A trusted supervision and evidence storage method for learning and training activities based on blockchain

Abstract

The present invention discloses a trusted supervision and evidence storage method for learning and training activities based on blockchain, including: participants in learning and training register as blockchain users; obtain face or fingerprint information of the sign-in personnel; identify the above information and obtain the identity of the sign-in personnel; confirm that the above identity belongs to the identity corresponding to the user on the chain; write the sign-in record, activity record, and issue points. The present invention uses blockchain for sign-in of learning and training activities for the first time, supports fingerprint and face recognition sign-in to solve the problem of proxy sign-in, and adopts encryption mechanism to avoid privacy leakage caused by sign-in. The present invention associates learning and training work with blockchain technology, realizes real-time trusted recording of learning and training activities, supports automatic accumulation of activity-related records and points of participants, and puts the above information on the chain as a whole, tamper-proof and traceable, realizing trusted supervision and effective evidence storage of learning and training activities.

Description

Technical Field

[0001] The present invention belongs to the technical field of blockchain, and specifically relates to a trusted supervision and evidence storage method for learning and training activities based on blockchain. Background Art

[0002] Blockchain technology is a technology that combines data blocks into a specific data structure in a chain in chronological order, and has the ability to integrate data sharing and privacy protection. Personnel information is uploaded to the chain, and timestamps are used to record learning and training activities in a chain. Distributed data storage enables collaborative sharing, and smart contracts are deployed on the blockchain to execute complex business logic. The sign-in issue for learning and training activities reflects issues such as the degree of participation and the influence of the activity. Sign-in on the chain makes the activity situation more intuitive, and to a certain extent reduces the phenomenon and risk of privacy leakage during sign-in and sign-in, further improves the effectiveness and authenticity of sign-in for learning and training activities, and helps upgrade and transform the activity management method. Summary of the invention

[0003] The present invention provides a trusted supervision and evidence storage method for learning and training activities based on blockchain, which utilizes the decentralized, tamper-proof, safe and reliable characteristics of blockchain technology to reduce the phenomenon and risk of privacy leakage during proxy sign-in and sign-in, and further improve the effectiveness and authenticity of sign-in for learning and training activities. For the first time, blockchain is used for sign-in, supervision and evidence storage for learning and training activities, and supports fingerprint and face recognition sign-in. It should be pointed out that the present invention is different from ordinary attendance sign-in, but associates sign-in with learning and training activities and supports the accumulation of activity-related records and personnel activity points, and realizes the overall chain, tamper-proof and traceability of the above information.

[0004] The present invention is achieved through the following technical solutions:

[0005] A trusted supervision and evidence storage method for learning and training activities based on blockchain, the steps are as follows:

[0006] Step 1: Extract feature data by scanning the face and fingerprint images of ordinary learners. Under the review of the group administrator, the administrator will upload the data to the personnel information management system, and also upload user information, namely user ID, face hash value, and fingerprint hash value;

[0007] Step 2: The event organizer submits a specific application for the implementation of the learning and training activities in accordance with the prescribed learning and training activity standards and sends it to the learning and training activity management system. After review by the training administrator, it is stored in the activity information chain;

[0008] Step 3: A face recognition and fingerprint recognition terminal is provided at the activity check-in location, and the terminal includes a scanning unit, a feature extraction unit, an information encryption unit, and a communication unit; the scanning unit scans the face or fingerprint information of the check-in person as the first field of the check-in information; the feature extraction unit calculates and extracts feature information from the first field; the information encryption unit encrypts the feature information and calculates its hash value using an asymmetric encryption algorithm;

[0009] Step 4: The server receives the hash ciphertext sent by the sign-in image processing system, forwards it to the personnel information management system, decrypts the hash ciphertext to obtain the facial image and fingerprint image feature values, and verifies the identity of the sign-in person by comparing the feature values ​​in the on-chain standard library;

[0010] Step 5: The learning and training activity management system integrates and compiles the information of the sign-in personnel, and the sign-in personnel who have been verified by the server and the personnel information management system are deemed to have successfully signed in; the system then analyzes the photos taken during the activity and signs out based on the attendance results at the end of the activity; the activity content and participant information are recorded through the smart contract on the activity information chain, and activity points are issued to those who have successfully signed in and signed out;

[0011] Step 6: The server supervises the normal progress of learning and training activities. After the activity is over, the above data and records will be packaged, compressed and uploaded to the chain.

[0012] Preferably, the ordinary learners in step 1 register and authenticate to become legal users on the personnel information chain. Each new user needs to pass the blockchain consensus mechanism and complete the registration after being authenticated by the on-chain supervisory node. User information is stored in a decentralized manner by the blockchain.

