vulnerabilities caused by tampering with the public key during transmission and protects the system from forgery or tampering attacks. This protection measure enhances the overall security of the system and makes the electronic signature process more reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1This is a block diagram of the electronic signature security issuance and processing system based on blockchain of the present invention;

[0047] Figure 2 This is a flowchart of the blockchain-based electronic signature security issuance processing method of the present invention. DETAILED DESCRIPTION

[0048] 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.

[0049] Example 1

[0050] See also Figure 1 , the present invention provides a blockchain-based electronic signature security issuance processing system, including an electronic signature generation module, a key processing module, an authorization threshold module and an electronic signature verification module;

[0051] The electronic signature generation module is used to allow the signer to sign the document to be signed by using the private key, using a signature algorithm (such as RSA, ECDSA) to generate a digital signature, and store the signed document on the blockchain to generate signature information;

[0052] The key processing module is used to use blockchain technology to divide the private key into several groups of shared parts to obtain the total number of shares Fzs, and analyze the performance status of the system under different threshold values ​​Ms in combination with the total number of shares Fzs, and record relevant performance status data information, and construct the performance factor Nnyz in the corresponding situation based on the relevant performance status data information, and monitor the relevant security status data information in the corresponding situation, and construct the security requirement factor Qxyz in the corresponding situation based on the relevant security status data information;

[0053] The authorization threshold module is used to construct a balance assessment prediction model using a convolutional neural network, and to fit the comprehensive assessment coefficient Zpxs in combination with the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case, and to determine the adapted threshold value Ms according to the comprehensive assessment coefficient Zpxs;

[0054] The electronic signature verification module is used to calculate and obtain a number checksum Xyh before sending the signed document and after receiving the signed document. 1 And the second checksum Xyh 2 , and the number one checksum Xyh 1 With the second checksum Xyh 2Perform a size comparison to determine whether there is any abnormal state in the public key during transmission.

[0055] During the operation of this system, through the electronic signature generation module, the signer uses the private key to sign the document to be signed, and the generated digital signature can effectively verify the authenticity and integrity of the document. At the same time, the signed document is stored on the blockchain, which further ensures the immutability and permanent preservation of the signature information and improves the security of the signature. The key processing module uses blockchain technology to divide the private key into several groups of shared parts, and analyzes the performance status of the system under different threshold values ​​Ms, records the relevant performance status data information, and constructs the performance factor Nnyz. By monitoring the security status data information, the security requirement factor Qxyz is constructed to prepare for the high-security management of the private key to avoid the risk of private key leakage. The authorization threshold module uses a convolutional neural network to construct a balanced evaluation prediction model, and combines the performance factor Nnyz and the security requirement factor Qxyz to calculate the comprehensive evaluation coefficient Zpxs. Through intelligent adjustment, the adaptive threshold value Ms can be accurately determined, thereby optimizing the system performance while ensuring system security, and providing a flexible configuration solution. When sending and receiving signed documents, the electronic signature verification module calculates the number one checksum Xyh 1 And the second checksum Xyh 2 , and size comparison can effectively determine whether there is an abnormal state of the public key during the transmission process. This mechanism can detect the anomaly of the public key in time, ensure that the public key has not been tampered with during the data transmission process, and further improve the reliability of the system. Through the above measures, the system not only improves the security and reliability of the electronic signature system, but also optimizes the performance of the system and solves many deficiencies in the traditional system.

[0056] Example 2

[0057] Please refer to Figure 1 ,Specifically: the electronic signature generation module includes a signing unit and a storage unit;

[0058] The signing unit is used to allow the user to log in to the system with a user name and password, and obtain a one-time verification password through a mobile phone text message. Before signing, the system checks whether the user has the signing authority, and allows the signatory to upload and convert the format of the document to be signed, including but not limited to PDF and Word. It provides a file preview function to ensure that the user has selected the correct file, and hashes the document to be signed by selecting a hash algorithm, such as SHA-256, to generate a unique hash value, and provides an algorithm selection drop-down menu for the signatory to select RSA or ECDSA, etc., to generate a digital signature based on the selected algorithm, and display the signature result;

[0059] The storage unit is used to store the signed document on the blockchain to create signature information, which includes the identity of the signatory, the signing timestamp, the algorithm used, the document hash and the digital signature.

