Electronic archive sharing utilization method based on multi-block chain

Abstract

The invention discloses a multi-block chain-based electronic archive sharing utilization method, which comprises the following steps of: obtaining an intelligent contract and an access control model, and adding the access control model to the intelligent contract to obtain a primary intelligent contract; designing a management contract, an authority judgment contract and an access control contract, and adding the contracts to the smart contract to form an Internet attribute access control model based on the smart contract; an access object credit evaluation model is constructed based on a PSO-RBF neural network, parameters of the model are updated by using a PSO algorithm, an optimal model is obtained to optimize a permission judgment contract, and an optimized permission judgment contract capable of performing credit calculation is obtained. And forming an optimized Internet attribute access control model based on the intelligent contract with a management contract and an access control contract, and constructing a multi-block chain electronic file sharing and utilization process to realize safe access and sharing of the electronic file. According to the method, fraud and malicious behaviors can be prevented, the security of the archive block chain system is enhanced, and network operation consumption is reduced while different user and service requirements are met.

Description

Technical Field

[0001] The present invention relates to the technical field of file sharing, and in particular to a method for sharing and utilizing electronic files based on multiple blockchains. Background Art

[0002] In recent years, with the progress of society and the development of science and technology, the storage method of archives has also undergone a series of changes. From the initial paper storage to the current electronic archives, it is gradually developing in the direction of informatization. However, electronic archives also have a series of problems:

[0003] Electronic archives are not absolutely safe and are vulnerable to malicious attacks; most electronic archives are centralized, and as the number of archives increases, storage costs also increase; archives in different regions need to be shared synchronously, which is costly and very difficult to achieve when there are many archives; the introduction of blockchain technology to the sharing and utilization of electronic archives has many advantages, such as decentralization, tamper-proofing, and traceability. These characteristics make blockchain have great room for development in archive sharing, but the existing use of blockchain for sharing and utilizing electronic archives has problems such as dynamic access rights, low intelligence level, and high network computing overhead, resulting in the sharing and utilization of electronic archives failing to achieve the expected results. Summary of the invention

[0004] The present invention provides an electronic archive sharing and utilization method based on multiple blockchains to overcome the technical problems of the existing use of blockchains for sharing and utilizing electronic archives, such as low level of dynamic access rights and intelligence, and high network computing overhead.

[0005] A method for sharing and utilizing electronic archives based on multiple blockchains, comprising:

[0006] S1: Obtain a smart contract and an access control model, and add the access control model to the smart contract to obtain a primary smart contract; the access control model is used to provide a user with an access control request function for an electronic archive;

[0007] S2: Design a management contract, a permission judgment contract and an access control contract, and add the three contracts to the primary smart contract to form an Internet attribute access control model based on smart contracts; the management contract is used to call and manage the permission judgment contract and the access contract, the permission judgment contract is used to judge whether the user has the permission to access the electronic archive, and the access contract is used to execute the user's command to access the electronic archive or deny the user's command to access the electronic archive according to the result of the permission judgment contract feedback;

[0008] S3: constructing a credit assessment model for the access object based on the PSO-RBF neural network, and using the PSO algorithm to update the parameters of the credit assessment model for the access object to obtain the best model parameters, and then obtain the best credit assessment model for the access object, and the best credit assessment model for the access object is used to evaluate the credit;

[0009] S4: Optimizing the authority judgment contract using the optimal access object credit evaluation model to obtain an optimized authority judgment contract capable of performing credit calculation, and forming an optimized Internet attribute access control model based on smart contracts with the management contract and the access control contract;

[0010] S5: Use the optimized smart contract-based Internet attribute access control model to build a multi-blockchain electronic archive sharing and utilization process to achieve secure access and sharing of electronic archives.

[0011] Furthermore, a management contract, a permission judgment contract and an access control contract are designed, and the three contracts are added to the primary smart contract to form an Internet attribute access control model based on smart contracts, including:

[0012] S21. Design Management Contract:

[0013] Design the ManageAdd() function to add user permission information for accessing electronic archives;

[0014] Design the ManageUpdate() function to update the user permission information for accessing electronic archives;

[0015] Design the ManageDelete() function to delete the user permission information for accessing electronic files;

[0016] Design the QueryData(hash) function to allow obtaining electronic file data through hash query;

[0017] Add four functions to the primary smart contract to form a management contract;

[0018] S22. Design authority judgment contract:

[0019] Call the access control request part of the access control model in the smart contract as the permission judgment contract:

[0020] The access control request part includes the QueryAccess() function, which is used to query whether there is an access anomaly in the user's permissions; the AddAccessIssue() function, which is used to add an access anomaly event; the DeleteAccessIssue() function, which is used to delete an access anomaly event; the Networks() function, which is used to obtain a new access credibility value for the user's permissions, i.e., the access credit value; the Feedback() function, which is used to feed back the result to the access control contract when the new access credibility value is greater than the set access node credit threshold and update the new access credibility value to the new access node credit threshold of the blockchain node, i.e., the computer security value of the blockchain network;

[0021] S23. Design access control contract:

[0022] Design the AccessControl() function to perform security decisions on the blockchain network, compare the pre-defined blockchain network security attacks with the computer security value fed back in the permission judgment contract, and make a decision to allow or deny access to the electronic archives;

[0023] Design the ACCSetMC() function to call the management contract function and modify the user authority according to the result of the authority judgment contract;

[0024] Design the CAnswer() function to return the result of the permission judgment contract to the system carrying the electronic archive to complete the operation of the controllable resources;

[0025] Design the letePolicy() function to delete existing computer security attacks;

[0026] Design the datePolicy() function to update computer security attacks;

[0027] Design the Policy() function, which is responsible for adding new computer security attacks and including them in the attack list;

[0028] Design the blishToACC() function to send the penalty result to the access control contract;

[0029] Seven functions are added to the primary smart contract to form an access control contract.

