Metacosmic-oriented multi-source data sharing method and management platform

Abstract

The invention relates to the technical field of data sharing management, in particular to a meta-universe-oriented multi-source data sharing method and management platform, and the management platform comprises a sharing management platform which is internally provided with a data preprocessing unit, a sharing classification unit, an authentication supervision unit, an access security unit and an information management unit; according to the invention, analysis is carried out from two points of data sharing processing and data sharing access security, so that the integrity and access security of the shared data are ensured, that is, shared information quality security supervision analysis is carried out on the sharing risk information of the to-be-shared data, so that the integrity of the to-be-shared data is ensured; the shared information of the key-free shared data is further subjected to refined classification management analysis, so that the key-free shared data is subjected to reasonable classification management, and the access permission information is subjected to access permission security certification analysis in a progressive manner, so that security certification is performed on the access end; the data loss risk in the sharing platform is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of data sharing management, and in particular to a multi-source data sharing method and management platform for a metaverse. Background Art

[0002] As the epitome of the next generation of the Internet, Metaverse fully integrates new generation interactive technologies such as AR / VR, 5G, blockchain, edge computing, artificial intelligence and other new generation information technologies, providing users with a virtual parallel universe full of infinite possibilities, and also providing good development opportunities for the industry;

[0003] With the development of the Internet and the deepening of informatization, more and more data can be used, and various data sources are also increasing. In order to realize the maximum value of data, open sharing of data is inevitable in the era. However, in the existing technology, it is impossible to screen, process and divide the data transmitted from multiple sources, which affects the quality of data sharing, and it is impossible to perform security supervision on the access rights authentication of the sharing platform, which increases the risk of data loss in the sharing platform, and it is impossible to further supervise the access network nodes, which increases the impact of the access network nodes on the security of data in the sharing platform;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide a multi-source data sharing method and management platform for the metaverse to solve the technical defects mentioned above. The present invention ensures the integrity and access security of shared data by analyzing from two points of view: data sharing processing and data sharing access security. That is, the shared data is pre-processed to obtain the data to be shared, and the shared information quality and security supervision analysis is performed on the shared risk information of the shared data, so as to divide the shared data to ensure the integrity of the data to be shared. At the same time, the data to be shared corresponding to the normal signal is divided into key shared data and keyless shared data, and the shared information of the keyless shared data is further refined and classified for management and analysis, so as to reasonably classify and manage the keyless shared data. The access permission security authentication analysis is performed on the access permission information in a progressive manner, so as to perform security authentication on the access terminal, so as to reduce the risk of data loss in the sharing platform, and at the same time help to improve the data security of the sharing platform.

[0006] The object of the present invention can be achieved by the following technical solutions: A multi-source data sharing management platform for the metaverse, including a sharing management platform, wherein the sharing management platform is internally provided with a data preprocessing unit, a sharing classification unit, an authentication supervision unit, an access security unit and an information management unit;

[0007] The data preprocessing unit is used to preprocess the shared data uploaded by each sharing source to obtain the data to be shared, collect the shared risk information of the data to be shared, and perform shared information quality and safety supervision analysis on the shared risk information to obtain normal signals and abnormal signals;

[0008] The sharing classification unit is used to respond to the normal signal, and to distinguish and process the access rights of the shared data corresponding to the normal signal, so as to classify the shared data into keyed shared data and keyless shared data, and to further perform detailed classification management and analysis on the shared information of the keyless shared data, so as to obtain the classification items and storage signals corresponding to the keyless shared data;

[0009] The authentication supervision unit is used to respond to the accessible signal, collect access permission information of the sharing platform, and perform access permission security authentication analysis on the access permission information to obtain an authorization signal and a jump signal;

[0010] The access security unit is used to respond to the accessible signal and the authorization signal, collect the access data of the shared platform, and perform security authentication supervision feedback analysis on the access data to obtain normal network nodes and abnormal network nodes.