[0060] The key processing module includes a segmentation unit, a data monitoring unit and a test analysis unit;

[0061] The splitting unit is used to split the signer's private key into several groups of shared parts using blockchain technology to obtain the total number of shares Fzs, wherein each shared part will be distributed to each participant in turn.

[0062] There are multiple participants in the system, each of whom receives a share. These participants can be different administrators, departments, or independent third parties of the system. In order to recover the original private key, a sufficient number of shares must be collected from the participants, and this number is determined by the threshold value. For example, if the threshold value is set to 3, at least 3 shares are required to recover the private key.

[0063] In this embodiment, the signing unit in the electronic signature generation module requires the user to log in to the system with a username and password, and to verify the mobile phone SMS verification code at the same time. This multiple identity authentication mechanism further ensures that only authorized users can perform the signing operation, effectively preventing unauthorized access and potential malicious behavior. The system supports uploading and conversion of multiple document formats (such as PDF and Word), and provides a file preview function to ensure that the user has selected the correct file. In addition, by selecting a hash algorithm to hash the document to be signed, a unique hash value is generated, thereby effectively preventing the document content from being tampered with before signing, ensuring the accuracy of the signature and the integrity of the document. The signing unit provides an algorithm selection drop-down menu, allowing the signer to select signature algorithms such as RSA or ECDSA as needed. This flexibility meets the needs of different users for signature algorithms and generates digital signatures based on the selection. The storage unit stores the signed document and related signature information on the blockchain, using the immutability and transparency of blockchain technology to ensure the long-term validity and security of the signature information. The segmentation unit in the key processing module uses blockchain technology to segment the signer's private key into several groups of shared parts, obtain the total number of shares Fzs, and distribute these parts to the participants. This segmentation technology enhances the security of the private key. By splitting the private key into multiple parts, the risk of a single participant being exposed to the complete private key is reduced. The data monitoring unit and the test analysis unit in the key processing module are responsible for recording and analyzing system performance data and security status data. These data are used to optimize the system's performance and security policies to ensure that the system can maintain efficient operating performance while providing sufficient security. In summary, the system not only improves the security of the electronic signature process, but also optimizes system performance and achieves comprehensive protection and efficient management of signing operations through enhanced identity authentication, diverse document processing options, blockchain storage, and private key segmentation technology.

[0064] Example 3

[0065] Please refer to Figure 1 Specifically: the data monitoring unit is used to monitor the performance status and security requirements of the system in real time under different threshold values ​​Ms, so as to record relevant performance status data information and relevant security status data information in real time, wherein the relevant performance status data information includes the packet loss rate Dbl, bandwidth utilization rate Kdsl, retransmission rate Csl and data transmission rate Scl under various threshold conditions;

[0066] The relevant security status data information includes the total number of shares Fzs and the threshold value Ms under various threshold conditions, the key length Mycd and the sharing length Mzjs.

[0067] The test analysis unit includes a first analysis subunit and a second analysis subunit;

[0068] The first analysis subunit is used to associate the data transmission rate Scl and the bandwidth utilization rate Kdsl according to the relevant performance status data information, and map the corresponding data values ​​in the interval [0, 1], and then obtain the performance factor Nnyz in the corresponding case according to the following formula:

[0069]

[0070] In the formula, Nnyz i Denoted as the performance factor for the i-th threshold case, Dbl i Expressed as the packet loss rate under the i-th threshold, Csl i Expressed as the retransmission rate under the i-th threshold, Kdsl i It is expressed as the bandwidth utilization rate under the i-th threshold condition, Scl i It represents the data transmission rate under the i-th threshold condition, C represents the first correction constant, α and β are weight values, and their specific values ​​are adjusted and set by the user, wherein 0<α≤1, 0<β≤1, and α+β=1.

[0071] The packet loss rate Dbl under various threshold conditions mentioned above can use network traffic monitoring tools or network management systems (such as Wireshark, SolarWinds, etc.) to capture network data packets in real time and calculate the packet loss rate. These tools analyze network data packets to determine the number of lost data packets and thus calculate the packet loss rate;

[0072] Bandwidth usage Kdsl is usually measured by network bandwidth monitoring equipment (such as NetFlow Analyzer, PRTG NetworkMonitor, etc.);

[0073] The retransmission rate Csl can be measured by using network performance monitoring tools (such as iPerf, Nagios, etc.) to measure the retransmission of data packets. By detecting the sending and receiving of data packets, the number and frequency of retransmissions can be calculated to obtain the retransmission rate.