[0030] Furthermore, a credit assessment model for an access object is constructed based on a PSO-RBF neural network, and the parameters of the credit access object assessment model are updated using a PSO algorithm to obtain optimal model parameters, thereby obtaining an optimal credit assessment model for an access object. The optimal credit assessment model for an access object is used to assess credit, including:

[0031] S31. Constructing the access object credit assessment model based on PSO-RBF neural network:

[0032] S311: Construct input layer:

[0033] Set the number of nodes in the input layer, expressed as X = (x1, x2, x3, ..., x n ), the node is used to represent the input vector; the input vector is defined by the historical data of the blockchain;

[0034] S312: Construct hidden layer:

[0035] Set the number of nodes in the hidden layer, expressed as B = (b1, b2, ... b 20 );

[0036] The Gaussian kernel function is used as the radial basis function of the hidden layer to perform nonlinear mapping and feature extraction on the input vector, as shown in formula (1):

[0037]

[0038] Where x represents the input vector, c i represents the i-th hidden layer node, σ i Represents the activation function width of the i-th hidden layer neuron;

[0039] S313: Construct output layer:

[0040] Set the number of nodes in the output layer, denoted as Y, representing the trustworthiness of the access object, denoted as Y = γ, γ∈(0,1);

[0041] S314, obtain the relationship between the output layer and the input layer, as shown in formula (2),

[0042]

[0043] Among them, ω0 represents the parameter used to adjust the output offset, ω i represents the weight function between the i-th hidden node and the output node, and x represents the input vector;

[0044] S32, using the PSO algorithm to update the center C and weight value ω of the radial basis function in the access object credit assessment model:

[0045] Assume that the dimension of the space search for food is P, the total number of particles is n, and the position of the i-th particle in the P-dimensional space is represented by x i =(x i1 ,x i2 ,…,x iP ), the speed is (v i1 ,vi2 ,…,v iP ), the velocity and position equations are shown in formulas (3) and (4),

[0046]

[0047]

[0048] in, represents the f-dimensional component of the m-th velocity of particle i; represents the f-dimensional component of the position of particle i at the mth iteration; represents the f-dimensional component of particle i at the optimal position; represents the global optimal position component of all particles in dimension f; y1 and y2 are defined as acceleration coefficient factors, ε represents a random number that follows a uniform distribution and is between [0,1]; ρ represents the inertia weight of particle i, as shown in formula (5),

[0049]

[0050] Among them, ρ max and ρ min represents the maximum and minimum values ​​of inertial mass; h represents the current number of iterations, h max Indicates the maximum number of iterations;

[0051] The speed and position are updated. The speed update formula is shown in formula (6):

[0052] v i (t+1)=ω·v i (t)+b1·r1(p i -x i (t))+b2·r2·(p g -x i (t)) (6)

[0053] Among them, v i (t) is the velocity of the ith particle at time t; ω represents the weight value, b1 and b2 are learning factors, r1 and r2 are random numbers in the interval [0,1], and p i is the individual extreme value of the ith particle, p g is the global extreme value, x i (t) is the position of the ith particle at time t; v i (t) and x i The expression of (t) is shown in formulas (7) and (8),

[0054]

[0055] Where D is the dimension of the solution space;

[0056] The position update formula is shown in formula (9):

[0057] X i (t+1)=x i (t)+v i (t+1) (9)

[0058] Obtain the residual sum of squares between the model predicted output value and the actual output value, as shown in formula (10),

[0059] E=(γ i -o i ) 2 (10)

[0060] Among them, E represents the residual sum of squares, γ i Represents the model's predicted output value, i.e., the continuously updated position, o i Indicates the actual output value, o i As shown in formula (11),

[0061]

[0062] Among them, i Indicates the actual output value, X i (t) represents the optimal position of the i-th particle at time t, C i represents the center value of the i-th particle, and g represents the width of the model network layer;

[0063] When the value of E converges, the PSO algorithm stops iterating the credit assessment model of the access object and saves the ω obtained by the last iterative update speed and the C obtained by the actual output value. i , as the weight value ω and center value C of the radial basis function, the update is completed;

[0064] S33: Input the updated weight value ω and the center value C into the access object credit evaluation model, and use the updated access object credit evaluation model to evaluate the user's credit.

[0065] Further, the input vectors include, but are not limited to, illegal request ratio, unauthorized request ratio, no access resource ratio, abnormal request ratio, prohibited request ratio, and request disallowed ratio.

[0066] Further, S4 uses the optimal access object credit evaluation model to optimize the authority judgment contract to obtain an optimized authority judgment contract capable of performing credit calculation, and forms an optimized Internet attribute access control model based on smart contracts with the management contract and the access control contract, including:

[0067] S41, the weight value ω of the radial basis function updated by the PSO algorithm and the actual output value o corresponding to the center value C i Input into the permission judgment contract as the initial access node credibility threshold;

[0068] S42: Determine whether there is an access control request and whether the access control request is abnormal:

[0069] If there is no access control request, the PSO algorithm is started at regular intervals to update the weight value ω and the center value C of the radial basis function, and the actual output value o corresponding to the weight value ω and the center value C of the radial basis function obtained by the update is i Input into the permission judgment contract as the new access node credibility threshold;

[0070] If the permission judgment contract receives the access control request sent by the management contract, it calls the QueryAccess() function to query whether there is an abnormal access event. If normal, it will feedback to the management contract. If abnormal, it will feedback to the management contract and use the Networks() function to call the best access object credit assessment model to generate a new access credit value.

[0071] If the new access credibility value is less than the initial access node credibility threshold, the command that the access credibility value is less than the initial access node credibility threshold is directly fed back to the access control contract. If the new access credibility value is greater than the set access node credibility threshold, the Feedback() function is used to update the new access credibility value to the new access node credibility threshold and feed back the command that the new access credibility value is greater than the initial access node credibility threshold to the access control contract.

