Electronic digital signature system and method

Abstract

The invention discloses an electronic digital signature system and method, particularly relates to the technical field of digital signatures, and comprises a digital signature extraction module, a signature verification module and a batch signature generation module. The method specifically comprises the following steps: S1, digital signature extraction; S2, signature verification; and S3, batch signature generation. According to the method, the review efficiency can be improved, the signature safety is ensured, the signature can be taken at any time, encryption and decryption integrated management is realized, the signature can be generated in batches, the accuracy is ensured, and meanwhile, the signature extraction accuracy is improved by adopting an advanced technology.

Description

Technical Field

[0001] The present invention relates to the technical field of digital signatures, and more specifically, to an electronic digital signature system and method. Background Art

[0002] With the continuous development of science and technology, electronic signatures are increasingly used in various fields. In project review and other work, the traditional paper signature method is inefficient and difficult to meet the needs of modern work. In order to improve the review efficiency and realize intelligent review, it is necessary to study and apply electronic digital signature technology; At present, the existing electronic signature technology has some shortcomings in signature extraction, verification and batch generation, such as; 1. The accuracy and precision of signature extraction need to be improved, and it is difficult to accurately extract the graphic features of handwritten signatures; 2. The security and reliability of signature verification need to be strengthened to ensure the authenticity and validity of signatures; 3. In terms of batch signature generation, there is a lack of efficient strategies and methods, which makes it difficult to meet the needs of large-scale review projects.

[0003] In addition, with the advancement of digital construction, higher requirements are placed on the security, stability and ease of use of electronic signature technology. Existing technical standards and specifications need to be continuously improved and updated to adapt to new application scenarios and needs. Therefore, in order to implement the State Grid's requirements on strengthening preliminary design review management, improving the professional capabilities of review units, and promoting intelligent review, the present invention provides an electronic digital signature system and method. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides an electronic digital signature system and method to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an electronic digital signature system, comprising a digital signature extraction module, a signature verification module and a batch signature generation module; The digital signature extraction module uses advanced deep learning algorithms combined with fine graphic recognition technology to accurately extract the graphic features of handwritten signatures in high-resolution images to form high-precision signature graphic data. Through the technical support of Dython or J2EE, it can quickly extract signature data information and convert it into an encrypted message digest to ensure the security and non-tamperability of the signature content. The signature verification module is used to process the extracted signature, convert the signature image into a message digest through an algorithm, and save it to a designated location in the background through the network. At the same time, the expert information related to the signature is associated and saved together to achieve on-demand access. The message digest is encrypted to generate a digital signature, and the encryption and decryption of the digital signature are integrated. After the background receives the parsed ciphertext and completes the parsing, it uses encryption verification for comparison to verify whether the signature is authentic and valid; The batch signature generation module adopts batch digital signature generation technology to form a batch digital signature strategy based on the expert group list and the review project list, locks the signature position according to the proposed review opinions, and generates digital signatures in batches based on the principle of group leader first and group members in order, to complete the electronic batch signatures of the review opinions, wherein the expert group list includes the expert group leader and group members.

[0006] Preferably, the digital signature extraction module includes a data extraction unit, a message digest conversion unit, an encryption processing unit and a feature extraction unit, wherein: A data extraction unit, configured to accurately extract signature data information with the support of Dython or J2EE technology; The message digest conversion unit is connected to the data extraction unit and is used to convert the extracted signature into a message digest; The encryption processing unit is connected to the message digest conversion unit to perform encryption operations on the message digest to ensure the security of the signature content; The feature extraction unit combines advanced deep learning algorithms with fine graphic recognition technology to accurately extract the graphic features of handwritten signatures in high-resolution images and form high-precision signature graphic data, including: A training data collection subunit, used for collecting a large number of high-resolution images containing handwritten signatures as training data; The data preprocessing subunit is connected to the training data collection subunit to preprocess the training data, including image enhancement, denoising and normalization operations; The model selection and training subunit is connected to the data preprocessing subunit, selects a convolutional neural network or a recurrent neural network, and trains the model using the preprocessed training data. During the training process, the model learns the graphic features and patterns of the handwritten signature and is optimized in combination with the fine graphic recognition technology; The signature extraction subunit is connected to the model selection and training subunit. The high-resolution image of the signature to be extracted is input into the trained model. The model automatically extracts the graphic features of the handwritten signature and generates high-precision signature graphic data based on the extracted graphic features.