[0013] Furthermore, the personnel information chain is a blockchain that stores the identity information of each person, and the chain includes smart contracts, supervisory nodes, and backup nodes; the smart contract provides specific instructions and signs a contract with the users on the chain; the supervisory nodes and backup nodes synchronize data with other blockchain nodes, and the supervisory nodes execute the consensus mechanism to review the joining of new nodes and maintain the security of the information on the chain. The backup nodes store all block information.

[0014] Preferably, the activity organizer in step 2 is equipped with a mobile terminal for checking the progress of the activity in real time; the mobile terminal is controlled by the server, randomly takes photos of the activity process during the activity, and signs out at the end of the activity.

[0015] Preferably, the encryption algorithm in step 3 is:

[0016]

[0017] Wherein, H(N) is the hash value of the message block, C is the compression function, and M is the message divided into blocks of 512 units into M(1), M(2), ..., M(N); the sign-in data processing system sends the above hash value as the query field to the personnel information management system, and retrieves partial or full information of the blockchain user corresponding to the sign-in personnel from the chain.

[0018] Furthermore, the encryption algorithm encrypts the scanned face or fingerprint information of the sign-in personnel and sends it to the next unit in the form of hash ciphertext, wherein the encryption algorithm is the 6 logical functions used in the SHA256 algorithm as follows:

[0019]

[0020]

[0021]

[0022]

[0023]

[0024]

[0025] Among them, ∧ represents bitwise "AND"; Indicates bitwise complement; Sn means bitwise exclusive OR; Sn means circular right shift n bits; Rn means right shift n bits; each function operates on 32-bit bytes and outputs 32-bit bytes.

[0026] Furthermore, the personnel information management system receives the encrypted hash value and executes the smart contract in the blockchain system to retrieve the ordinary user information corresponding to the hash value. The smart contract is responsible for verifying the retrieved user information and checking its consistency with the sign-in personnel information.

[0027] Preferably, in addition to receiving the hash ciphertext sent by the sign-in data processing system, the server in step 4 is also responsible for supervising learning and training activities, and uses mobile terminals to randomly take photos of the activity process to analyze the dynamic changes in attendance and the progress of learning and training activities in real time; the server is responsible for the credible storage of learning and training activities and sign-in data. The above data will be saved by the server and sent to the training administrator for review and approval, and then stored in the activity information chain. The training administrator retrieves the above data from the chain as credible evidence of the activity record.

[0028] Furthermore, the check-in data processing system uses the steps of face image acquisition, face area cropping, face correction, image preprocessing, feature data extraction, and feature data encryption to process the image scanned by the check-in device, and uses a convolutional neural network to extract feature data, mainly including a convolution calculation layer, an activation layer, and a pooling layer.

[0029] Preferably, the activity content in step 5 includes the activity theme, time, location, number of people, and list of participants. The above information is stored in the activity information chain and written after the on-chain supervisory nodes reach a consensus.

[0030] The beneficial effects of the present invention are as follows:

[0031] 1. Use blockchain for signing in for learning and training activities, supporting fingerprint and face recognition signing in. Different from ordinary attendance signing in, signing in is associated with learning and training activities and supports the accumulation of activity-related records and personnel activity points, and realizes the overall chaining, tamper-proof and traceability of the above information;

[0032] 2. Use face recognition and fingerprint technology to sign in, providing reliable protection for the sign-in process. At the same time, the present invention stores sign-in records, personnel identity information and learning and training activity records in a decentralized manner on the blockchain, making these data difficult to be tampered with, ensuring the fairness of sign-in and the security of data storage;

[0033] 3. Confirm the identity of the person who signs in by encrypting the characteristic hash value of the face and fingerprint image. Before and after the process, only the internal modules of the system and external entities will store the data securely, and the data will not be entrusted to any third party;

[0034] 4. Use convolutional neural networks to recognize facial images, with built-in deep learning capabilities. By learning to recognize the facial features of people who sign in at learning and training activities of the same social organization, the efficiency and accuracy of recognition will become higher and higher;

[0035] 5. The data of learning and training activities is backed up and stored by the blockchain system and verified and supervised by the training administrator, ensuring the completeness and security of data storage;

[0036] 6. Learning and training activities are jointly supervised by training administrators and event organizers to ensure consistency in sign-in and sign-out personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a step diagram of a trusted supervision and evidence storage method for learning and training activities based on blockchain provided by an exemplary embodiment;

[0038] Figure 2 It is a system diagram of a blockchain-based trusted supervision and evidence storage method for learning and training activities provided by an exemplary embodiment;

[0039] Figure 3 is a diagram of a face recognition module based on convolutional neural network sign-in provided by an exemplary embodiment;

[0040] Figure 4 It is a block diagram of the functions of a blockchain-based learning and training activity server provided by an exemplary embodiment. DETAILED DESCRIPTION

[0041] The present invention will be further described below in conjunction with the accompanying drawings and specific implementation methods.