[0072] Furthermore, S5 uses the optimized smart contract-based Internet attribute access control model to build a multi-blockchain electronic archive sharing and utilization process to achieve secure access and sharing of electronic archives, including:

[0073] The multi-blockchain electronic archive sharing and utilization process includes an initialization phase, a device registration phase, a dynamic authority allocation phase, and an execution phase;

[0074] S51, initialization phase:

[0075] The proxy node deploys the management contract, authority judgment contract and access control contract to the blockchain, and enables all proxy nodes to obtain the address through broadcasting;

[0076] S52, device registration stage, the device registration stage is the block node registration stage of the archive blockchain network:

[0077] The manager completes the registration of the block node and generates a pair of keys, which are used to encrypt and verify the transmission of electronic documents in the network;

[0078] The manager adds an access policy for block S1 to access resource R2 in block S2 to the permission judgment contract; the access policy defines the way and scope in which block S1 can access resource R2 in block S2; resource R2 is the electronic file to be accessed;

[0079] S53, Dynamic Permission Allocation Stage:

[0080] The subject S1 who applies for access to the electronic archive initiates an access request to the electronic archive resource R2 of the object S2; the object S2 is the electronic archive carrying system; the subject S1 who applies for access to the electronic archive is the user who applies for access to the electronic archive;

[0081] Subject S1 provides its identity and permission information to prove that it has the authority to access resource R2 of object S2;

[0082] Object S2 verifies the identity and permission information provided by subject S1 to ensure that subject S1 actually has the required permissions;

[0083] If the verification is successful, object S2 will perform access control on the electronic archive to determine whether subject S1 is allowed to access resource R2 of object S2; the determining factors of access control include but are not limited to the authority level of subject S1, the sensitivity of resource R2, access time and access method;

[0084] Object S2 determines the final access control decision by calculating and comparing the decision factors. If subject S1 is authorized to access resource R2, the system will allow it to access the resource. If subject S1 is not authorized to access resource R2, the system will deny its access request.

[0085] The proxy node checks and generates access control results based on the optimized smart contract-based Internet attribute access control model and records them in the blockchain;

[0086] The administrator of the blockchain node obtains the management authority of the electronic file, and after completing the access control of the electronic file, writes the record information of the electronic file access control into the new block, triggers the corresponding event of the smart contract, and feeds back the access permission results to the administrator of the blockchain to complete the sharing and use of the electronic file.

[0087] Beneficial effects: The present invention provides a method for sharing and utilizing electronic archives based on multiple blockchains. By designing management contracts, authority judgment contracts and access control contracts, an Internet attribute access control model based on smart contracts is obtained to meet the dynamic access needs of heterogeneous nodes. An access object credit evaluation model is constructed based on a particle swarm optimization radial basis function (PSO-RBF) neural network, and the authority judgment contract is optimized. The access node credit threshold can be set, and an Internet attribute access control model of a smart contract capable of dynamic threshold adjustment is obtained. Finally, a multi-blockchain electronic archive sharing and utilization workflow is constructed according to the Internet attribute access control model and algorithm based on the smart contract, which helps to prevent fraud and malicious behavior, thereby enhancing the security of the archive blockchain system. By integrating credit evaluation in the smart contract, the dependence on centralized authority is reduced, the purpose of decentralized autonomy is achieved, and the needs of different users and businesses are met while reducing network computing consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0089] Figure 1 This is a method flow chart of the electronic archive sharing and utilization method based on multiple blockchains of the present invention;

[0090] Figure 2 This is a use case diagram of the management contract module of the present invention;

[0091] Figure 3 It is a schematic diagram of the components of the inherent characteristics of electronic archives;

[0092] Figure 4 A schematic diagram of the access control flow;

[0093] Figure 5 It is a schematic diagram of the credit assessment model based on PSO-RBF neural network of the present invention;

[0094] Figure 6 This is a schematic diagram of the interactive workflow between contracts of the present invention;

[0095] Figure 7 This is a schematic diagram of the multi-blockchain electronic archive sharing and utilization control process of the present invention;

[0096] Figure 8 A training error variation curve diagram of the credit assessment model of the present invention;

[0097] Fig. 9 is a sampling error variation curve diagram of the credit assessment model of the present invention;

[0098] Fig.10 It is a time consumption variation diagram under different access times of the present invention;

[0099] Fig.11 It is a response change diagram under the access control request of the present invention;

[0100] Fig.12 This is a processing response time diagram of different methods of the present invention. DETAILED DESCRIPTION

[0101] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0102] This embodiment provides a method for sharing and utilizing electronic archives based on multiple blockchains. Figure 1 As shown, including:

[0103] S1: Obtain a smart contract and an access control model, and add the access control model to the smart contract to obtain a primary smart contract; the access control model is used to provide a user with an access control request function for an electronic archive;

[0104] S2: Design a management contract, a permission judgment contract and an access control contract, and add the three contracts to the primary smart contract to form an Internet attribute access control model based on smart contracts; the management contract is used to call and manage the permission judgment contract and the access contract, the permission judgment contract is used to judge whether the user has the permission to access the electronic archive, and the access contract is used to execute the user's command to access the electronic archive or deny the user's command to access the electronic archive according to the result of the permission judgment contract feedback;

[0105] S3: constructing a credit assessment model for the access object based on the PSO-RBF neural network, and using the PSO algorithm to update the parameters of the credit assessment model for the access object to obtain the best model parameters, and then obtain the best credit assessment model for the access object, and the best credit assessment model for the access object is used to evaluate the credit;

[0106] S4: Optimizing the authority judgment contract using the optimal access object credit evaluation model to obtain an optimized authority judgment contract capable of performing credit calculation, and forming an optimized Internet attribute access control model based on smart contracts with the management contract and the access control contract;

[0107] S5: Use the optimized smart contract-based Internet attribute access control model to build a multi-blockchain electronic archive sharing and utilization process to achieve secure access and sharing of electronic archives.

[0108] Specifically, a smart contract and an access control model are obtained, and the access control model is added to the smart contract to obtain a primary smart contract. The access control model is used to provide a user with an access control request function for electronic archives. The smart contract is an overall framework, and functions need to be designed and added to the smart contract to implement operations on the blockchain. The access control model is added to the smart contract to provide some operations and provide a basis for subsequent model construction; a management contract, a permission judgment contract, and an access control contract are designed, and the three contracts are added to the primary smart contract to form an Internet attribute access control model based on a smart contract. The three contracts are designed to achieve trusted and dynamic permission management of access control to electronic archives; an access object credit evaluation model is constructed based on a PSO-RBF neural network, and the parameters of the access object credit evaluation model are updated using a PSO algorithm to obtain the best model parameters, thereby obtaining the best access object credit evaluation model. The best The access object credit assessment model is used to assess credit. Combining the PSO algorithm to construct the access object credit assessment model can overcome the local optimization trap of the RBF parameter space, reduce the dependence on initial conditions, and has the advantages of fast dynamic adjustment of credit value and high precision. The optimal access object credit assessment model is used to optimize the authority judgment contract to obtain an optimized authority judgment contract that can perform credit calculation, and form an optimized Internet attribute access control model based on smart contracts with the management contract and the access control contract. In this scheme, the authority judgment contract is combined with the credit assessment model, which can automatically adjust the trust threshold range of the archive block node to adapt to the ever-changing business environment and risk conditions. Finally, the optimized Internet attribute access control model based on smart contracts is used to construct a multi-blockchain electronic archive sharing and utilization process to achieve secure access and sharing of electronic archives, prevent fraud and malicious behavior, and enhance the security of the archive blockchain system.