[0074] The data transmission rate Scl is usually measured by a data transmission test tool (such as iPerf, Speedtest, etc.). These tools can test the actual data transmission rate of a network connection and provide real-time data transmission rate data.

[0075] In this embodiment, the data monitoring unit can track and record the performance status of the system under different threshold values ​​Ms in real time. This function ensures that the performance data of the system under various conditions is timely acquired and analyzed, thereby providing a comprehensive and accurate view of the system's operating status. Similarly, the data monitoring unit will also monitor and record security status data, including the total number of shares Fzs, the threshold value Ms, the key length Mycd and the sharing length Mzjs. These data help identify potential security issues and provide necessary information support for the security assessment of the system. The first analysis subunit calculates the performance factor Nnyz based on the recorded relevant performance status data. This method associates and maps each performance indicator to an interval, and comprehensively evaluates the system performance in a weighted manner to obtain a comprehensive performance factor. This detailed analysis helps users understand the system performance under different threshold conditions, so that they can make targeted adjustments and optimizations. This flexibility ensures that the system can be optimized according to specific application scenarios and needs, and improves the adaptability and flexibility of the system. By recording and analyzing performance status and security status data information in real time, the system can make instant adjustments during operation to meet different performance and security requirements. This capability ensures that the system can meet security requirements while providing stable performance, enhancing the overall system efficiency and security. The analysis results of the second analysis subunit will provide a scientific basis for further optimization and adjustment of the system. The analysis of the performance factor Nnyz and security requirement factor after comprehensive evaluation helps users identify system bottlenecks and potential risks, so as to formulate more reasonable system configuration and optimization plans. In summary, the system achieves an effective balance between system performance and security through precise real-time monitoring, optimized performance factor calculation, and flexible adjustment capabilities, improves the overall stability and reliability of the system, and provides users with comprehensive performance and security evaluation support.

[0076] Example 4

[0077] Please refer to Figure 1 Specifically: the second analysis subunit is used to combine the threshold value Ms and the total number of shares Fzs in the corresponding situation to generate the calculation complexity Jfd, and construct the security requirement factor Qxyz in the corresponding situation according to the relevant security status data information, which is obtained in the following way:

[0078]

[0079] In the formula, Jfd i It is expressed as the computational complexity of the i-th threshold case, Ms i It is expressed as the threshold value under the i-th threshold condition, a 1 and a 2 They are respectively represented as the total number of shares Fzs and the threshold value Ms under the i-th threshold condition iThe weight value of the weight is set by the user, where 0<a 1 ≤1,0<a 2 ≤1, and a 1 +a 2 =1;

[0080]

[0081] In the formula, Mycd i It is expressed as the key length under the i-th threshold condition, Mzjs i It represents the sharing length under the i-th threshold condition, P represents the second correction constant, χ and δ are weight values, and their specific values ​​are adjusted and set by the user, wherein 0<χ≤1, 0<δ≤1, and χ+δ=1.

[0082] The key length Mycd mentioned above refers to the number of bytes of the key, usually expressed as bytes. For example, the length of an AES key can be 128 bits, 192 bits, or 256 bits. The key length determines the strength of the key and the security of encryption. Longer keys provide higher security, but also increase computing and storage requirements. They can usually be obtained through key management systems or key generation tools (such as OpenSSL, Keycloak, etc.). These systems will record the generated key length and provide relevant key attribute information;

[0083] The share length Mzjs is expressed as the number of bytes in each share, and is usually determined by a key splitting tool (such as Shamir's Secret Sharing implementation tool), which generates the specific length of each share when splitting the key and records it accordingly.