[0007] Preferably, the signature verification module includes an image processing unit, a storage and association unit, an encryption and decryption management unit and a verification and comparison unit, wherein: An image processing unit, used for receiving the extracted signature image and converting it into a message digest through a specific algorithm; The storage and association unit is connected to the image processing unit to associate and save the message digest and the expert information related to the signature to a designated location in the background so that it can be called at any time; The encryption and decryption management unit is connected with the storage and association unit to encrypt the message digest to generate a digital signature, and realize the integrated management of encryption and decryption of the digital signature to ensure the security and manageability of the signature; The verification and comparison unit is connected to the encryption and decryption management unit. When the background receives the parsed ciphertext and completes the parsing, it uses encryption verification to perform a comparison to verify whether the signature is authentic and valid.

[0008] Preferably, the batch signature generation module includes a policy formulation unit, a signature position locking unit and a signature sequence generation unit, wherein: The strategy formulation unit formulates a reasonable strategy for batch generation of digital signatures based on the expert group list and the review project list; The signature position locking unit is connected to the strategy formulation unit to accurately lock the signature position based on the prepared review opinions; The signature sorting and generating unit is connected to the signature position locking unit, and generates digital signatures in batches according to the principle of group leader first and group members in sequence.

[0009] Preferably, the digital signature extraction module also includes a message digest verification unit and an expert information management unit, wherein the message digest verification unit is connected to the verification and comparison unit to verify the converted message digest to ensure its integrity and accuracy, and the expert information management unit is connected to the storage and association unit to manage the expert information related to the signature, including the entry, update and query of the expert information.

[0010] Preferably, the batch signature generation module also includes a signature style setting unit and an error handling unit, wherein the signature style setting unit is connected to the signature sorting generation unit and is used to set the style of the digital signature so that it complies with specific specifications and requirements, and the error handling unit is connected to the signature sorting generation unit and promptly handles and records errors occurring during the batch signature generation process to ensure the accuracy of signature generation.

[0011] The present invention also provides a method for generating an electronic digital signature in the above system, comprising the following steps: S1. Digital signature extraction: Use the digital signature extraction module to select the graphic extraction system as the data mining tool for electronic signature verification. With the support of Dython, J2EE and other technologies, extract the signature data information. The extracted signature is converted into a message digest and then encrypted to ensure the security of the signature content. Specifically, it includes: S1.1. Data extraction: With specific technical support, the signature data information is accurately extracted through the data extraction unit; S1.2, message digest conversion, using a message digest conversion unit to convert the extracted signature into a message digest; S1.3, encryption operation, the message digest is encrypted by the encryption processing unit to ensure the security of the signature content; S1.4, feature extraction, the feature extraction unit will collect a large number of high-resolution images containing handwritten signatures as training data, and preprocess them, including image enhancement, denoising and normalization operations; then select a convolutional neural network or a recurrent neural network, and use the preprocessed training data to train the model; during the training process, the model learns the graphic features and patterns of the handwritten signature, and optimizes it in combination with fine graphic recognition technology; finally, the high-resolution image of the signature to be extracted is input into the trained model, and the model automatically extracts the graphic features of the handwritten signature, and generates high-precision signature graphic data based on the extracted graphic features.