[0011] Preferably, the shared information quality security supervision and analysis process of the data preprocessing unit is as follows:

[0012] The shared data uploaded by each sharing source is obtained, and the shared data is preprocessed, including removing duplicate values ​​and invalid data, and the preprocessed shared data is obtained and set as the data to be shared;

[0013] The sharing risk information of each data to be shared is obtained, the sharing risk data includes the number of bytes and the storage value, the number of bytes and the storage value before the data to be shared is obtained, and the number of bytes and the storage value before the transmission are extracted with text characters, and the string composed of the number of bytes and the storage value before the transmission is set as the string before the transmission, the number of bytes and the storage value after the data to be shared is obtained, and the number of bytes and the storage value after the transmission are extracted with text characters, and the string composed of the number of bytes and the storage value after the transmission is set as the string after the transmission;

[0014] The pre-transmission string and the post-transmission string are compared and analyzed one by one to obtain the number of differences between the pre-transmission string and the post-transmission string, and the number of differences between the pre-transmission string and the post-transmission string is set as the shared information quality index, and the shared information quality index is judged:

[0015] If the shared information quality index is equal to zero, a normal signal is generated;

[0016] If the shared information quality index is not equal to zero, an exception signal is generated.

[0017] Preferably, the detailed classification management and analysis process of the shared classification unit is as follows:

[0018] The data to be shared corresponding to the normal signal is obtained and set as normal shared data. The access rights to the normal shared data are obtained and the access rights are judged and processed:

[0019] If the normal shared data is set with access rights, the normal shared data is determined to be key-shared data;

[0020] If the normal shared data is not set with access rights, the normal shared data is determined to be keyless shared data;

[0021] The keyless shared data is set to g, where g is a natural number greater than zero, and the shared information of each keyless shared data is obtained, the shared information including the keyword proportion and the word meaning index. The keyword proportion and the word meaning index are labeled GZg and CZg respectively, and the partition matching index Pg of each keyless shared data is obtained according to the formula. The partition matching index Pg is matched and classified with the preset partition matching index interval entered and stored internally, so as to obtain the classification item and storage signal corresponding to the keyless shared data.

[0022] Preferably, the keyword proportion represents the product of the number of keywords set in the key sharing data and the paragraph proportion after data normalization processing, and the paragraph proportion represents the total number of paragraphs corresponding to the number of keywords appearing in the paragraph exceeding the preset threshold; the word meaning index represents the ratio of the number of paragraphs corresponding to the number of text groups consisting of more than two consecutive keywords greater than the preset threshold to the total number of paragraphs.

[0023] Preferably, the access authority security authentication analysis process of the authentication supervision unit is as follows:

[0024] Collect the time period during which the sharing platform is running and set it as a time threshold, and obtain the access permission information of the sharing platform within the time threshold. The access permission information includes the registration ID, registration password, and real-name authentication;

[0025] Extract characters from the registration ID and the registration password, and set the character string formed by extracting characters from the registration ID and the registration password as the first identification string, extract characters from the last six digits of the identity document for real-name authentication, and set the character string formed by extracting characters from the last six digits of the identity document for real-name authentication as the second identification string, and set the character string formed by combining the first identification string and the second identification string as the standard character string;

[0026] Get the filling page of each access terminal, get the filling ID, filling password and the last six digits of the ID card from the filling page, set the string composed of the characters of the filling ID and filling password as the authentication identification string, set the string composed of the characters of the last six digits of the ID card as the authentication identity string, set the string composed of the authentication identification string and the authentication identity string as the authentication authority string, and compare and analyze the authentication authority string with the standard string one by one:

[0027] If the authentication permission string and the standard string are in one-to-one correspondence, an authorization signal is generated;

[0028] If the one-to-one correspondence between the authentication authority string and the standard string is not satisfied, a jump signal is generated.