[0084] In this embodiment, the second analysis subunit combines the threshold value Ms and the total number of shares Fzs under different circumstances to generate the computational complexity Jfd. This computational complexity evaluation takes into account the impact of the threshold value and the total number of shares, provides the system with an accurate quantification of the complexity of the processing process, and helps to predict the processing performance and resource requirements of the system under different configurations. According to the computational complexity Jfd and security status data such as the key length Mycd and the share length Mzjs, the second analysis subunit constructs the corresponding security requirement factor Qxyz. This construction method of the security requirement factor ensures that the system can adjust the security configuration according to the actual computational complexity and security parameters, and enhances the in-depth analysis of the security of the system. Combined with the computational complexity and security requirement factors, the system can comprehensively consider the performance and security requirements and provide more comprehensive configuration suggestions. This comprehensive evaluation method helps to achieve a balance between performance and security during system design and operation, and improve the overall reliability and efficiency of the system. Through a detailed analysis of the computational complexity and security requirement factors, the system can provide flexible security configuration options to meet different application requirements and security standards. This flexibility ensures that the system can maintain an efficient and secure operating state in the face of changing security requirements and performance challenges.

[0085] Example 5

[0086] Please refer to Figure 1 ,Specifically: the authorization threshold module includes a comprehensive analysis unit and a configuration acquisition unit;

[0087] The comprehensive analysis unit is used to construct a balance assessment prediction model using a convolutional neural network, and input the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case into the balance assessment prediction model. After dimensionless processing, the comprehensive assessment coefficient Zpxs in the corresponding case is obtained, which is specifically obtained in the following manner:

[0088]

[0089] Where Zpxs i It is expressed as the comprehensive evaluation coefficient under the i-th threshold condition, F 1 and F 2 are weight values, where 0<F 1 ≤1,0<F 2 ≤1, and F 1 +F 2 =1.

[0090] Use convolutional neural networks to build an initial model, and train and test the initial model with relevant performance status data information and relevant safety status data information under different thresholds. Use the trained initial model as a recognition model, obtain feature information in the recognition model, and train and test the recognition model with the obtained feature information. Finally, use the trained recognition model as a prediction model for operation balance assessment.

[0091] The configuration acquisition unit is used to pre-set a first evaluation threshold W1 and a second evaluation threshold W2, and the first evaluation threshold W1 is greater than the second evaluation threshold W2. According to the calculation method of obtaining the comprehensive evaluation coefficient Zpxs in the comprehensive analysis unit, several groups of comprehensive evaluation coefficients Zpxs under different situations are obtained, and the several groups of comprehensive evaluation coefficients Zpxs are respectively compared and analyzed with the first evaluation threshold W1 and the second evaluation threshold W2 to determine the adapted threshold value Ms. The specific comparison content is as follows:

[0092] If the comprehensive evaluation coefficient Zpxs in the corresponding case is less than or equal to the second evaluation threshold W2, it means that the threshold value Ms in the current threshold case cannot achieve a balance between the system security requirements and the system performance;

[0093] If the second evaluation threshold W2 < the comprehensive evaluation coefficient Zpxs in the corresponding case ≤ the first evaluation threshold W1, it means that the threshold value Ms in the current threshold case can make the system achieve a balance between security requirements and system performance, and the threshold value Ms in the threshold case will be adapted at this time;

[0094] If the comprehensive evaluation coefficient Zpxs in the corresponding situation is greater than the first evaluation threshold W1, it means that the threshold value Ms in the current threshold situation cannot enable the system to achieve a balance between security requirements and system performance.

[0095] In this embodiment, the comprehensive analysis unit uses the balance evaluation prediction model constructed by the convolutional neural network CNN, combines the performance factor Nnyz and the safety requirement factor Qxyz, and generates the comprehensive evaluation coefficient Zpxs through dimensionless processing. This method enables the system to comprehensively consider the balance between performance and safety, and optimize the threshold value selection in a scientific data-driven manner. The configuration acquisition unit pre-sets the first evaluation threshold W1 and the second evaluation threshold W2, and the comparison analysis of the comprehensive evaluation coefficient Zpxs, which can accurately determine the adapted threshold value Ms. This threshold-based comparison analysis ensures that the selection of the threshold value can achieve a relative balance between safety requirements and system performance, thereby improving the overall efficiency of the system. The system can flexibly adjust the threshold value according to the comparison results of the comprehensive evaluation coefficient Zpxs with the preset thresholds W1 and W2 to adapt to different safety requirements and performance conditions. For example, when the comprehensive evaluation coefficient Zpxs is between the two thresholds, the system can automatically select the appropriate threshold value, thereby ensuring the stability and reliability of the system under different circumstances. Through the automated evaluation and comparison process, the system reduces the need for manual intervention and improves the accuracy and efficiency of decision-making. Users can quickly obtain relatively suitable threshold values ​​through the comprehensive evaluation coefficients and threshold comparison results automatically generated by the system, thereby simplifying the system configuration and optimization process. In summary, the system provides an efficient threshold value optimization solution through the synergy of the comprehensive analysis unit and the configuration acquisition unit, enabling the system to achieve a precise balance between security and performance, which not only improves the system's operating efficiency, but also enhances the system's security and user experience.