[0012] S2, signature verification, the extracted signature is processed through the signature verification module, the signature image is converted into a message digest through an algorithm, and is uniformly saved to the designated location of the background through the network, and the expert information related to the signature is also associated and saved, so that it can be used at any time; the message digest is encrypted to generate a digital signature, and the encryption and decryption of the digital signature are integrated. After the background receives the parsed ciphertext and completes the parsing, it uses encryption verification for comparison to verify whether the signature is authentic and valid; specifically includes: S2.1, image processing, using the image processing unit to convert the signature image into a message digest through an algorithm; S2.2, storage and association, the message digest and the expert information related to the signature are associated and saved to the designated location of the background through the storage and association unit; S2.3, encryption and management, using the encryption and decryption management unit to encrypt the message digest to generate a digital signature, and realize the integrated management of encryption and decryption of the digital signature; S2.4, verification and comparison, using the encryption verification of the verification and comparison unit to verify the authenticity and validity of the signature; S3. Batch signature generation: using the batch digital signature generation technology of the batch signature generation module, a batch digital signature generation strategy is formed according to the expert group list and the review project list. The signature position is locked according to the proposed review opinions. The digital signatures are generated in batches according to the principle of group leader first and group members in order, and the electronic batch signatures of the review opinions are completed; specifically, it includes: S3.1, Strategy formulation: The strategy formulation unit formulates a batch generation digital signature strategy based on the expert group list and the review project list; S3.2, Signature position locking, using the signature position locking unit to lock the signature position according to the prepared review opinions; S3.3. Signature sorting generation: The signature sorting generation unit is used to generate digital signatures in batches according to the principle of group leader first and group members in order.

[0013] Preferably, in the digital signature extraction step of S1, it also includes, before data extraction, cleaning and screening the signature data information through a data preprocessing step to remove invalid data; according to actual needs, selecting a suitable encryption algorithm in S1.3 to improve the security of the signature content, wherein the encryption algorithm is the message digest 5 algorithm, the hash algorithm or the SHA-256 algorithm.

[0014] Preferably, in the signature verification step of S2, it also includes verifying the message digest through a message digest verification step after the message digest is converted to ensure its accuracy and completeness; and effectively managing and maintaining the expert information through an expert information management step after the expert information is associated and saved.

[0015] Preferably, the batch signature generation step of S3 also includes setting a suitable digital signature style in accordance with relevant regulations and requirements in a signature style setting step; in the batch signature generation process, errors that occur are promptly handled and recorded through an error handling step to ensure the accuracy of signature generation.

[0016] Technical effects and advantages of the present invention: 1. The present invention adopts batch digital signature verification technology and batch digital signature generation, which greatly reduces the time and workload of expert signatures, realizes the electronic batch signature of review opinions, and significantly improves the efficiency of project review; 2. The present invention combines advanced deep learning algorithms with fine graphic recognition technology to accurately extract the graphic features of handwritten signatures and encrypt the signatures to achieve integrated management of encryption and decryption of digital signatures, ensuring the security and non-tamperability of the signature content, and effectively preventing the signature from being forged or tampered with; 3. The system of the present invention can accurately verify the authenticity and validity of the signature, ensuring the reliability of the review results. At the same time, the associated preservation of electronic batch signatures and related information makes the review process more standardized and traceable, which helps to improve the quality and fairness of the review work. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is the overall system diagram of the present invention.

[0018] Figure 2 It is a system diagram of the digital signature extraction module and signature verification module of the present invention.

[0019] Figure 3 This is a system diagram of the batch signature generation module of the present invention.

[0020] Figure 4 It is a flow chart of the present invention.

[0021] Figure 5 It is a detailed flow chart of step S1 of the present invention.

[0022] Figure 6 It is a detailed flow chart of step S2 of the present invention.

[0023] Figure 7 It is a detailed flow chart of step S3 of the present invention.

[0024] The accompanying drawings are marked as follows: 1. digital signature extraction module; 2. signature verification module; 3. batch signature generation module; 100. data extraction unit; 101. message digest conversion unit; 102. encryption processing unit; 103. feature extraction unit; 1031. training data collection subunit; 1032. data preprocessing subunit; 1033. model selection and training subunit; 1034. signature extraction subunit; 200. image processing unit; 201. storage and association unit; 202. encryption and decryption management unit; 203. verification and comparison unit; 300. policy formulation unit; 301. signature position locking unit; 302. signature sorting generation unit; 104. message digest verification unit; 105. expert information management unit; 303. signature style setting unit; 304. error handling unit. DETAILED DESCRIPTION

[0025] 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.