[0029] Preferably, the security authentication supervision feedback analysis process of the access security unit is as follows:

[0030] The access network node data of the shared platform within the time threshold is obtained. The access network node data includes the network environment assessment value and the network risk assessment value. The network risk assessment coefficient Wh of each access network node is obtained according to the formula. The network risk assessment coefficient Wh is compared and analyzed with the preset network risk assessment coefficient threshold stored in the internal input, and the normal network nodes and abnormal network nodes are obtained.

[0031] According to a multi-source data sharing management platform for the metaverse as described in claim 6, it is characterized in that the network environment evaluation value represents the product of the total number of data losses of the access network node corresponding to the authorization signal and the total number of log record errors after data normalization processing; the network risk evaluation value represents the value obtained by dividing the difference between the maximum and minimum network speeds of the access network node corresponding to the authorization signal and the vulnerability patching rate after data normalization processing.

[0032] The beneficial effects of the present invention are as follows:

[0033] (1) The present invention ensures the integrity and access security of shared data by analyzing from two points of view: data sharing processing and data sharing access security. That is, the shared data is preprocessed to obtain the data to be shared, and the shared information quality and security supervision analysis is performed on the shared risk information of the shared data, so as to divide the shared data to ensure the integrity of the shared data. At the same time, the shared data corresponding to the normal signal is divided into key-shared data and keyless shared data, and the shared information of the keyless shared data is further refined and classified for management analysis, so as to reasonably classify and manage the keyless shared data.

[0034] (2) Perform access rights security authentication analysis on access rights information in a progressive manner so as to perform security authentication on the access end, thereby reducing the risk of data loss in the shared platform and helping to improve the data security of the shared platform. At the same time, further security authentication supervision feedback analysis is performed on the access data to reduce the impact of abnormal network nodes on the shared data in the public platform and avoid data loss and tampering. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention will be further described below in conjunction with the accompanying drawings;

[0036] Figure 1 It is a flowchart of the system of the present invention;

[0037] Figure 2 It is a reference diagram of the method of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] Embodiment 1:

[0040] See also Figure 1 to Figure 2 As shown, the present invention is a multi-source data sharing management platform for the metaverse, including a sharing management platform, wherein the sharing management platform is internally provided with a data preprocessing unit, a sharing classification unit, an authentication supervision unit, an access security unit and an information management unit;

[0041] The data preprocessing unit is used to preprocess the shared data uploaded by each sharing source to obtain the data to be shared, collect the shared risk information of the data to be shared, and perform shared information quality and safety supervision analysis on the shared risk information, so as to divide the shared data to be shared, so as to ensure the integrity of the data to be shared. The specific shared information quality and safety supervision analysis process is as follows:

[0042] Acquire the shared data uploaded by each sharing source, and preprocess the shared data, the preprocessing includes removing duplicate values, removing invalid data, etc., acquire the preprocessed shared data, and set it as the data to be shared, acquire the sharing risk information of each data to be shared, the sharing risk data includes the number of bytes and the storage value, acquire the number of bytes and the storage value before the data to be shared is transmitted, and perform text character extraction on the number of bytes and the storage value before transmission, and set the string composed of the text character extraction on the number of bytes and the storage value before transmission as the pre-transmission string, acquire the number of bytes and the storage value after the data to be shared is transmitted, and perform text character extraction on the number of bytes and the storage value after transmission, and set the string composed of the text character extraction on the number of bytes and the storage value after transmission as the post-transmission string;

[0043] The pre-transmission string and the post-transmission string are compared and analyzed one by one to obtain the number of differences between the pre-transmission string and the post-transmission string, and the number of differences between the pre-transmission string and the post-transmission string is set as the shared information quality index, and the shared information quality index is judged:

[0044] If the shared information quality index is equal to zero, a normal signal is generated;

[0045] If the shared information quality index is not equal to zero, an abnormal signal is generated, and the normal signal and the abnormal signal are sent to the information management unit. After receiving the normal signal and the abnormal signal, the information management unit immediately performs corresponding preset operations corresponding to the normal signal and the abnormal signal, so as to divide the data to be shared to ensure the integrity of the data to be shared;