[0096] Example 6

[0097] Please refer to Figure 1 ,Specifically: the electronic signature verification module includes a calculation unit and a comparison unit;

[0098] The calculation unit is used to calculate a checksum Xyh before sending the public key 1 After receiving the public key, the receiver calculates the second checksum Xyh of the received public key 2 , where the checksum for number one is Xyh 1 and checksum No.2Xyh 2 The calculation content is: divide the public key to be calculated into blocks of fixed size, add each byte of each block together, accumulate the calculation results and perform modulo operation, and the final calculated value is the checksum, which is usually a fixed-length value (such as 16 bits, 32 bits, etc.);

[0099] The comparison unit is used to compare the number one checksum Xyh 1 With the second checksum Xyh 2Compare and if the values ​​are equal, then there is no abnormal state in the transmission of the public key; if the values ​​are not equal, then there is an abnormal state in the transmission of the public key.

[0100] In this embodiment, the calculation unit calculates a checksum Xyh before sending the public key. 1 , and calculate the second checksum Xyh after receiving the public key 2 , using block segmentation, byte accumulation and modulus operation to generate a fixed-length checksum. This calculation method ensures that every byte of the public key data is processed correctly during transmission and provides a simple and effective way to detect data integrity and consistency. 1 With the second checksum Xyh 2 By comparing, the system can confirm whether the public key has been accidentally changed or damaged during the transmission process. If the two values ​​are equal, it means that there is no abnormality in the transmission of the public key, ensuring the integrity of the data; if the values ​​are not equal, it indicates that there may be an abnormality in the transmission process, which requires further investigation or retransmission. The comparison function of the comparison unit can effectively prevent the public key from being tampered with during the transmission process. In practical applications, this mechanism is crucial for preventing security threats such as man-in-the-middle attacks MITM, because it can help detect any unauthorized changes or tampering, thereby protecting the overall security of the system. By performing consistency checks at the sending and receiving ends, the system can ensure the reliability of the public key, thereby maintaining the security and accuracy of the electronic signature. This process ensures that the public key data is accurate when the public key is used for signature verification, preventing signature verification failure or data tampering due to public key errors. The method of comparing checksums makes problem detection during the public key transmission process direct and efficient. If a checksum mismatch is found, the system can immediately mark it as an abnormal state, which helps to quickly identify and solve the problem and reduce the complexity and time cost of system maintenance. By implementing the checksum verification mechanism, users can perform electronic signature operations with greater confidence. In short, by calculating and comparing the checksum, an effective data integrity protection measure is provided for the public key transmission process. This verification mechanism not only enhances the security and data reliability of the system, but also simplifies anomaly detection and system maintenance, providing users with a higher level of trust assurance.

[0101] Example 7

[0102] Please refer to Figure 1 and Figure 2 , specifically: A blockchain-based electronic signature secure issuance processing method includes the following steps:

[0103] Step 1: Have the signer sign the document to be signed using the private key in advance to generate a digital signature, and store the signed document on the blockchain to generate signature information;

[0104] Step 2: Use blockchain technology to divide the private key into several groups of different sharing parts to obtain the total number of shares Fzs. Combined with the total number of shares Fzs, analyze the performance status of the system under different threshold values ​​Ms, and record relevant performance status data information. Based on the relevant performance status data information, construct the performance factor Nnyz under the corresponding situation. Meanwhile, monitor the relevant security status data information under the corresponding situation. Based on the relevant security status data information, construct the security requirement factor Qxyz under the corresponding situation.

[0105] Step 3: Use the convolutional neural network to build a balance assessment prediction model, and combine the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case to fit and obtain the comprehensive assessment coefficient Zpxs. According to the comprehensive assessment coefficient Zpxs, determine the adaptive threshold value Ms;

[0106] Step 4: Before sending the signed document and after receiving the signed document, calculate and obtain the first checksum Xyh 1 And the second checksum Xyh 2 , and the number one checksum Xyh 1 With the second checksum Xyh 2 Perform a size comparison to determine whether there is any abnormal state in the public key during transmission.