[0109] In a specific embodiment, a smart contract and an access control model are obtained, and the access control model is added to the smart contract to obtain a primary smart contract; the access control model is used to provide a user with an access control request function for an electronic archive:

[0110] Build the big framework of smart contract and input the access control model into the smart contract to get the primary smart contract.

[0111] In smart contracts, different functions can be added, different roles can be defined, and specific operation permissions can be assigned to each role. Smart contracts can use events to record key operations such as permission comparison and abnormal access records. These events can be used by blockchain browsers to monitor and audit the use of permission judgment contracts. Smart contracts also have the ability to pass permission judgment results, which is implemented in Solidity using modifiers and events. Modifiers can be used to check whether the caller has the permission to execute the function, and events can be used to record permission changes or access attempts.

[0112] In the Internet environment, attributes are realized by associating the attributes of each subject, object, operation, and environment with access rights. The ABAC-based access control model is suitable for management of devices and a wide range of data Internet. However, for dynamic access management of heterogeneous devices, ABAC adopts an attribute discovery mechanism and cannot accurately and appropriately classify and assign permissions to receiving devices based on {attributes, permissions}. This will limit normal access and real-time processing of data by heterogeneous devices, and bring challenges to edge scenarios. At the same time, access control strategies need to rely on third-party entities for permission access control on the one hand, and provide sufficient storage and computing service capabilities for access control on the other hand. The credibility and security of third-party entities cannot be guaranteed, and the investment of a large number of devices increases costs and has poor scalability. Therefore, only basic access control functions are provided for subsequent contracts. Building smart contracts with access control models can provide a partial operating basis and provide a framework and implementation platform for subsequent contracts.

[0113] In a specific embodiment, a management contract, a permission judgment contract and an access control contract are designed, and the three contracts are added to the primary smart contract to form an Internet attribute access control model based on a smart contract:

[0114] S21. Design Management Contract:

[0115] Design the ManageAdd() function to add user permission information for accessing electronic archives;

[0116] Design the ManageUpdate() function to update the user permission information for accessing electronic archives;

[0117] Design the ManageDelete() function to delete the user permission information for accessing electronic files;

[0118] Design the QueryData(hash) function to allow obtaining electronic file data through hash query;

[0119] Add four functions to the primary smart contract to form a management contract together with the access control model. User nodes with corresponding permissions on the blockchain can call these functions when sending access control requests;

[0120] The use case diagram of the management contract module is as follows Figure 2 As shown, the contract management personnel manage the information related to the user rights to access the electronic archives, including the addition, modification, deletion and query of the user rights information to access the electronic archives. In the management contract link, each link corresponds to a rights information operation, and the details of the management contract operation can be viewed through the corresponding link. The management contract is used to call and manage the rights judgment contract and the access contract, and control based on the changed access initiator and the corresponding media access control address;

[0121] The management contract includes attributes and permissions. Attributes represent the inherent characteristics of accessing electronic archive information. Intrinsic characteristics such as Figure 3 As shown, including authenticity, reliability, integrity and readability, permissions are digitally represented as various executable operations, including but not limited to reading, writing and managing;

[0122] S22. Design authority judgment contract:

[0123] Call the access control request part of the access control model in the smart contract as the permission judgment contract:

[0124] The access control request part includes the QueryAccess() function, which is used to query whether there is an access anomaly in the user's permissions; the AddAccessIssue() function, which is used to add an access anomaly event; the DeleteAccessIssue() function, which is used to delete an access anomaly event; the Networks() function, which is used to obtain a new access credibility value for the user's permissions, i.e., the access credit value; the Feedback() function, which is used to feed back the result to the access control contract when the new access credibility value is greater than the set access node credit threshold and update the new access credibility value to the new access node credit threshold of the blockchain node, i.e., the computer security value of the blockchain network;

[0125] The authority judgment contract is used to determine the authority of the user to apply for archival resource operations, including comparison of subject authority, comparison of resource authority, and evaluation and recording of access anomalies, so that when an abnormal situation occurs, it can be identified in time and corresponding measures can be taken;

[0126] S23. Design access control contract:

[0127] Design the AccessControl() function to perform security decisions on the blockchain network, compare the pre-defined blockchain network security attacks with the computer security value fed back in the permission judgment contract, and make a decision to allow or deny access to the electronic archives;

[0128] Design the ACCSetMC() function to call the management contract function and modify the user authority according to the result of the authority judgment contract;

[0129] Design the CAnswer() function to return the result of the permission judgment contract to the system carrying the electronic archive to complete the operation of the controllable resources;

[0130] Design the letePolicy() function to delete existing computer security attacks;

[0131] Design the datePolicy() function to update computer security attacks;

[0132] Design the Policy() function, which is responsible for adding new computer security attacks and including them in the attack list;

[0133] Design the blishToACC() function to send the penalty result to the access control contract; add seven functions to the primary smart contract to form the access control contract together with the access control model. The access control process is as follows: Figure 4 As shown, the access control contract is used to achieve the final access control of the electronic archive bearing system and the electronic archive, and transmit the judgment conclusion to the user through the right judgment contract result:

[0134] After the execution module receives the access control trigger event, it first performs an event legitimacy check. If it does not meet the security decision, the request is ignored and the event ends. If it meets the security decision, the management contract is called to send an access control request to the authority judgment contract. The result of calling the management contract modifies the authority of the electronic file, encapsulates the authority judgment contract result into a block, and sends it to the new node with the help of the network module. The legitimacy of the block is further verified, and those with security attack risks will be discarded. Those that meet the requirements are stored in the database and the security attacks are updated or added. After all block data is collected and verified, the execution block process begins.