[0042] Reference Figure 1 , which shows a step diagram of a trusted supervision and evidence storage method for learning and training activities based on blockchain provided by an exemplary embodiment of the present invention, including ordinary learners registering as blockchain users; obtaining face or fingerprint information of sign-in personnel; identifying the above information and obtaining the identity of the sign-in personnel; confirming that the above identity belongs to the identity corresponding to the user on the chain; writing sign-in records and activity records, and issuing points. The specific steps of the method are as follows:

[0043] Step S101: Ordinary learners scan their faces and extract fingerprints to store user information, namely user ID, face hash value, fingerprint hash value, etc., on the blockchain system, and register and authenticate to become a legal user on the personnel information chain; each new user must pass the blockchain consensus mechanism and be authenticated by the chain supervision node to complete the registration; after successful registration, the user's information is decentralized and stored by the blockchain for comparison with the face or fingerprint information of the sign-in personnel in the next step.

[0044] Step S102: A face recognition and fingerprint recognition terminal is provided at the activity check-in location, and the terminal includes a scanning unit, a feature extraction unit, an information encryption unit, and a communication unit; the scanning unit scans the face or fingerprint information of the check-in person as the first field of the check-in information; the feature extraction unit calculates and extracts feature information from the first field; the information encryption unit encrypts the feature information and calculates its hash value using an asymmetric encryption algorithm, wherein the encryption algorithm is:

[0045]

[0046] Among them, H (N) is the hash value of the message block, C is the compression function, and M is the block size of the message in units of 512. (1) , M (2) ,...,M (N) ; The communication unit sends the above hash value as a query field to the blockchain system, and retrieves partial or all blockchain user information corresponding to the sign-in person from the chain.

[0047] Step S103: The identity verification module receives and processes the hash value in the above steps. The module includes a communication unit, a query unit, and a personnel identity verification unit; the communication unit receives the hash value of the sign-in person sent by the sign-in terminal, and passes it to the query unit after confirmation; the query unit is a user on the blockchain system, and uses the above hash value as a retrieval condition to retrieve the user information corresponding to the condition on the personnel information chain.

[0048] Step S104: The activity recording module integrates and compiles the information of the sign-in personnel, and the sign-in personnel who have passed the verification by the above module are deemed to have signed in successfully;

[0049] Step S105: The activity content includes the activity theme, time, location, number of people, list of participants and points. The above information is stored in the activity information chain. After the chain supervision nodes reach a consensus, the activity content and participant information are recorded;

[0050] Step S106: Points are issued to those who successfully participate in the learning and training activities through smart contracts.

[0051] Reference Figure 2 , which shows a system diagram of a blockchain-based trusted supervision and evidence storage method for learning and training activities provided by an exemplary embodiment of the present invention, including a personnel information management system, a check-in data processing system, a learning and training activity management system, a server, and a learning and training activity organizer equipped with a mobile terminal, etc.

[0052] The personnel information management system is a blockchain that stores the identity information of ordinary learners, including group administrators, personnel information chains, smart contracts, supervisory nodes, and backup nodes; the group administrator is responsible for reviewing whether the registration information of first-time participants is reasonable. Users who pass the review will be registered as new users of the personnel information chain, and the registration information will be stored on the chain. The smart contract provides specific instructions and signs a contract with the user on the chain; the supervisory node and backup node synchronize data with other blockchain nodes. The supervisory node executes the consensus mechanism to review the joining of new nodes and maintain the security of information on the chain. The backup node stores all block information, including registration information, sign-in information, etc.

[0053] The present invention uses the SHA256 asymmetric encryption algorithm to encrypt the scanned face or fingerprint data of the sign-in personnel and send it to the next unit in the form of hash ciphertext.

[0054] The query node in the personnel information chain receives the encrypted hash value and executes the smart contract in the personnel information management system to retrieve the blockchain user information corresponding to the hash value; the personnel identity verification unit is responsible for verifying the retrieved user information and checking its consistency with the signed-in personnel information.

[0055] The sign-in data processing system is responsible for data collection, processing and feature data transmission of face images and fingerprint images of sign-in personnel, and includes a collection device and a device with image processing and data encryption functions.