[0107] 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 blockchain-based electronic signature security issuance and processing system, characterized by: It includes an electronic signature generation module, a key processing module, an authorization threshold module and an electronic signature verification module; The electronic signature generation module is used to allow the signer to sign the document to be signed by using the private key to generate a digital signature, and store the signed document on the blockchain to generate signature information; The key processing module is used to use blockchain technology to divide the private key into several groups of shared parts to obtain the total number of shares Fzs, and analyze the performance status of the system under different threshold values ​​Ms in combination with the total number of shares Fzs, and record relevant performance status data information, and construct the performance factor Nnyz in the corresponding situation based on the relevant performance status data information, and monitor the relevant security status data information in the corresponding situation, and construct the security requirement factor Qxyz in the corresponding situation based on the relevant security status data information; The key processing module includes a segmentation unit, a data monitoring unit and a test analysis unit; The splitting unit is used to split the signer's private key into several groups of shared parts using blockchain technology to obtain a total number of shares Fzs, wherein each shared part allocation will be allocated to each participant in turn; The data monitoring unit is used to monitor the performance status and security requirements of the system in real time under different threshold values ​​Ms, so as to record relevant performance status data information and relevant security status data information in real time, wherein the relevant performance status data information includes the packet loss rate Dbl, bandwidth utilization rate Kdsl, retransmission rate Csl and data transmission rate Scl under various threshold conditions; The relevant security status data information includes the total number of shares Fzs and the threshold value Ms under various threshold conditions, the key length Mycd and the sharing length Mzjs; The test analysis unit includes a first analysis subunit and a second analysis subunit; The first analysis subunit is used to associate the data transmission rate Scl and the bandwidth utilization rate Kdsl according to the relevant performance status data information, and map the corresponding data values ​​in the interval Then, the performance factor Nnyz in the corresponding case is obtained according to the following formula: ； In the formula, Nnyz i Denoted as the performance factor for the i-th threshold case, Dbl i Expressed as the packet loss rate under the i-th threshold, Csl i Expressed as the retransmission rate under the i-th threshold, Kdsl i It is expressed as the bandwidth utilization rate under the i-th threshold condition, Scl i It is represented as the data transmission rate under the i-th threshold condition, C is represented as the first correction constant, and They are all weight values, and their specific values ​​are adjusted and set by the user; The second analysis subunit is used to generate the computational complexity Jfd by combining the threshold value Ms and the total number of shares Fzs in the corresponding situation, and to construct the security requirement factor Qxyz in the corresponding situation according to the relevant security status data information, which is specifically obtained in the following manner: ； In the formula, Jfd i It is expressed as the computational complexity of the i-th threshold case, Ms i It is represented as the threshold value under the i-th threshold condition, a1 and a2 are respectively represented as the total number of shares Fzs and the threshold value Ms under the i-th threshold condition i The specific value is set by the user. ； In the formula, Mycd i It is expressed as the key length under the i-th threshold condition, Mzjs i It is expressed as the sharing length under the i-th threshold condition, P is expressed as the second correction constant, and They are all weight values, and their specific values ​​are adjusted and set by the user; The authorization threshold module is used to construct a balance assessment prediction model using a convolutional neural network, and to fit the comprehensive assessment coefficient Zpxs in combination with the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case, and to determine the adapted threshold value Ms according to the comprehensive assessment coefficient Zpxs; The authorization threshold module includes a comprehensive analysis unit and a configuration acquisition unit; The comprehensive analysis unit is used to construct a balance assessment prediction model using a convolutional neural network, and input the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case into the balance assessment prediction model. After dimensionless processing, the comprehensive assessment coefficient Zpxs in the corresponding case is obtained, which is specifically obtained in the following manner: ； Where Zpxs i It is expressed as the comprehensive evaluation coefficient under the i-th threshold condition, where F1 and F2 are weight values; The electronic signature verification module is used to calculate and obtain the first checksum Xyh1 and the second checksum Xyh2 before sending the signed document and after receiving the signed document, and compare the first checksum Xyh1 with the second checksum Xyh2 to determine whether there is an abnormal state of the public key during the transmission process.

