Self-adaptive configuration method and system for credential and credential platform

Abstract

The invention discloses a self-adaptive configuration method and system for a credential platform. Configuration information of different services on each node in the same cluster is configured in the same target terminal. And respectively carrying out adaptive configuration and installation package deployment in the target terminal according to the operating system type and the system architecture type. And after the setting is completed, entering a pre-starting environment through the boot file, and entering a virtual system. And after the virtual system is entered, performing configuration of a silent installation file to complete deployment of the credential and credential platform. The method simplifies the configuration process of different services on each node in the same cluster, can update the configuration information in real time, enables the configuration information to take effect without restarting the service, achieves the hot configuration effect, enables the operation and maintenance to be more visual, convenient and rapid, increases a configuration automatic rollback mechanism, and improves the efficiency. Under the condition of configuration errors, the cloud platform can still run normally, and the stability and fault tolerance of the platform are improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and specifically to a method and system for adaptively configuring an information and communication platform. Background Art

[0002] The ICT industry is the information technology application innovation industry. The core of the ICT industry development is to build a domestic information technology software and hardware underlying architecture system and a full-cycle ecosystem through industry applications, laying a solid digital foundation for the future development of science and technology. At present, it is necessary to vigorously develop software and hardware with independent intellectual property rights to ensure the ownership and controllability of some operating systems.

[0003] In recent years, there are more and more ICT platforms. ICT brings together some previous industries and gives them a new name: Information Technology Application Innovation Industry, referred to as "ICT". ICT involves industries including IT infrastructure: CPU chips, servers, storage, switches, routers, various clouds and related service content, basic software: databases, operating systems, middleware, application software: OA, ERP, office software, government applications, streaming version signing software, information security: boundary security products, terminal security products, etc. In traditional technology, due to the niche nature of the ICT platform CPU and system, there is no standard automated process for deploying the system, which greatly affects the system deployment efficiency of the ICT platform, and thus affects the testing efficiency under the ICT platform. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for adaptive configuration of an information and communication platform to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above purpose, the present invention provides the following technical solution: a method for adaptively configuring an information innovation platform, comprising the following steps:

[0006] 1) Configure the configuration information of different services on each node in the same cluster in the same target terminal;

[0007] 2) performing adaptive configuration and installation package deployment in the target terminal according to the operating system type and system architecture type respectively;

[0008] 3) After the setting is completed, enter the pre-start environment through the boot file and enter the virtual system;

[0009] 4) After entering the virtual system, configure the silent installation file to complete the deployment of the trusted innovation platform.

[0010] Furthermore, step 1) includes: calling the underlying commands of the trusted computing platform through the API management configuration unit to configure the configuration information of different services on each node under the same cluster in the same target terminal; deploying the configuration platform and creating a target terminal for storing the configuration information; adding initial configuration information through the management interface of the configuration platform and storing the initial configuration information in the target terminal; adding, deleting, modifying or querying the configuration information stored in the target terminal; and exchanging data between the configuration information and the target terminal through ORM.

[0011] Further, step 2) includes: for the Loongson architecture, packaging the source code into a deb installation package in the source code packaging environment under the Loongson architecture to deploy the installation package in the Loongson environment; for the Loongson architecture, determining whether the deployment test function is currently available, if so, packaging the source code into a deb installation package to deploy the installation package in the Loongson environment, if the deployment test function is currently unavailable, automatically calling the backup implementation method to re-determine whether the deployment test function is currently available.

[0012] Furthermore, step 2) also includes: if the service on the corresponding node of the trusted innovation platform runs successfully, the configuration is determined to be correct, and the configuration status in the corresponding configuration information is configured to the first state; if the service on the corresponding node of the trusted innovation platform runs abnormally, it is determined to be a configuration error, and the configuration status in the corresponding configuration information is configured to the second state, and the configuration information with the most recent configuration time and the first configuration status is re-acquired to configure the trusted innovation platform; after entering the virtual system, it is necessary to set the configuration system related information of the silent installation file in advance, and the relevant information includes the user password and pre-installation package.

[0013] Furthermore, the file classification model adaptively configured in step 2) includes the following steps:

[0014] S1. Construct file reference network data. First, construct a node feature matrix, then construct an adjacency matrix describing the topological structure of the file reference network, and finally divide it into training set, validation set, and test set;

[0015] S2. Build an improved graph convolutional neural network and perform training;

[0016] S3. Use the model trained in step S2 to classify the files. The prediction method uses the model trained in step S2 to classify the files.