[0046] When a normal signal is generated, the sharing classification unit is used to respond to the normal signal and perform discrimination processing on the access rights of the shared data corresponding to the normal signal so as to divide it into key-shared data and keyless shared data, and further perform detailed classification management and analysis on the shared information of the keyless shared data so as to perform reasonable classification management on the keyless shared data to improve the subsequent retrieval rate. The specific detailed classification management and analysis process is as follows:

[0047] The data to be shared corresponding to the normal signal is obtained and set as normal shared data. The access rights to the normal shared data are obtained and the access rights are judged and processed:

[0048] If the normal shared data is set with access rights, the normal shared data is determined to be key-shared data;

[0049] If the normal shared data is not set with access rights, the normal shared data is determined to be keyless shared data;

[0050] Set the keyless shared data to g, where g is a natural number greater than zero, and obtain the shared information of each keyless shared data, including the keyword proportion and word meaning index. The keyword proportion and word meaning index are labeled GZg and CZg respectively. According to the formula Pg = (GZg×a1+CZg×a2×a3) 2 The partition matching index of each keyless shared data is obtained, wherein a1 and a2 are preset proportional factor coefficients of the keyword proportion and the word meaning index respectively, and the proportional factor coefficient is used to correct the deviation of each parameter in the formula calculation process, so as to make the calculation result more accurate, a3 is the preset correction factor coefficient, a1, a2 and a3 are all greater than zero, Pg is the partition matching index of each keyless shared data, the partition matching index Pg is matched and classified with the preset partition matching index interval stored in the internal input, and the classification item and storage signal corresponding to the keyless shared data are obtained, and the storage signal is sent to the information management unit, and the keyless shared data is included in the corresponding classification item.

[0051] In the embodiment of the present invention, the keyword proportion indicates the product value obtained by multiplying the number of keywords set in the key sharing data and the paragraph proportion after data normalization processing, and the paragraph proportion indicates the total number of paragraphs corresponding to the number of keywords appearing in the paragraph exceeding the preset threshold;

[0052] In the embodiment of the present invention, the word meaning index represents the ratio of the number of paragraphs corresponding to the number of text groups consisting of more than two consecutive keywords being greater than a preset threshold to the total number of paragraphs.

[0053] Embodiment 2:

[0054] When the shared management platform generates an accessible signal, the authentication supervision unit is used to respond to the accessible signal, collect the access rights information of the shared platform, and perform access rights security authentication analysis on the access rights information, so as to perform security authentication on the access end, thereby reducing the risk of data loss in the shared platform and helping to improve the data security of the shared platform. The specific access rights security authentication analysis process is as follows:

[0055] Collect the time period during which the sharing platform is running and set it as a time threshold, and obtain the access permission information of the sharing platform within the time threshold. The access permission information includes the registration ID, registration password, and real-name authentication;

[0056] Extract characters from the registration ID and the registration password, and set the character string formed by extracting characters from the registration ID and the registration password as the first identification string, extract characters from the last six digits of the identity document for real-name authentication, and set the character string formed by extracting characters from the last six digits of the identity document for real-name authentication as the second identification string, and set the character string formed by combining the first identification string and the second identification string as the standard character string;

[0057] Get the filling page of each access terminal, get the filling ID, filling password and the last six digits of the ID card from the filling page, set the string composed of the characters of the filling ID and filling password as the authentication identification string, set the string composed of the characters of the last six digits of the ID card as the authentication identity string, set the string composed of the authentication identification string and the authentication identity string as the authentication authority string, and compare and analyze the authentication authority string with the standard string one by one:

[0058] If the authentication permission string and the standard string are in one-to-one correspondence, an authorization signal is generated;

[0059] If the authentication permission string does not correspond to the standard string one by one, a jump signal is generated. When the jump signal is generated, it will automatically jump to the filling page immediately;