[0135] In this embodiment, the management contract, the authority judgment contract and the access control contract are constructed, which can optimize the access control model and realize the trusted and dynamic authority management of the access control of the electronic archives.

[0136] In a specific embodiment, a credit evaluation model for an access object is constructed based on a PSO-RBF neural network, and the parameters of the credit access object evaluation model are updated using a PSO algorithm to obtain the best model parameters, thereby obtaining the best credit evaluation model for an access object. The scheme in which the best credit evaluation model for an access object is used to evaluate credit is:

[0137] S31. Constructing the access object credit assessment model based on PSO-RBF neural network:

[0138] S311: Construct input layer:

[0139] Set the number of nodes in the input layer, expressed as X = (x1, x2, x3, ..., x n ), nodes are used to represent input vectors; the six types of input vectors are:

[0140] (1) Illegal request, which means that the request sent by the access object has illegal errors, including illegal permissions, syntax errors, address errors, etc. The illegal request is used as the feature input vector x1 of the input layer;

[0141] (2) Unauthorized request, which means that the access right to the object is not authenticated or there is no preset access right information. Unauthorized request is used as the feature input vector x2 of the input layer;

[0142] (3) Abnormal request, which means that the access object is attacked by security, thus sending a large number of requests to consume system resources, etc. Abnormal request is used as the feature input vector x3 of the input layer;

[0143] (4) Forbidden request, which means that the access object is forbidden by the system, indicating that the credit threshold of the access object is low and it is in an untrustworthy state. The forbidden request is used as the feature input vector x4 of the input layer;

[0144] (5) Request not allowed, which means that the permission requested to access the object exceeds the preset range, and the request not allowed is used as the feature input vector x5 of the input layer;

[0145] (6) Access resource does not exist, which means that the resource that the access object wants to access is not found or does not exist. After sending a large number of such requests, it may cause a DoS attack (Denial of Service, DoS). Access resource does not exist as the feature input vector x6 of the input layer;

[0146] The input vector is divided and defined by blockchain historical data;

[0147] S312: Construct hidden layer:

[0148] Set the number of nodes in the hidden layer, expressed as B = (b1, b2, ... b 20 );

[0149] The Gaussian kernel function is used as the radial basis function of the hidden layer to perform nonlinear mapping and feature extraction on the input vector, as shown in formula (12):

[0150]

[0151] Where x represents the input vector, c i represents the i-th hidden layer node, σ i Represents the activation function width of the i-th hidden layer neuron;

[0152] S313: Construct output layer:

[0153] Set the number of nodes in the output layer, denoted as Y, representing the trustworthiness of the access object, denoted as Y = γ, γ∈(0,1);

[0154] S314, obtain the relationship between the output layer and the input layer, as shown in formula (13),

[0155]

[0156] Among them, ω0 represents the parameter used to adjust the output offset, ω i represents the weight function between the i-th hidden node and the output node, and x represents the input vector;

[0157] S32, using the PSO algorithm to update the center C and weight value ω of the radial basis function in the access object credit assessment model:

[0158] Assume that the dimension of the space search for food is P, the total number of particles is n, and the position of the i-th particle in the P-dimensional space is represented by x i =(x i1 ,x i2 ,…,x iP ), the speed is (v i1 ,v i2 ,…,v iP ), the velocity and position equations are shown in equations (14) and (15),

[0159]

[0160] in, represents the f-dimensional component of the m-th velocity of particle i; represents the f-dimensional component of the position of particle i at the mth iteration; represents the f-dimensional component of particle i at the optimal position; represents the global optimal position component of all particles in dimension f; y1 and y2 are defined as acceleration coefficient factors, ε represents a random number that follows a uniform distribution and is between [0,1]; ρ represents the inertia weight of particle i, as shown in formula (16),

[0161]

[0162] Among them, ρ max and ρ min represents the maximum and minimum values ​​of inertial mass; h represents the current number of iterations, h max Indicates the maximum number of iterations;

[0163] The speed and position are updated. The speed update formula is shown in formula (17):

[0164] v i (t+1)=ω·v i (t)+b1·r1(p i -x i (t))+b2·r2·(p g -x i (t)) (17)

[0165] Among them, v i (t) is the velocity of the ith particle at time t; ω represents the weight value, b1 and b2 are learning factors, r1 and r2 are random numbers in the interval [0,1], and p i is the individual extreme value of the ith particle, p g is the global extreme value, x i (t) is the position of the ith particle at time t; v i (t) and x i The expression of (t) is shown in formulas (18) and (19),

[0166]

[0167]

[0168] Where D is the dimension of the solution space;

[0169] The position update formula is shown in formula (20):

[0170] X i (t+1)=x i (t)+v i (t+1) (20)

[0171] Obtain the residual sum of squares between the model predicted output value and the actual output value, as shown in formula (21),

[0172] E=(γi -o i ) 2 (twenty one)

[0173] Among them, E represents the residual sum of squares, γ i Represents the model's predicted output value, i.e., the continuously updated position, o i Indicates the actual output value, o i As shown in formula (22),

[0174]

[0175] Among them, i Indicates the actual output value, X i (t) represents the optimal position of the i-th particle at time t, C i represents the center value of the i-th particle, and g represents the width of the model network layer;

[0176] When the value of E converges, the PSO algorithm stops iterating the credit assessment model of the access object and saves the ω obtained by the last iterative update speed and the C obtained by the actual output value. i , as the weight value ω and center value C of the radial basis function, the update is completed;

[0177] S33, input the updated weight value ω and the center value C into the access object credit evaluation model, and use the updated access object credit evaluation model to evaluate the user's credit. The constructed access object credit evaluation model is as follows: Figure 5 shown.

[0178] This scheme combines the PSO algorithm to build an access object credit assessment model, which can overcome the local optimization trap of the RBF parameter space, reduce the dependence on initial conditions, and has the advantages of fast dynamic adjustment of credit value and high accuracy.