[0017] Furthermore, in step S2, the model construction specifically includes the following steps:

[0018] a) Calculate the Laplacian matrix L, where D is the degree matrix of the adjacency matrix A and I is the N-dimensional identity matrix;

[0019]

[0020] b) Initialize the node similarity matrix B as an N*N zero matrix;

[0021] c) Calculate the edge weight matrix C, which is a matrix of size N*N. The element c in the matrix ij Indicates the similarity between the feature vectors of node i and node j. The more similar they are, the closer c ij The larger the value of ;

[0022] C = softmax(B) #(2)

[0023] d) Extract the features of the graph network, where Θ is the parameter matrix to be learned of size d*m, d is the dimension of the node features, and m is the dimension of the output H;

[0024] H=CLXΘ#(3)

[0025] e) By edge weight c ij Calculate the new feature vector expression s of the current node j , and compress it using the squash function to obtain the final feature vector expression v of the current node j , where W in Formula 3 is ij is a parameter matrix to be learned of size N*N*d; the squash function can compress the vector, making the vector with small modulus smaller and the vector with large modulus larger;

[0026] u j|i =W ij H i #(4)

[0027]

[0028] f) Calculate u j|i With v j Similarity, update the edge weight matrix, where k represents all neighboring points of node i;

[0029] b ij =b ij +u j|i ·v j #(7)

[0030]

[0031] g) Calculate the value of the loss function, where H is the prediction result of GCN on the category to which the file belongs, as shown in Formula 3, V is the prediction result of the dynamic routing algorithm on the category to which the file belongs, as shown in Formula 6, y is the actual category of the file, and crossenrtopy is the cross entropy loss function;

[0032] loss=0.8*crossentropy(H,y)+0.2*crossentropy(V,y)#(9)

[0033] Repeat steps d, e, f, and g until the model converges.

[0034] Furthermore, a system for an adaptive configuration method of an ICT platform includes a configuration platform, a target terminal and the ICT platform deployed in the same cluster, wherein: the configuration platform is used to generate configuration information of different services on each node in the same cluster; the target terminal is used to store the configuration information configured by the configuration platform; and the ICT platform is used to obtain the configuration information in the target terminal to run different services on each node.

[0035] Furthermore, it also includes: an API management configuration unit, which is used to configure the configuration information of different services on each node under the same cluster in the same database through the management interface of the configuration platform; or, it is used to call the underlying commands of the cloud platform to configure the configuration information of different services on each node under the same cluster in the same database.

[0036] Furthermore, the configuration information includes a configuration service name, a configuration node name, a configuration type, a configuration value, a configuration variable name, a configuration time, and a configuration status.

[0037] Furthermore, when the service on the corresponding node of the trusted innovation platform runs successfully, it is determined that the configuration is correct, and the configuration status in the corresponding configuration information is configured to the first state; when the service on the corresponding node of the trusted innovation platform runs abnormally, it is determined that the configuration is wrong, and the configuration status in the corresponding configuration information is configured to the second state, and the configuration information with the most recent configuration time and the first configuration status is re-obtained to configure the cloud platform.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] (1) The configuration information of the present invention is uniformly managed using a database, which can adapt to more different application scenarios, simplify the configuration process of different services on each node in the same cluster, and can update the configuration information in real time, so that the configuration information can take effect without restarting the service, achieving the effect of hot configuration, making operation and maintenance more intuitive, convenient and fast, and adding an automatic configuration rollback mechanism. In the event of a configuration error, the cloud platform can still operate normally, thereby improving the platform stability and fault tolerance.

[0040] (2) The present invention obtains the operating system type and system architecture type of the credible innovation platform corresponding to the target terminal, and adaptively configures and deploys the installation package in the target terminal for the operating system type and system architecture type; and adaptively configures and deploys the installation package for the chip type corresponding to the credible innovation platform in the target terminal, and can adaptively adapt various operating systems, system architectures and chips of the credible innovation platform in the target terminal, which can effectively improve the automation and efficiency of the credible innovation platform configuration, and can effectively improve the convenience of the credible innovation platform configuration. When users download this terminal assistant, they do not need to distinguish too many different domestic operating systems. At the same time, after downloading and installing, the functions provided by the terminal assistant are also adapted to different operating systems, and there will not be such a big difference in user use. In addition, this terminal assistant provides an application center module. After the user selects the software, the subsequent installation package acquisition and architecture adaptation operations are automatically performed by the program. At the same time, the performance of each terminal can be monitored, and the user can clearly know the terminal usage status. For users of the credible innovation operating system, this application helps to simplify the operation process, solve problems such as unfamiliar operation, and greatly improve the user experience of using credible innovation products.