[0056] Reference Figure 3 , which shows a module diagram of face recognition based on convolutional neural network sign-in provided by an exemplary embodiment of the present invention. The face recognition device needs to be placed at the learning and training activity site; the device includes: a sign-in information collection module, a feature extraction module, an encryption module, a data sending module, and a backup module.

[0057] The check-in information collection module 201 is used to collect facial information of the check-in personnel; the device collects facial data by detecting facial images and locating facial feature points; the facial area of ​​the data is cropped out, and the face correction algorithm of the affine transformation matrix is ​​used to calculate the face area to reduce the impact of low recognition rate caused by side face or half face problems caused by camera posture.

[0058] The face correction algorithm uses an affine transformation matrix to convert the five features of the face image into feature coordinate points centered on the nose and other feature coordinate points according to a specific ratio, estimates the corrected homography matrix, and then performs an affine transformation on the face image to obtain a corrected image; after preprocessing, it is sent to the feature extraction module 202 in the form of an image.

[0059] The feature extraction module 202 is used to extract the facial features of the check-in personnel and compare them with the facial data stored on the chain to determine the identity of the personnel; after receiving the pre-processed facial image, a convolutional neural network is used to extract the features of the facial image, and the convolutional neural network consists of three parts: convolution, activation, and pooling; the convolution part is called the convolution calculation layer, which sums the linear products of the image data and compares the local parts of the image with the local parts of the image of the standard value one by one; the activation layer uses the ReLU activation function to alleviate the problem of gradient disappearance; the pooling layer is used to compress the amount of data and parameters, reduce overfitting, and compress the input facial image.

[0060] The encryption module 203 is used to encrypt, package and send the feature data; the feature data extracted from the facial image of the sign-in person needs to be compared with the facial data stored in the personnel information chain. The whole process uses the SHA256 asymmetric encryption algorithm to ensure data security.

[0061] The data sending module 204 is used for the encryption module 203 to send the hash ciphertext encrypted by the feature data to the personnel blockchain system; the smart contract is deployed on the personnel blockchain system, the data in the standard library is extracted, and the feature data after the decryption of the hash ciphertext is compared with the standard data, and whether the signed-in person is a participant of the learning and training activity is determined through the comparison result.

[0062] The backup module 205 is used to back up the facial image data of the sign-in personnel, the feature data extracted by the feature extraction module 202 and the hash ciphertext of the encryption module 203 .

[0063] Reference Figure 4 , which shows a functional block diagram of a learning and training activity server based on blockchain provided by an exemplary embodiment of the present invention. The server is responsible for information interaction between the personnel information management system, the check-in data processing system, the mobile terminal of the learning and training activity organizer, and the learning and training activity management system. Among them, the modules that each system interfaces with the server are: image processing device, personnel information chain, mobile terminal, and activity information chain.

[0064] Function ①: After the image processing device and the server recognize the features of the facial image, the former uses a specific encryption algorithm on the feature value and sends it to the latter in the form of hash ciphertext. The latter serves as the hub of information interaction and is responsible for the safe and reliable transmission of the hash ciphertext.

[0065] Function ②: server and personnel information link, the former compresses the hash ciphertext and check-in time into a data packet and sends it to the latter for verifying the identity of the check-in personnel.

[0066] Function ③: personnel information chain and server, the former decrypts the received hash ciphertext, obtains the characteristic value and compares it with the data in the standard library, queries the user on the chain, and finds the characteristic value that matches it; if the identity after comparison is consistent, the verification result is sent to the latter to confirm that the sign-in person is a legitimate user on the chain; if it is inconsistent, the sign-in fails.

[0067] Function ④: The server and the mobile terminal, the former can use the latter to supervise the ongoing learning and training activities, and collect activity data by taking on-site photos; the sign-in work after the activity is completed by the two in collaboration.

[0068] Function ⑤: The server and the activity information chain, the former is responsible for sending the activity data collected during the activity, and the latter is responsible for receiving and reviewing, and storing evidence records to confirm that the identities of the sign-in personnel and the sign-out personnel are consistent, and the user points are calculated through the smart contract and distributed together after the activity ends.