[0179] In a specific embodiment, the permission judgment contract is optimized using the optimal access object credit evaluation model to obtain an optimized permission judgment contract capable of performing credit calculation, and the solution for forming an optimized Internet attribute access control model based on smart contracts with the management contract and the access control contract is:

[0180] S41, the weight value ω of the radial basis function updated by the PSO algorithm and the actual output value o corresponding to the center value C i Input into the permission judgment contract as the initial access node credibility threshold;

[0181] S42: Determine whether there is an access control request and whether the access control request is abnormal:

[0182] If there is no access control request, the PSO algorithm is started at regular intervals to update the weight value ω and the center value C of the radial basis function, and the actual output value o corresponding to the weight value ω and the center value C of the radial basis function obtained by the update is i Input into the permission judgment contract as the new access node credibility threshold;

[0183] If the permission judgment contract receives the access control request sent by the management contract, it calls the QueryAccess() function to query whether there is an abnormal access event. If normal, it will feedback to the management contract. If abnormal, it will feedback to the management contract and use the Networks() function to call the best access object credit assessment model to generate a new access credit value.

[0184] If the new access credibility value is less than the initial access node credibility threshold, the command that the access credibility value is less than the initial access node credibility threshold is directly fed back to the access control contract. If the new access credibility value is greater than the set access node credibility threshold, the Feedback() function is used to update the new access credibility value to the new access node credibility threshold and feed back the command that the new access credibility value is greater than the initial access node credibility threshold to the access control contract.

[0185] The interactive workflow between contracts is as follows Figure 6 As shown, the management contract sends a subject permission access control request to the permission judgment contract. After the permission judgment contract obtains the request, it queries the access control contract to see if there is any access exception assessment and record. If it is normal, it will be fed back to the management contract resource permission access control policy. If it is abnormal, the permission judgment contract sends a request to obtain the credit value to the access control contract. The access control contract generates an access credit threshold by calling the access object credit assessment model and feeds it back to the permission judgment contract, and updates the access history record of the access object. The permission judgment contract feeds back the abnormal result to the management contract.

[0186] In this solution, the permission judgment contract is combined with the access object credit assessment model, which can automatically adjust the trust threshold range of the archive block node to adapt to the changing business environment and risk conditions. The model can also provide real-time feedback so that administrators can adjust strategies based on the feedback results and optimize the access control effect. For example, when the model detects that the trust threshold of the archive block node is low, the administrator can take corresponding measures, such as strengthening the security protection of the block, limiting the access rights of some sensitive operations, etc., to improve the security performance of the archive blockchain system.

[0187] In a specific embodiment, the optimized smart contract-based Internet attribute access control model is used to construct a multi-blockchain electronic archive sharing and utilization process, and the solution for achieving secure access and sharing of electronic archives is:

[0188] The multi-blockchain electronic archive sharing and utilization process includes the initialization phase, the device registration phase, the dynamic authority allocation phase and the execution phase; the overall process is as follows Figure 7 As shown;

[0189] S51, initialization phase:

[0190] The proxy node deploys the management contract, authority judgment contract and access control contract to the blockchain, and enables all proxy nodes to obtain the address through broadcasting;

[0191] S52, device registration stage, the device registration stage is the block node registration stage of the archive blockchain network:

[0192] The manager completes the registration of the block node and generates a pair of keys, which are used to encrypt and verify the transmission of electronic documents in the network;

[0193] The manager adds an access policy for block S1 to access resource R2 in block S2 to the permission judgment contract; the access policy defines the way and scope in which block S1 can access resource R2 in block S2; resource R2 is the electronic file to be accessed;

[0194] S53, Dynamic Permission Allocation Stage:

[0195] The subject S1 who applies for access to the electronic archive initiates an access request to the electronic archive resource R2 of the object S2; the object S2 is the electronic archive carrying system; the subject S1 who applies for access to the electronic archive is the user who applies for access to the electronic archive;

[0196] Subject S1 provides its identity and permission information to prove that it has the authority to access resource R2 of object S2;

[0197] Object S2 verifies the identity and permission information provided by subject S1 to ensure that subject S1 actually has the required permissions;

[0198] If the verification is successful, object S2 will perform access control on the electronic archive to determine whether subject S1 is allowed to access resource R2 of object S2; the determining factors of access control include but are not limited to the authority level of subject S1, the sensitivity of resource R2, access time and access method;

[0199] Object S2 determines the final access control decision by calculating and comparing the decision factors. If subject S1 is authorized to access resource R2, the system will allow it to access the resource. If subject S1 is not authorized to access resource R2, the system will deny its access request.

[0200] S54, Execution phase:

[0201] The proxy node checks and generates access control results based on the optimized smart contract-based Internet attribute access control model and records them in the blockchain;

[0202] The administrator of the blockchain node obtains the management authority of the electronic file, and after completing the access control of the electronic file, writes the record information of the electronic file access control into the new block, triggers the corresponding event of the smart contract, and feeds back the access permission results to the administrator of the blockchain to complete the sharing and use of the electronic file.

[0203] 1. Training and testing the access object credit assessment model in the present invention:

[0204] 500 sample data are selected for credit assessment. First, the data is initialized and amplified 100 times as the input of the neural network. Then 400 node samples are selected as training data and trained for 200 rounds. The remaining 100 node sample data are used for testing. The training results are shown in Figure 2. Figure 8-Figure 9 As shown,

[0205] Figure 8 It is a training error variation curve diagram, in which the horizontal axis represents the training rounds, the vertical axis represents the error value, and the blue line represents the error curve. It can be seen from the figure that the error value gradually decreases with the increase of the training rounds, indicating that the error value of the present invention is low and the accuracy is high;

[0206] Fig. 9 The sampling error variation curve is shown in FIG. 1 , where the horizontal axis represents the number of samples, the vertical axis represents the credit value, the blue line represents the actual value, and the yellow line represents the estimated value. It can be seen from the figure that the actual value using this model is very close to the estimated value, which shows that the credit assessment model for the visit object of the present invention has excellent convergence and high reliability, and has significant advantages in both learning efficiency and accuracy.