[0041] (3) The configuration information of the adaptive configuration system of the credible innovation platform of the present invention is uniformly managed using a database, which can adapt to more different application scenarios and simplify the configuration process of different services on each node in the same cluster. It can update the configuration information in real time and make the configuration information effective without restarting the service, achieving the effect of hot configuration and making operation and maintenance more intuitive, convenient and fast. In addition, an automatic configuration rollback mechanism is added, which can still enable the normal operation of the credible innovation platform in the event of a configuration error, thereby improving the stability and fault tolerance of the platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0043] Figure 1 A schematic diagram of the process of the adaptive configuration method of the credential creation platform of the present invention;

[0044] Figure 2 Establish a flow chart for the adaptively configured file classification model;

[0045] Figure 3 Schematic diagram of the convolution process of the improved GCN for the file classification model;

[0046] Figure 4 This is a flowchart of the dynamic routing algorithm for the file classification model;

[0047] Figure 5This is a schematic diagram comparing the accuracy of the graph convolutional neural network before and after the improvement;

[0048] Figure 6 This is a schematic diagram of the adaptive configuration system of the trusted computing platform of the present invention. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present invention are described clearly and completely below. 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.

[0050] The present invention provides the following technical solutions: Figure 1 As shown, a method for adaptively configuring a trusted innovation platform is Figure 1 As shown, the following steps are included:

[0051] 1) Configure the configuration information of different services on each node in the same cluster in the same target terminal;

[0052] 2) performing adaptive configuration and installation package deployment in the target terminal according to the operating system type and system architecture type respectively;

[0053] 3) After the setting is completed, enter the pre-start environment through the boot file and enter the virtual system;

[0054] 4) After entering the virtual system, configure the silent installation file to complete the deployment of the trusted innovation platform.

[0055] Its configuration information is uniformly managed using a database, which can adapt to more different application scenarios, simplify the configuration process of different services on each node in the same cluster, and can update configuration information in real time, making the configuration information effective without restarting the service, achieving the effect of hot configuration, making operation and maintenance more intuitive, convenient and fast, and adding an automatic configuration rollback mechanism, which can enable the cloud platform to operate normally in the event of configuration errors, thereby improving the platform stability and fault tolerance.

[0056] Step 1) includes: calling the underlying commands of the trusted computing platform through the API management configuration unit to configure the configuration information of different services on each node under the same cluster in the same target terminal; deploying the configuration platform and creating a target terminal for storing the configuration information; adding initial configuration information through the management interface of the configuration platform and storing the initial configuration information in the target terminal; adding, deleting, modifying or querying the configuration information stored in the target terminal; and exchanging data between the configuration information and the target terminal through ORM.

[0057] The configuration platform in the present invention is deployed on the master node of the cluster in a containerized form, and is created in a way that the front-end and back-end are separated, so that the configuration interface can be adapted to the xinchuang platform, or its own front-end interface can be used alone. The back-end code and the database interact with each other through the ORM method, and the model class created by the back-end is generated as a migration file. The configuration platform in the present invention is deployed on the master node of the cluster in a containerized form, and is created in a way that the front-end and back-end are separated, so that the configuration interface can be adapted to the xinchuang platform, or its own front-end interface can be used alone. The back-end code and the target terminal interact with each other through the ORM method, and the model class created by the back-end is generated as a migration file. The target terminal is created when the configuration platform is deployed, and the migration file is executed when the user deploys it, thereby creating a target terminal for storing configuration information. In order for the platform to be used normally, the configuration platform must first add initial configuration information. When the user configures the front-end of the configuration platform, the parameters are passed to the back-end by calling the API interface in the API management configuration unit, and the back-end persists the configuration information to the target terminal through the ORM method. When the trusted innovation platform reads configuration information, it first creates a connection with the target terminal on the trusted innovation platform, creates model classes and migration files that are consistent with the model classes of the configuration platform, and can use the ORM method to interact with the configuration platform to read configuration information. When the trusted innovation platform calls the configuration, it will pass the configuration service name, configuration node name, configuration type, and configuration variable name, and read the configuration information based on the configuration time and configuration status.