[0069] The specific implementation modes of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above implementation modes, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

Claims

1. A blockchain-based trusted supervision and evidence storage method for learning and training activities, characterized in that: Here are the steps: Step 1: Extract feature data by scanning the face and fingerprint images of ordinary learners. Under the review of the group administrator, the administrator will upload the data to the personnel information management system, and also upload user information, namely user ID, face hash value, and fingerprint hash value; Step 2: The event organizer submits a specific application for the implementation of the learning and training activities in accordance with the prescribed learning and training activity standards and sends it to the learning and training activity management system. After review by the training administrator, it is stored in the activity information chain; Step 3: A face recognition and fingerprint recognition terminal is provided at the activity check-in location, and the terminal includes a scanning unit, a feature extraction unit, an information encryption unit, and a communication unit; the scanning unit scans the face or fingerprint information of the check-in person as the first field of the check-in information; the feature extraction unit calculates and extracts feature information from the first field; the information encryption unit encrypts the feature information and calculates its hash value using an asymmetric encryption algorithm; Step 4: The server receives the hash ciphertext sent by the sign-in image processing system, forwards it to the personnel information management system, decrypts the hash ciphertext to obtain the facial image and fingerprint image feature values, and verifies the identity of the sign-in person by comparing the feature values ​​in the on-chain standard library; Step 5: The learning and training activity management system integrates and compiles the information of the sign-in personnel, and the sign-in personnel who have been verified by the server and the personnel information management system are deemed to have successfully signed in; the system then analyzes the photos taken during the activity and signs out based on the attendance results at the end of the activity; the activity content and participant information are recorded through the smart contract on the activity information chain, and activity points are issued to those who have successfully signed in and signed out; Step 6: The server supervises the normal development of learning and training activities. After the activity is over, the above data and records are packaged, compressed and uploaded to the chain; The ordinary learners in step 1 register and authenticate to become legal users on the personnel information chain. Each new user must pass the blockchain consensus mechanism and be authenticated by the chain supervisory node to complete the registration. User information is stored in a decentralized manner on the blockchain. The personnel information chain is a blockchain that stores the identity information of each person. The chain includes smart contracts, supervisory nodes, and backup nodes. The smart contracts provide specific instructions and sign contracts with users on the chain. The supervisory nodes and backup nodes synchronize data with other blockchain nodes. The supervisory nodes execute the consensus mechanism to review the joining of new nodes and maintain the security of information on the chain. The backup nodes store all block information. The activity organizer in step 2 is equipped with a mobile terminal for real-time checking of the progress of the activity; the mobile terminal is controlled by the server, randomly takes photos of the activity process during the activity, and signs out at the end of the activity.

2. According to claim 1, a blockchain-based trusted supervision and evidence storage method for learning and training activities is characterized in that: The encryption algorithm in step 3 is: Wherein, H(N) is the hash value of the message block, C is the compression function, and M is the message divided into blocks of 512 units into M(1), M(2), ..., M(N); the sign-in data processing system sends the above hash value as the query field to the personnel information management system, and retrieves partial or full information of the blockchain user corresponding to the sign-in personnel from the chain.

3. According to claim 2, a blockchain-based trusted supervision and evidence storage method for learning and training activities is characterized in that: The encryption algorithm encrypts the scanned face or fingerprint information of the sign-in personnel and sends it to the next unit in the form of hash ciphertext. The encryption algorithm is the SHA256 algorithm. The six logical functions used are as follows: Among them, ∧ represents bitwise "AND"; Indicates bitwise complement; It means bitwise exclusive OR; Sn means circular right shift n bits; Rn means right shift n bits; each function operates on 32-bit bytes and outputs 32-bit bytes.

4. According to claim 2, a blockchain-based trusted supervision and evidence storage method for learning and training activities is characterized in that: The personnel information management system receives the encrypted hash value and executes the smart contract in the blockchain system to retrieve the ordinary user information corresponding to the hash value. The smart contract is responsible for verifying the retrieved user information and checking its consistency with the sign-in personnel information.

5. According to claim 1, a blockchain-based trusted supervision and evidence storage method for learning and training activities is characterized in that: In addition to receiving the hash ciphertext sent by the sign-in data processing system, the server in step 4 is also responsible for supervising learning and training activities. By using mobile terminals to randomly take photos of the activity process, it analyzes the dynamic changes in attendance and the progress of learning and training activities in real time. The server is responsible for the credible storage of learning and training activities and sign-in data. The above data will be saved by the server and sent to the training administrator for review and approval, and then stored in the activity information chain. The training administrator retrieves the above data from the chain as credible evidence of the activity record.

6. According to claim 5, a blockchain-based trusted supervision and evidence storage method for learning and training activities is characterized in that: The check-in data processing system uses the steps of face image acquisition, face area cropping, face correction, image preprocessing, feature data extraction, and feature data encryption to process the image scanned by the check-in device, and uses a convolutional neural network to extract feature data, mainly including a convolution calculation layer, an activation layer, and a pooling layer.

7. According to claim 1, a blockchain-based trusted supervision and evidence storage method for learning and training activities is characterized in that: The activity content in step 5 includes the activity theme, time, location, number of people, and list of participants. The above information is stored in the activity information chain and written after the on-chain supervisory nodes reach a consensus.

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