[0060] The access security unit is used to respond to the access signal and authorization signal, collect the access data of the sharing platform, and perform security authentication supervision feedback analysis on the access data to ensure the data security of the sharing platform and avoid data loss and tampering. The specific security authentication supervision feedback analysis process is as follows:

[0061] Obtain access network node data of the shared platform within the time threshold. The access network node data includes network environment assessment value and network risk assessment value. According to the formula Wh = [(HJh × f1 + WPh × f2) ÷ f3] 2 The network risk assessment coefficient of each access network node is obtained, wherein HJh represents the network environment assessment value of the access network node corresponding to each authorization signal, WPh represents the network risk assessment value of each access network node, h represents the access network node corresponding to each authorization signal, h is a natural number greater than zero, f1 and f2 are preset weight factor coefficients of the network environment assessment value and the network risk assessment value, respectively, f3 is a preset fault tolerance factor coefficient, f1, f2 and f3 are all greater than zero, Wh is the network risk assessment coefficient of the access network node corresponding to each authorization signal, and the network risk assessment coefficient Wh is compared and analyzed with the preset network risk assessment coefficient threshold value stored in the internal input:

[0062] If the ratio between the network risk assessment coefficient Wh and the preset network risk assessment coefficient threshold is less than 1, the access network node corresponding to the corresponding authorization signal is determined to be a normal network node;

[0063] If the ratio between the network risk assessment coefficient Wh and the preset network risk assessment coefficient threshold is greater than or equal to 1, the access network node corresponding to the corresponding authorization signal is determined to be an abnormal network node, and the normal network node and the abnormal network node are sent to the information management unit. After receiving the normal network node and the abnormal network node, the information management unit immediately divides and manages the normal network node and the abnormal network node to reduce the impact of the abnormal network node on the shared data in the public platform, so as to improve the security of the shared data access process;

[0064] In the embodiment of the present invention, the network environment evaluation value represents the product value obtained by multiplying the total number of data loss of the access network node corresponding to the authorization signal and the total number of log record errors after data normalization processing. It should be noted that the environment of the access network node is analyzed from the perspective of network security and function to reduce the impact of unstable access network nodes on the shared platform, thereby reducing the potential impact risk;

[0065] In an embodiment of the present invention, the network risk assessment value represents the value obtained by dividing the difference between the maximum and minimum network speeds of the access network node corresponding to the authorization signal by the vulnerability patching rate after data normalization. It should be noted that the analysis is performed from the perspective of network risk to understand the network security of the access network node and to avoid interference of risky networks with data in the shared platform.

[0066] Embodiment three:

[0067] A multi-source data sharing method for the metaverse includes the following steps:

[0068] Step 1: Pre-process the shared data uploaded by each sharing source to obtain the data to be shared, and collect the sharing risk information of the data to be shared;

[0069] Step 2: Conduct shared information quality and safety supervision analysis on shared risk information, and perform judgment processing on the obtained shared information quality index. If a normal signal is obtained, proceed to step 3. If an abnormal signal is obtained, feedback management is provided;

[0070] Step 3: The access rights are identified and processed by information feedback so as to be divided into key-shared data and keyless shared data, and the shared information of the keyless shared data is further classified and analyzed to obtain the classification items and storage signals corresponding to the keyless shared data;

[0071] Step 4: Perform access rights security authentication analysis on the access rights information, and compare the obtained authentication permission string with the standard string one by one. If an authorization signal is obtained, proceed to step 5. If a jump signal is obtained, it will automatically jump to the filling page;

[0072] Step 5: Perform security authentication supervision feedback analysis on access data in a progressive manner, compare and analyze the obtained network risk assessment coefficient Wh, and obtain normal network nodes and abnormal network nodes;