[0058] In step 2), it includes: for the Loongson architecture, in the source code packaging environment under the Loongson architecture, the source code is packaged into a deb installation package to deploy the installation package in the Loongson environment; for the Loongson architecture, it is determined whether the deployment test function is currently available, if so, the source code is packaged into a deb installation package to deploy the installation package in the Loongson environment, if the deployment test function is currently unavailable, the backup implementation method is automatically called to re-determine whether the deployment test function is currently available. In one or more embodiments of the present application, for different trusted terminals, different architectures, or different domestically produced chips, the terminal assistant needs to be adapted before it can be installed and deployed on the above-mentioned many trusted platforms. The adaptive configuration method of the trusted innovation platform can be executed by an application called a terminal assistant for adaptive configuration of the trusted innovation platform. The application can be pre-installed in the target terminal and started in the target terminal. The user can select or enter the operating system type and system architecture type of the trusted innovation platform corresponding to the target terminal in the front page of the application. The user can also select or enter the chip type corresponding to the trusted innovation platform in the front page of the application, so that the terminal assistant obtains the operating system type and system architecture type of the trusted innovation platform corresponding to the target terminal according to the user input, and determines the chip type corresponding to the trusted innovation platform automatically or according to the user input.

[0059] Step 2) also includes: if the service on the corresponding node of the trusted innovation platform runs successfully, the configuration is determined to be correct, and the configuration status in the corresponding configuration information is configured to the first status; if the service on the corresponding node of the trusted innovation platform runs abnormally, the configuration is determined to be wrong, and the configuration status in the corresponding configuration information is configured to the second status, and the configuration information with the most recent configuration time and the first configuration status is re-acquired to configure the trusted innovation platform; after entering the virtual system, it is necessary to set the configuration system related information of the silent installation file in advance, and the relevant information includes the user password and pre-installation package. The operating system type and system architecture type of the trusted innovation platform corresponding to the target terminal are obtained, and adaptive configuration and installation package deployment are performed in the target terminal for the operating system type and system architecture type respectively; and, the chip type corresponding to the trusted innovation platform is adaptively configured and the installation package is deployed in the target terminal, so that various operating systems, system architectures and chips of the trusted innovation platform can be adaptively adapted in the target terminal, which can effectively improve the automation and efficiency of the trusted innovation platform configuration, and can effectively improve the convenience of the trusted innovation platform configuration. When users download this terminal assistant, they do not need to distinguish too many different domestic operating systems. At the same time, after downloading and installing, the functions provided by the terminal assistant are also adapted to different operating systems, and there will not be such a big difference in user use. In addition, this terminal assistant provides an application center module. After the user selects the software, the subsequent installation package acquisition and architecture adaptation operations are automatically performed by the program. At the same time, the performance of each terminal can be monitored, and the user can clearly know the terminal usage status. For users of trusted innovation operating systems, this application helps to simplify the operation process, solve problems such as unfamiliar operation, and greatly improve the user experience of using trusted innovation products.

[0060] like Figure 2-5 As shown, the file classification model adaptively configured in step 2) includes the following steps:

[0061] S1. Construct file reference network data. First, construct a node feature matrix, then construct an adjacency matrix describing the topological structure of the file reference network, and finally divide it into training set, validation set, and test set;

[0062] S2. Build an improved graph convolutional neural network and perform training;

[0063] S3. Use the model trained in step S2 to classify the files. The prediction method uses the model trained in step S2 to classify the files.

[0064] Furthermore, in step S2, the model construction specifically includes the following steps:

[0065] a) Calculate the Laplacian matrix L, where D is the degree matrix of the adjacency matrix A and I is the N-dimensional identity matrix;

[0066]

[0067] b) Initialize the node similarity matrix B as an N*N zero matrix;

[0068] c) Calculate the edge weight matrix C, which is a matrix of size N*N. The element c in the matrix ij Indicates the similarity between the feature vectors of node i and node j. The more similar they are, the closer c ij The larger the value of ;

[0069] C = softmax(B) #(2)

[0070] d) Extract the features of the graph network, where Θ is the parameter matrix to be learned of size d*m, d is the dimension of the node features, and m is the dimension of the output H;

[0071] H=CLXΘ#(3)

[0072] e) By edge weight c ij Calculate the new feature vector expression s of the current node j , and compress it using the squash function to obtain the final feature vector expression v of the current node j , where W in Formula 3 is ij is a parameter matrix to be learned of size N*N*d; the squash function can compress the vector, making the vector with small modulus smaller and the vector with large modulus larger;

[0073] u j|i =W ij H i #(4)

[0074]

[0075] f) Calculate u j|i With v j Similarity, update the edge weight matrix, where k represents all neighboring points of node i;

[0076] b ij =b ij +u j|i ·v j #(7)

[0077]

[0078] g) Calculate the value of the loss function, where H is the prediction result of GCN on the category to which the file belongs, as shown in Formula 3, V is the prediction result of the dynamic routing algorithm on the category to which the file belongs, as shown in Formula 6, y is the actual category of the file, and crossenrtopy is the cross entropy loss function;

[0079] loss=0.8*crossentropy(H,y)+0.2*crossentropy(V,y)#(9)

[0080] Repeat steps d, e, f, and g until the model converges.