[0207] 2. Performance test of the present invention:

[0208] Test results such as Figure 10-12 As shown,

[0209] Fig.10 The figure shows the time consumed by different subjects for 500 consecutive accesses to different data, and presents the average time for every 10 accesses. The horizontal axis represents the amount of data queried, the vertical axis represents the access time, and each point represents the average access time. It can be seen from the figure that as the number of accesses increases, the time of each access shows a linear growth trend, and the average time of the 500th access is about 1.3 seconds. Since each access record is stored in the blockchain, the amount of query data gradually increases, and the access time increases linearly in direct proportion to the amount of query data;

[0210] When testing the response time of the access control request of the access object credit assessment model, the request was sent at a rate of 0 to 10,000 nodes per second. The response time after calling the PSO-RBF algorithm and without calling the PSO-RBF algorithm was compared. Fig.11 As shown in the figure, the horizontal axis represents the number of request nodes, the vertical axis represents the response time, the blue line represents calling the PSO-RBF algorithm to respond, and the yellow line represents not calling the algorithm to respond;

[0211] Due to the large amount of calculation, the PSO-RBF algorithm needs to be called, which will cause delays, and when there are 10,000 request nodes, the response time will increase by about 5 seconds. By simulating the concurrent requests of multi-threaded clients, the ManageAdd() function of the adding function, the QueryData() function of the query function, and the PublishToACC() function of the sending function are tested under different concurrent requests. The processing time of the working difficulty is 0, 1, and 2, such as Fig.12 As shown in the figure, the horizontal axis is the test function, and the vertical axis is the processing time. It can be seen from the figure that in the case of asynchronous requests, there is almost no delay in adding and sending contracts, which shows that edge nodes show obvious superiority in the Internet environment, indicating that the method of the present invention can save time and reduce network computing.

[0212] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for sharing and utilizing electronic archives based on multiple blockchains, characterized in that: include: S1: Obtain a smart contract and an access control model, and add the access control model to the smart contract to obtain a primary smart contract; the access control model is used to provide a user with an access control request function for an electronic archive; S2: Design a management contract, a permission judgment contract and an access control contract, and add the three contracts to the primary smart contract to form an Internet attribute access control model based on smart contracts; the management contract is used to call and manage the permission judgment contract and the access contract, the permission judgment contract is used to judge whether the user has the permission to access the electronic archive, and the access contract is used to execute the user's command to access the electronic archive or deny the user's command to access the electronic archive according to the result of the permission judgment contract feedback; S3: constructing a credit assessment model for the access object based on the PSO-RBF neural network, and using the PSO algorithm to update the parameters of the credit assessment model for the access object to obtain the best model parameters, and then obtain the best credit assessment model for the access object, and the best credit assessment model for the access object is used to evaluate the credit; S4: Optimizing the authority judgment contract using the optimal access object credit evaluation model to obtain an optimized authority judgment contract capable of performing credit calculation, and forming an optimized Internet attribute access control model based on smart contracts with the management contract and the access control contract; S5: Use the optimized smart contract-based Internet attribute access control model to build a multi-blockchain electronic archive sharing and utilization process to achieve secure access and sharing of electronic archives.

2. The electronic archive sharing and utilization method based on multiple blockchains according to claim 1 is characterized in that: S2 designs a management contract, a permission judgment contract, and an access control contract, and adds the three contracts to the primary smart contract to form an Internet attribute access control model based on smart contracts, including: S21. Design Management Contract: Design the ManageAdd() function to add user permission information for accessing electronic archives; Design the ManageUpdate() function to update the user permission information for accessing electronic archives; Design the ManageDelete() function to delete the user permission information for accessing electronic files; Design the QueryData(hash) function to allow obtaining electronic file data through hash query; Add four functions to the primary smart contract to form a management contract; S22. Design authority judgment contract: Call the access control request part of the access control model in the smart contract as the permission judgment contract: The access control request part includes the QueryAccess() function, which is used to query whether there is an access anomaly in the user's permissions; the AddAccessIssue() function, which is used to add an access anomaly event; the DeleteAccessIssue() function, which is used to delete an access anomaly event; the Networks() function, which is used to obtain a new access credibility value for the user's permissions, i.e., the access credit value; the Feedback() function, which is used to feed back the result to the access control contract when the new access credibility value is greater than the set access node credit threshold and update the new access credibility value to the new access node credit threshold of the blockchain node, i.e., the computer security value of the blockchain network; S23. Design access control contract: Design the AccessControl() function to perform security decisions on the blockchain network, compare the pre-defined blockchain network security attacks with the computer security value fed back in the permission judgment contract, and make a decision to allow or deny access to the electronic archives; Design the ACCSetMC() function to call the management contract function and modify the user authority according to the result of the authority judgment contract; Design the CAnswer() function to return the result of the permission judgment contract to the system carrying the electronic archive to complete the operation of the controllable resources; Design the letePolicy() function to delete existing computer security attacks; Design the datePolicy() function to update computer security attacks; Design the Policy() function, which is responsible for adding new computer security attacks and including them in the attack list; Design the blishToACC() function to send the penalty result to the access control contract; Seven functions are added to the primary smart contract to form an access control contract.