[0073] In summary, the present invention ensures the integrity and access security of shared data by analyzing from two points of view: data sharing processing and data sharing access security. That is, the shared data is preprocessed to obtain the data to be shared, and the shared information quality and security supervision analysis is performed on the shared risk information of the shared data, so as to divide the shared data to ensure the integrity of the data to be shared. At the same time, the data to be shared corresponding to the normal signal is divided into key shared data and keyless shared data, and the shared information of the keyless shared data is further refined and classified for management and analysis, so as to reasonably classify and manage the keyless shared data to improve the subsequent retrieval rate, and the access permission security authentication analysis is performed on the access permission information in a progressive manner, so as to perform security authentication on the access terminal, so as to reduce the risk of data loss in the sharing platform, and at the same time help to improve the data security of the sharing platform, and at the same time further perform security authentication supervision feedback analysis on the access data to reduce the impact of abnormal network nodes on the shared data in the public platform, and avoid data loss and tampering.

[0074] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0075] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A multi-source data sharing management platform for the Metaverse, characterized by: It includes a shared management platform, which is internally provided with a data pre-processing unit, a shared classification unit, an authentication and supervision unit, an access security unit and an information management unit; The data preprocessing unit is used to preprocess the shared data uploaded by each sharing source to obtain the data to be shared, collect the shared risk information of the data to be shared, and perform shared information quality and safety supervision analysis on the shared risk information to obtain normal signals and abnormal signals; The sharing classification unit is used to respond to the normal signal, and to distinguish and process the access rights of the shared data corresponding to the normal signal, so as to classify the shared data into keyed shared data and keyless shared data, and to further perform detailed classification management and analysis on the shared information of the keyless shared data, so as to obtain the classification items and storage signals corresponding to the keyless shared data; The authentication supervision unit is used to respond to the accessible signal, collect access permission information of the sharing platform, and perform access permission security authentication analysis on the access permission information to obtain an authorization signal and a jump signal; The access security unit is used to respond to the accessible signal and the authorization signal, collect the access data of the shared platform, and perform security authentication supervision feedback analysis on the access data to obtain normal network nodes and abnormal network nodes.

2. A multi-source data sharing management platform for the Metaverse according to claim 1, characterized in that: The shared information quality security supervision and analysis process of the data preprocessing unit is as follows: The shared data uploaded by each sharing source is obtained, and the shared data is preprocessed, including removing duplicate values ​​and invalid data, and the preprocessed shared data is obtained and set as the data to be shared; The sharing risk information of each data to be shared is obtained, the sharing risk data includes the number of bytes and the storage value, the number of bytes and the storage value before the data to be shared is obtained, and the number of bytes and the storage value before the transmission are extracted with text characters, and the string composed of the number of bytes and the storage value before the transmission is set as the string before the transmission, the number of bytes and the storage value after the data to be shared is obtained, and the number of bytes and the storage value after the transmission are extracted with text characters, and the string composed of the number of bytes and the storage value after the transmission is set as the string after the transmission; The pre-transmission string and the post-transmission string are compared and analyzed one by one to obtain the number of differences between the pre-transmission string and the post-transmission string, and the number of differences between the pre-transmission string and the post-transmission string is set as the shared information quality index, and the shared information quality index is judged: If the shared information quality index is equal to zero, a normal signal is generated; If the shared information quality index is not equal to zero, an exception signal is generated.

3. A multi-source data sharing management platform for the Metaverse according to claim 2, characterized in that: The detailed classification management and analysis process of the shared classification unit is as follows: The data to be shared corresponding to the normal signal is obtained and set as normal shared data. The access rights to the normal shared data are obtained and the access rights are judged and processed: If the normal shared data is set with access rights, the normal shared data is determined to be key-shared data; If the normal shared data is not set with access rights, the normal shared data is determined to be keyless shared data; The keyless shared data is set to g, where g is a natural number greater than zero, and the shared information of each keyless shared data is obtained, the shared information including the keyword proportion and the word meaning index. The keyword proportion and the word meaning index are labeled GZg and CZg respectively, and the partition matching index Pg of each keyless shared data is obtained according to the formula. The partition matching index Pg is matched and classified with the preset partition matching index interval entered and stored internally, so as to obtain the classification item and storage signal corresponding to the keyless shared data.