2. The blockchain-based electronic signature security issuance and processing system according to claim 1 is characterized by: The electronic signature generation module includes a signing unit and a storage unit; The signing unit is used to allow the user to log in to the system with a user name and password, and obtain a one-time verification password through a mobile phone text message, and allows the signatory to upload and convert the format of the document to be signed, including but not limited to PDF and Word, and to perform hash processing on the document to be signed by selecting a hash algorithm to generate a unique hash value, and provide the signatory with an algorithm selection drop-down menu, generate a digital signature according to the selected algorithm, and display the signature result; The storage unit is used to store the signed document on the blockchain to create signature information, which includes the identity of the signatory, the signing timestamp, the algorithm used, the document hash and the digital signature.

3. The blockchain-based electronic signature security issuance and processing system according to claim 1 is characterized by: The configuration acquisition unit is used to pre-set a first evaluation threshold W1 and a second evaluation threshold W2, and the first evaluation threshold W1 is greater than the second evaluation threshold W2. According to the calculation method of obtaining the comprehensive evaluation coefficient Zpxs in the comprehensive analysis unit, several groups of comprehensive evaluation coefficients Zpxs under different situations are obtained, and the several groups of comprehensive evaluation coefficients Zpxs are respectively compared and analyzed with the first evaluation threshold W1 and the second evaluation threshold W2 to determine the adapted threshold value Ms. The specific comparison content is as follows: If the comprehensive evaluation coefficient Zpxs in the corresponding case is less than or equal to the second evaluation threshold W2, it means that the threshold value Ms in the current threshold case cannot achieve a balance between the system security requirements and the system performance; If the second evaluation threshold W2 < the comprehensive evaluation coefficient Zpxs in the corresponding case ≤ the first evaluation threshold W1, it means that the threshold value Ms in the current threshold case can make the system achieve a balance between security requirements and system performance, and the threshold value Ms in the threshold case will be adapted at this time; If the comprehensive evaluation coefficient Zpxs in the corresponding situation is greater than the first evaluation threshold W1, it means that the threshold value Ms in the current threshold situation cannot enable the system to achieve a balance between security requirements and system performance.

4. The blockchain-based electronic signature security issuance and processing system according to claim 1 is characterized by: The electronic signature verification module includes a calculation unit and a comparison unit; The calculation unit is used to calculate a first checksum Xyh1 before sending the public key, and after receiving the public key, the receiving end calculates a second checksum Xyh2 of the received public key, wherein the calculation contents of the first checksum Xyh1 and the second checksum Xyh2 are: dividing the public key to be calculated for the checksum into blocks of a fixed size, adding together each byte of each block, accumulating the calculation results and performing a modulo operation, and the value finally calculated is the checksum; The comparison unit is used to compare the first checksum Xyh1 with the second checksum Xyh2. If the values ​​are equal, there is no abnormal state in the public key during the transmission process; if the values ​​are unequal, there is an abnormal state in the public key during the transmission process.

5. A blockchain-based electronic signature secure issuance processing method, used to implement the blockchain-based electronic signature secure issuance processing system as described in any one of claims 1 to 4 above, characterized in that: The following steps are included: Step 1: Have the signer sign the document to be signed using the private key in advance to generate a digital signature, and store the signed document on the blockchain to generate signature information; Step 2: Use blockchain technology to divide the private key into several groups of different sharing parts to obtain the total number of shares Fzs. Combined with the total number of shares Fzs, analyze the performance status of the system under different threshold values ​​Ms, and record relevant performance status data information. Based on the relevant performance status data information, construct the performance factor Nnyz under the corresponding situation. Meanwhile, monitor the relevant security status data information under the corresponding situation. Based on the relevant security status data information, construct the security requirement factor Qxyz under the corresponding situation. Step 3: Use the convolutional neural network to build a balance assessment prediction model, and combine the performance factor Nnyz and the safety requirement factor Qxyz in the corresponding case to fit and obtain the comprehensive assessment coefficient Zpxs. According to the comprehensive assessment coefficient Zpxs, determine the adaptive threshold value Ms; Step 4: Before sending the signed document and after receiving the signed document, calculate and obtain the first checksum Xyh1 and the second checksum Xyh2 respectively, and compare the first checksum Xyh1 with the second checksum Xyh2 to determine whether there is any abnormal state in the public key during the transmission process.

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