[0026] As attached Figure 1 As shown, the present invention provides an electronic digital signature system, including a digital signature extraction module 1, a signature verification module 2 and a batch signature generation module 3.

[0027] As attached Figure 1 , 2 As shown, the digital signature extraction module 1 includes a data extraction unit 100, a message digest conversion unit 101, an encryption processing unit 102 and a feature extraction unit 103.

[0028] The data extraction unit 100, with the support of Dython or J2EE technology, accurately extracts the signature data information. Specifically, it uses the relevant functions and interfaces provided by Dython or J2EE to obtain the signature data information from the input data source, and performs preliminary processing and sorting; The message digest conversion unit 101 is connected to the data extraction unit 100, receives the extracted signature, and converts it into a message digest through a specific algorithm, and can compress the signature data into a message digest of a fixed length for subsequent processing and storage; The encryption processing unit 102 is connected to the message digest conversion unit 101 and performs encryption operation on the message digest. The encryption processing unit 102 encrypts the message digest according to a preset encryption algorithm, which may be the message digest 5 algorithm, the hash algorithm or the SHA-256 algorithm, to ensure the security of the signature content and prevent unauthorized access and tampering; The feature extraction unit 103 uses a combination of advanced deep learning algorithms and fine pattern recognition technology to extract the graphic features of the handwritten signature. The specific steps are as follows: Collect a large number of high-resolution images containing handwritten signatures as training data and perform preprocessing on them, including image enhancement, denoising and normalization operations. Image enhancement is used to improve the quality and readability of the image, denoising removes interference factors in the image, and normalization makes the image data have a unified format and range; Select a convolutional neural network or a recurrent neural network and train the model using the preprocessed training data. During the training process, the model learns the graphic features and patterns of handwritten signatures and is optimized with fine graphic recognition technology to improve the accuracy of feature extraction. The high-resolution image of the signature to be extracted is input into the trained model. The model automatically extracts the graphic features of the handwritten signature and generates high-precision signature graphic data based on the extracted graphic features.

[0029] As attached Figure 1-2 As shown, the signature verification module 2 includes an image processing unit 200 , a storage and association unit 201 , an encryption and decryption management unit 202 and a verification and comparison unit 203 .

[0030] The image processing unit 200 is used to receive the extracted signature image and convert it into a message digest through a specific algorithm. The algorithm generates a corresponding message digest based on the pixel information and graphic features of the signature image for subsequent verification and comparison; The storage and association unit 201 is connected to the image processing unit 200, and associates the message digest with the expert information related to the signature and saves it to a designated location in the background, so as to realize the correspondence between the signature information and the expert information, and facilitate quick call and query when needed; The encryption and decryption management unit 202 is connected to the storage and association unit 201, encrypts the message digest to generate a digital signature, and realizes the integrated management of encryption and decryption of the digital signature. The message digest is encrypted by an encryption algorithm to generate a digital signature, and the security and manageability of the digital signature are ensured during the encryption and decryption process. The verification and comparison unit 203 is connected to the encryption and decryption management unit 202. When the background receives the parsed ciphertext and completes the parsing, it uses encryption verification for comparison. By comparing the generated digital signature with the preset standard signature or verification information, it verifies whether the signature is authentic and valid.

[0031] As attached Figure 1 , 3 As shown, the batch signature generation module 3 includes a policy formulation unit 300 , a signature position locking unit 301 and a signature sequence generation unit 302 .

[0032] The strategy formulation unit 300 formulates a reasonable strategy for batch generation of digital signatures based on the expert group list and the review project list, and determines the generation order, rules and related parameters of the signatures in consideration of the composition of the expert group and the requirements of the review project; The signature position locking unit 301 is connected to the policy formulation unit 300, and accurately locks the signature position according to the prepared review opinions, and determines the specific position of each signature in the document according to the format and requirements of the review document; The signature sorting generation unit 302 is connected to the signature position locking unit 301, and generates digital signatures in batches according to the principle of group leader first and group members in sequence. According to the determined signature sequence and position, it generates corresponding digital signatures and ensures the accuracy and consistency of the signatures.