3. The electronic archive sharing and utilization method based on multiple blockchains according to claim 1 is characterized in that: S3 constructs an access object credit assessment model based on the PSO-RBF neural network, and uses the PSO algorithm to update the parameters of the credit access object assessment model to obtain the best model parameters, and then obtain the best access object credit assessment model. The best access object credit assessment model is used to assess credit, including: S31. Constructing the access object credit assessment model based on PSO-RBF neural network: S311: Construct input layer: Set the number of nodes in the input layer, expressed as X = (x1, x2, x3, ..., x n ), the node is used to represent the input vector; the input vector is defined by the historical data of the blockchain; S312: Construct hidden layer: Set the number of nodes in the hidden layer, expressed as B = (b1, b2, ... b 20 ); The Gaussian kernel function is used as the radial basis function of the hidden layer to perform nonlinear mapping and feature extraction on the input vector, as shown in formula (1): Where x represents the input vector, c i represents the i-th hidden layer node, σ i Represents the activation function width of the i-th hidden layer neuron; S313: Construct output layer: Set the number of nodes in the output layer, denoted as Y, representing the trustworthiness of the access object, denoted as Y = γ, γ∈(0, 1); S314, obtain the relationship between the output layer and the input layer, as shown in formula (2), Among them, ω0 represents the parameter used to adjust the output offset, ω i represents the weight function between the i-th hidden node and the output node, and x represents the input vector; S32, using the PSO algorithm to update the center C and weight value ω of the radial basis function in the access object credit assessment model: Assume that the dimension of the space search for food is P, the total number of particles is n, and the position of the i-th particle in the P-dimensional space is represented by x i =(x i1 , x i2 , ..., x iP ), the speed is (v i1 , v i2 , ..., v iP ), the velocity and position equations are shown in formulas (3) and (4), in, represents the f-dimensional component of the m-th velocity of particle i; represents the f-dimensional component of the position of particle i at the mth iteration; represents the f-dimensional component of particle i at the optimal position; represents the global optimal position component of all particles in dimension f; y1 and y2 are defined as acceleration coefficient factors, ε represents a random number that follows a uniform distribution and is between [0, 1]; ρ represents the inertia weight of particle i, as shown in formula (5), Among them, ρ max and ρ min represents the maximum and minimum values ​​of inertial mass; h represents the current number of iterations, h max Indicates the maximum number of iterations; The speed and position are updated. The speed update formula is shown in formula (6): v i (t+1)=ω·v i (t)+b1·r1(p i -x i (t))+b2·r2·(p g -x i (t)) (6) Among them, v i (t) is the velocity of the ith particle at time t; ω represents the weight value, b1 and b2 are learning factors, r1 and r2 are random numbers in the interval [0, 1], and p i is the individual extreme value of the ith particle, p g is the global extreme value, x i (t) is the position of the ith particle at time t; v i (t) and x i The expression of (t) is shown in formulas (7) and (8), Where D is the dimension of the solution space; The position update formula is shown in formula (9): X i (t+1)=x i (t)+v i (t+1) (9) Obtain the residual sum of squares between the model predicted output value and the actual output value, as shown in formula (10), E=(γ i -the i ) 2 (10) Among them, E represents the residual sum of squares, γ i Represents the model's predicted output value, i.e., the continuously updated position, o i Indicates the actual output value, o i As shown in formula (11), Among them, i Indicates the actual output value, X i (t) represents the optimal position of the i-th particle at time t, C i represents the center value of the i-th particle, and g represents the width of the model network layer; When the value of E converges, the PSO algorithm stops iterating the credit assessment model of the access object and saves the ω obtained by the last iterative update speed and the C obtained by the actual output value. i , as the weight value ω and center value C of the radial basis function, the update is completed; S33: Input the updated weight value ω and the center value C into the access object credit evaluation model, and use the updated access object credit evaluation model to evaluate the user's credit.

4. The electronic archive sharing and utilization method based on multiple blockchains according to claim 3 is characterized in that: The input vectors include, but are not limited to, illegal request ratio, unauthorized request ratio, no-access-resource ratio, abnormal request ratio, prohibited request ratio, and request-not-allowed ratio.

5. The electronic archive sharing and utilization method based on multiple blockchains according to claim 1 is characterized in that: S4 uses the optimal access object credit evaluation model to optimize the authority judgment contract to obtain an optimized authority judgment contract capable of credit calculation, and forms an optimized Internet attribute access control model based on smart contracts with the management contract and the access control contract, including: S41, the weight value ω of the radial basis function updated by the PSO algorithm and the actual output value o corresponding to the center value C i Input into the permission judgment contract as the initial access node credibility threshold; S42: Determine whether there is an access control request and whether the access control request is abnormal: If there is no access control request, the PSO algorithm is started at regular intervals to update the weight value ω and the center value C of the radial basis function, and the actual output value o corresponding to the weight value ω and the center value C of the radial basis function obtained by the update is i Input into the permission judgment contract as the new access node credibility threshold; If the permission judgment contract receives the access control request sent by the management contract, it calls the QueryAccess() function to query whether there is an abnormal access event. If normal, it will feedback to the management contract. If abnormal, it will feedback to the management contract and use the Networks() function to call the best access object credit assessment model to generate a new access credit value. If the new access credibility value is less than the initial access node credibility threshold, the command that the access credibility value is less than the initial access node credibility threshold is directly fed back to the access control contract. If the new access credibility value is greater than the set access node credibility threshold, the Feedback() function is used to update the new access credibility value to the new access node credibility threshold and feed back the command that the new access credibility value is greater than the initial access node credibility threshold to the access control contract.

6. The electronic archive sharing and utilization method based on multiple blockchains according to claim 1 is characterized in that: S5 uses the optimized smart contract-based Internet attribute access control model to build a multi-blockchain electronic archive sharing and utilization process to achieve secure access and sharing of electronic archives, including: The multi-blockchain electronic archive sharing and utilization process includes an initialization phase, a device registration phase, a dynamic authority allocation phase, and an execution phase; S51, initialization phase: The proxy node deploys the management contract, authority judgment contract and access control contract to the blockchain, and enables all proxy nodes to obtain the address through broadcasting; S52, device registration stage, the device registration stage is the block node registration stage of the archive blockchain network: The manager completes the registration of the block node and generates a pair of keys, which are used to encrypt and verify the transmission of electronic documents in the network; The manager adds an access policy for block S1 to access resource R2 in block S2 to the permission judgment contract; the access policy defines the way and scope in which block S1 can access resource R2 in block S2; resource R2 is the electronic file to be accessed; S53, Dynamic Permission Allocation Stage: The subject S1 who applies for access to the electronic archive initiates an access request to the electronic archive resource R2 of the object S2; the object S2 is the electronic archive carrying system; the subject S1 who applies for access to the electronic archive is the user who applies for access to the electronic archive; Subject S1 provides its identity and permission information to prove that it has the authority to access resource R2 of object S2; Object S2 verifies the identity and permission information provided by subject S1 to ensure that subject S1 actually has the required permissions; If the verification is successful, object S2 will perform access control on the electronic archive to determine whether subject S1 is allowed to access resource R2 of object S2; the determining factors of access control include but are not limited to the authority level of subject S1, the sensitivity of resource R2, access time and access method; Object S2 determines the final access control decision by calculating and comparing the decision factors. If subject S1 is authorized to access resource R2, the system will allow it to access the resource. If subject S1 is not authorized to access resource R2, the system will deny its access request. S54, Execution phase: The proxy node checks and generates access control results based on the optimized smart contract-based Internet attribute access control model and records them in the blockchain; The administrator of the blockchain node obtains the management authority of the electronic file, and after completing the access control of the electronic file, writes the record information of the electronic file access control into the new block, triggers the corresponding event of the smart contract, and feeds back the access permission results to the administrator of the blockchain to complete the sharing and use of the electronic file.

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