4. A multi-source data sharing management platform for the Metaverse according to claim 3, characterized in that: The keyword proportion represents the product of the number of keywords set in the key sharing data and the paragraph proportion after data normalization processing. The paragraph proportion represents the total number of paragraphs corresponding to the number of keywords appearing in the paragraph exceeding the preset threshold; the word meaning index represents the ratio of the number of paragraphs corresponding to the number of text groups consisting of more than two consecutive keywords greater than the preset threshold to the total number of paragraphs.

5. A multi-source data sharing management platform for the Metaverse according to claim 4, characterized in that: The access rights security authentication analysis process of the authentication supervision unit is as follows: Collect the time period during which the sharing platform is running and set it as a time threshold, and obtain the access permission information of the sharing platform within the time threshold. The access permission information includes the registration ID, registration password, and real-name authentication; Extract characters from the registration ID and the registration password, and set the character string formed by extracting characters from the registration ID and the registration password as the first identification string, extract characters from the last six digits of the identity document for real-name authentication, and set the character string formed by extracting characters from the last six digits of the identity document for real-name authentication as the second identification string, and set the character string formed by combining the first identification string and the second identification string as the standard character string; Get the filling page of each access terminal, get the filling ID, filling password and the last six digits of the ID card from the filling page, set the string composed of the characters of the filling ID and filling password as the authentication identification string, set the string composed of the characters of the last six digits of the ID card as the authentication identity string, set the string composed of the authentication identification string and the authentication identity string as the authentication authority string, and compare and analyze the authentication authority string with the standard string one by one: If the authentication permission string and the standard string are in one-to-one correspondence, an authorization signal is generated; If the one-to-one correspondence between the authentication authority string and the standard string is not satisfied, a jump signal is generated.

6. A multi-source data sharing management platform for the Metaverse according to claim 5, characterized in that: The security authentication supervision feedback analysis process of the access security unit is as follows: The access network node data of the shared platform within the time threshold is obtained. The access network node data includes the network environment assessment value and the network risk assessment value. The network risk assessment coefficient Wh of each access network node is obtained according to the formula. The network risk assessment coefficient Wh is compared and analyzed with the preset network risk assessment coefficient threshold entered and stored internally to obtain normal network nodes and abnormal network nodes.

7. A multi-source data sharing management platform for the Metaverse according to claim 6, characterized in that: The network environment assessment value represents the product of the total number of data losses of the access network node corresponding to the authorization signal and the total number of log record errors after data normalization processing; the network risk assessment value represents the value obtained by dividing the difference between the maximum and minimum network speeds of the access network node corresponding to the authorization signal and the vulnerability patching rate after data normalization processing.

8. A multi-source data sharing method for the Metaverse, the method being applied to the multi-source data sharing management platform for the Metaverse as claimed in claim 7, characterized in that: The following steps are involved: Step 1: Preprocess the shared data uploaded by each sharing source to obtain the data to be shared, and collect the sharing risk information of the data to be shared; Step 2: Conduct shared information quality and safety supervision analysis on shared risk information, and perform judgment processing on the obtained shared information quality index. If a normal signal is obtained, proceed to step 3. If an abnormal signal is obtained, feedback management is provided; Step 3: The access rights are identified and processed by information feedback so as to be divided into key-shared data and keyless shared data, and the shared information of the keyless shared data is further classified and analyzed to obtain the classification items and storage signals corresponding to the keyless shared data; Step 4: Perform access rights security authentication analysis on the access rights information, and compare the obtained authentication permission string with the standard string one by one. If an authorization signal is obtained, proceed to step 5. If a jump signal is obtained, it will automatically jump to the filling page; Step 5: Perform security authentication supervision feedback analysis on the access data in a progressive manner, compare and analyze the obtained network risk assessment coefficient Wh, and obtain normal network nodes and abnormal network nodes.

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