[0033] As attached Figure 4-7 As shown, the present invention also provides a method for generating an electronic digital signature using the above system, comprising the following steps: S1. Digital signature extraction S1.1, data extraction, under the support of specific technology, the signature data information is accurately extracted by the data extraction unit 100. Prior to this, it also includes a data preprocessing step to clean and screen the signature data information and remove invalid data; S1.2, message digest conversion, using the message digest conversion unit 101 to convert the extracted signature into a message digest; S1.3, encryption operation, the message digest is encrypted by the encryption processing unit 102 to ensure the security of the signature content; S1.4, Feature extraction: Collect a large number of high-resolution images containing handwritten signatures as training data and preprocess them, including image enhancement, denoising and normalization operations; Select a convolutional neural network or a recurrent neural network and train the model using the preprocessed training data. During the training process, the model learns the graphic features and patterns of handwritten signatures and is optimized with fine graphic recognition technology. The high-resolution image of the signature to be extracted is input into the trained model. The model automatically extracts the graphic features of the handwritten signature and generates high-precision signature graphic data based on the extracted graphic features.

[0034] S2. Signature Verification S2.1, image processing: using the image processing unit 200 to convert the signature image into a message digest through an algorithm; S2.2, storage and association, the message digest and the expert information related to the signature are associated and saved to a designated location in the background through the storage and association unit 201; S2.3, encryption and management, using the encryption and decryption management unit 202 to encrypt the message digest to generate a digital signature, and realize the integrated management of encryption and decryption of the digital signature; S2.4, verification and comparison, using the encryption verification of the verification and comparison unit 203 to compare and verify the authenticity and validity of the signature. After the message digest is converted, the message digest can also be verified through the message digest verification step to ensure its accuracy and completeness. After the expert information is associated and saved, the expert information is effectively managed and maintained through the expert information management step; S3, batch signature generation S3.1, strategy formulation, the strategy formulation unit 300 formulates a batch generation digital signature strategy based on the expert group list and the review project list; S3.2, signature position locking, the signature position is locked according to the prepared review opinion by the signature position locking unit 301; S3.3. Use the signature sorting generation unit 302 to generate digital signatures in batches according to the principle of group leader first and group members in order. In the signature style setting step, set the appropriate digital signature style according to relevant regulations and requirements. In the batch signature generation process, timely handle and record the errors that occur through the error handling step to ensure the accuracy of signature generation.

[0035] In summary, the main principle of the present invention is to use the deep learning algorithm combined with the graphic recognition technology in the digital signature extraction module 1 to quickly and accurately extract the handwritten signature features and convert them into encrypted message digests, thereby ensuring the security and non-tamperability of the signature; The signature verification module 2 converts the signature image into a message digest and associates it with expert information for integrated management of encryption and decryption to verify the authenticity of the signature; The batch signature generation module 3 formulates a strategy based on the expert group and the list of review projects to achieve electronic batch signatures.

[0036] The present invention improves review efficiency, ensures signature security, realizes on-demand retrieval of signatures, has integrated encryption and decryption management, can generate signatures in batches and ensure accuracy, and at the same time adopts advanced technology to improve the accuracy of signature extraction.

[0037] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An electronic digital signature system, characterized in that: It includes a digital signature extraction module (1), a signature verification module (2) and a batch signature generation module (3); The digital signature extraction module (1) uses an advanced deep learning algorithm combined with fine graphic recognition technology to accurately extract the graphic features of a handwritten signature from a high-resolution image, thereby forming high-precision signature graphic data. With the technical support of Dython or J2EE, it is possible to quickly extract signature data information and convert it into an encrypted message digest, thereby ensuring the security and non-tamperability of the signature content. The signature verification module (2) is used to process the extracted signature, convert the signature image into a message digest through an algorithm, and save it to a designated location in the background through the network. At the same time, the expert information related to the signature is associated and saved together to achieve on-demand access. The message digest is encrypted to generate a digital signature, and the encryption and decryption of the digital signature are integrated. After the background receives the parsed ciphertext and completes the parsing, the encryption verification is used for comparison to verify whether the signature is authentic and valid; The batch signature generation module (3) adopts batch digital signature generation technology, forms a batch digital signature generation strategy based on the expert group list and the review project list, locks the signature position according to the prepared review opinions, and generates digital signatures in batches based on the principle of group leader first and group members in order, thereby completing the electronic batch signature of the review opinions, wherein the expert group list includes the expert group leader and group members.

2. The electronic digital signature system according to claim 1, characterized in that: The digital signature extraction module (1) comprises a data extraction unit (100), a message digest conversion unit (101), an encryption processing unit (102) and a feature extraction unit (103), wherein: A data extraction unit (100) is configured to accurately extract signature data information with the support of Dython or J2EE technology; The message digest conversion unit (101) is connected to the data extraction unit (100) and is used to convert the extracted signature into a message digest; The encryption processing unit (102) is connected to the message digest conversion unit (101) to perform encryption operation on the message digest to ensure the security of the signature content; The feature extraction unit (103) uses an advanced deep learning algorithm combined with fine graphic recognition technology to accurately extract the graphic features of the handwritten signature in a high-resolution image to form high-precision signature graphic data, specifically including: A training data collection subunit (1031), used to collect a large number of high-resolution images containing handwritten signatures as training data; The data preprocessing subunit (1032) is connected to the training data collecting subunit (1031) to preprocess the training data, including image enhancement, denoising and normalization operations; The model selection and training subunit (1033) is connected to the data preprocessing subunit (1032), selects a convolutional neural network or a recurrent neural network, and trains the model using the preprocessed training data. During the training process, the model learns the graphic features and patterns of the handwritten signature and is optimized in combination with the fine graphic recognition technology; The signature extraction subunit (1034) is connected to the model selection and training subunit (1033), and inputs the high-resolution image of the signature to be extracted into the trained model. The model automatically extracts the graphic features of the handwritten signature and generates high-precision signature graphic data based on the extracted graphic features.

3. The electronic digital signature system according to claim 2, characterized in that: The signature verification module (2) comprises an image processing unit (200), a storage and association unit (201), an encryption and decryption management unit (202) and a verification and comparison unit (203), wherein: An image processing unit (200) is used to receive the extracted signature image and convert it into a message digest through a specific algorithm; The storage and association unit (201) is connected to the image processing unit (200) to associate the message digest with the expert information related to the signature and save it to a designated location in the background so that it can be called at any time; The encryption and decryption management unit (202) is connected to the storage and association unit (201), encrypts the message digest to generate a digital signature, and implements integrated management of encryption and decryption of the digital signature to ensure the security and manageability of the signature; The verification and comparison unit (203) is connected to the encryption and decryption management unit (202). When the background receives the parsed ciphertext and completes the parsing, it uses encryption verification to perform a comparison to verify whether the signature is authentic and valid.

4. The electronic digital signature system according to claim 3, characterized in that: The batch signature generation module (3) comprises a policy formulation unit (300), a signature position locking unit (301) and a signature sequence generation unit (302), wherein: The strategy formulation unit (300) formulates a reasonable batch generation digital signature strategy based on the expert group list and the review project list; The signature position locking unit (301) is connected to the strategy formulation unit (300) and accurately locks the signature position according to the prepared review opinions; The signature sorting generation unit (302) is connected to the signature position locking unit (301) and generates digital signatures in batches according to the principle of group leader first and group members in order.

5. The electronic digital signature system according to claim 4, characterized in that: The digital signature extraction module (1) further comprises a message digest verification unit (104) and an expert information management unit (105), wherein the message digest verification unit (104) is connected to the verification and comparison unit (203) and is used to verify the converted message digest to ensure its integrity and accuracy, and the expert information management unit (105) is connected to the storage and association unit (201) and manages the expert information related to the signature, including the entry, update and query of the expert information.

6. The electronic digital signature system according to claim 5, characterized in that: The batch signature generation module (3) further comprises a signature style setting unit (303) and an error handling unit (304), wherein the signature style setting unit (303) is connected to the signature order generation unit (302) and is used to set the style of the digital signature so that it complies with specific specifications and requirements, and the error handling unit (304) is connected to the signature order generation unit (302) and promptly handles and records errors that occur during the batch signature generation process to ensure the accuracy of signature generation.

7. A method for generating an electronic digital signature using the system of claim 6, characterized in that: The following steps are involved: S1. Digital signature extraction: Using the digital signature extraction module (1), the graphic extraction system is selected as the data mining tool for electronic signature verification. With the support of Dython, J2EE and other technologies, the signature data information is extracted. The extracted signature is converted into a message digest and then encrypted to ensure the security of the signature content. Specifically, it includes: S1.1, data extraction, with the support of specific technology, accurately extract the signature data information through the data extraction unit (100); S1.2, message digest conversion, using the message digest conversion unit (101) to convert the extracted signature into a message digest; S1.3, encryption operation, performing encryption operation on the message digest via the encryption processing unit (102) to ensure the security of the signature content; S1.4, feature extraction, the feature extraction unit (103) collects a large number of high-resolution images containing handwritten signatures as training data, and preprocesses them, including image enhancement, denoising and normalization operations; then selects a convolutional neural network or a recurrent neural network, and uses the preprocessed training data to train the model; during the training process, the model learns the graphic features and patterns of the handwritten signature, and optimizes them in combination with fine graphic recognition technology; finally, the high-resolution image of the signature to be extracted is input into the trained model, and the model automatically extracts the graphic features of the handwritten signature, and generates high-precision signature graphic data based on the extracted graphic features; S2, signature verification, the extracted signature is processed by the signature verification module (2), the signature image is converted into a message digest through an algorithm, and is uniformly saved to a designated location in the background through the network, and the expert information related to the signature is also associated and saved to achieve on-demand access; the message digest is encrypted to generate a digital signature, and the encryption and decryption of the digital signature are integrated. After the background receives the parsed ciphertext and completes the parsing, the encryption verification is used for comparison to verify whether the signature is authentic and valid; specifically, it includes: S2.1, image processing, using the image processing unit (200) to convert the signature image into a message digest through an algorithm; S2.2, storage and association, the message digest and the expert information related to the signature are associated and saved to a designated location in the background through the storage and association unit (201); S2.3, encryption and management, using the encryption and decryption management unit (202) to encrypt the message digest to generate a digital signature, and realize the integrated management of encryption and decryption of the digital signature; S2.4, verification and comparison, using the encryption verification of the verification and comparison unit (203) to perform a comparison to verify the authenticity and validity of the signature; S3, batch signature generation, using the batch digital signature generation technology of the batch signature generation module (3), based on the expert group list and the review project list, forming a batch digital signature generation strategy, locking the signature position according to the prepared review opinions, and batch generating digital signatures in the principle of group leader first and group members in order, completing the electronic batch signature of the review opinions; specifically including: S3.1, strategy formulation, the strategy formulation unit (300) formulates a batch generation digital signature strategy based on the expert group list and the review project list; S3.2, signature position locking, the signature position is locked according to the prepared review opinion by means of the signature position locking unit (301); S3.

3. Signature sorting generation: The signature sorting generation unit (302) generates digital signatures in batches according to the principle of group leader first and group members in order.

8. A method according to claim 7, characterized in that: In the digital signature extraction step of S1, it also includes cleaning and screening the signature data information through a data preprocessing step before data extraction to remove invalid data; according to actual needs, a suitable encryption algorithm is selected in S1.3 to improve the security of the signature content, wherein the encryption algorithm is the message digest 5 algorithm, the hash algorithm or the SHA-256 algorithm.

9. A method according to claim 8, characterized in that: The signature verification step of S2 also includes verifying the message digest through a message digest verification step after the message digest is converted to ensure its accuracy and completeness; and effectively managing and maintaining the expert information through an expert information management step after the expert information is associated and saved.

10. A method according to claim 9, characterized in that: The batch signature generation step of S3 also includes setting a suitable digital signature style in accordance with relevant regulations and requirements in the signature style setting step; in the batch signature generation process, errors are promptly handled and recorded through the error handling step to ensure the accuracy of signature generation.

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