[0081] It not only utilizes the text information of the file and the citation relationship between files, but also takes into account the similarity of the word vectors of the files. This model takes into account the similarity of the word vectors between different files. If the word vector of a file cited by the current file is similar to the word vector of the current file, the weight of the edge between the two files will be relatively large; if the word vector of a file cited by the current file is not similar to the word vector of the current file, the weight of the edge between the two files will be relatively small. The word vector of the current file is weighted and averaged with the word vector of the file it cites, and the result is used as the vector expression of the current file. This reduces the impact of the referenced files with very different content from the current file on the classification results.

[0082] The configuration platform and the trusted innovation platform are deployed in the same cluster. Logging in to the configuration platform can change the configuration of each component of the trusted innovation platform. The configuration platform server provides an interface to the client, supporting users to add, delete, modify, and query configuration information on the configuration platform. The specific configuration methods are as follows: a) Add configuration information. On the management interface of the configuration platform, set the service name, node name, configuration type, configuration value, configuration variable name, and create a configuration information in combination with the configuration time and configuration status of the configuration; b) Query configuration information. On the management interface of the configuration platform, enter the id of the configuration information to query the corresponding configuration information in the database, and display each information in the configuration information on the management interface; c) Delete configuration information. After querying the configuration information, the corresponding configuration information can be deleted from the database; d) Modify configuration information. After querying the configuration information, one or more phases of information in the configuration information can be modified. The modified configuration information is stored in the database as a new configuration information, and the original configuration information will not be deleted. Among them, the configuration state in the present invention includes a first state (active) and a second state (error), the first state is a correct state, which can support the normal operation of the service, and the second state is an error state, which cannot support the normal operation of the service. Preferably, in the first configuration stage of the configuration information, the first state (active) is used as the default configuration state of the configuration information. After the trusted innovation platform obtains the corresponding configuration information, if the service on the corresponding node of the trusted innovation platform runs successfully, it is determined that the configuration is correct, and the configuration state in the corresponding configuration information is configured as the first state (active); if the service on the corresponding node of the trusted innovation platform runs abnormally, it is determined that the configuration is wrong, and the configuration state in the corresponding configuration information is configured as the second state (error).

[0083] The configuration information can be saved to the database through the configuration platform management interface or the underlying command call of the trusted innovation platform, which is convenient for data display or being called by the trusted innovation platform. In order for the trusted innovation platform to operate normally, the target terminal must contain the configuration information of different services on each node under the same cluster, and each service corresponds to at least one configuration information with a configuration status of the first state (active) for the corresponding service to operate normally. The trusted innovation platform can directly call the configuration information in the database, and after the configuration information is modified, it can take effect without restarting the corresponding service, and can achieve the effect of hot configuration. According to the configuration situation, the configuration information that is successfully called in the trusted innovation platform will be changed to active, and the configuration information in the configuration database will be changed again next time. If the cloud platform makes an error when calling after the configuration information in the configuration database is modified this time, the configuration automatic rollback mechanism will be started to call the most recent historical correct configuration information saved in the configuration database to ensure the continuous stability of the cloud platform.

[0084] The present invention also provides a system for a self-adaptive configuration method of a trust innovation platform, such as Figure 6 As shown, it includes a configuration platform, a target terminal and an information and innovation platform deployed in the same cluster, wherein: the configuration platform is used to generate configuration information of different services on each node in the same cluster; the target terminal is used to store the configuration information configured by the configuration platform; the information and innovation platform is used to obtain the configuration information in the target terminal to run different services on each node.

[0085] It also includes: an API management configuration unit, which is used to configure the configuration information of different services on each node under the same cluster in the same database through the management interface of the configuration platform; or, it is used to call the underlying command of the cloud platform to configure the configuration information of different services on each node under the same cluster in the same database. The configuration information includes the configuration service name, the configuration node name, the configuration type, the configuration value, the configuration variable name, the configuration time and the configuration status. When the service on the corresponding node of the credible innovation platform runs successfully, it is determined that the configuration is correct, and the configuration status in the corresponding configuration information is configured to the first state; when the service on the corresponding node of the credible innovation platform runs abnormally, it is determined that the configuration is wrong, and the configuration status in the corresponding configuration information is configured to the second state, and the configuration information with the most recent configuration time and the configuration status of the first state is re-acquired to configure the cloud platform. The configuration information is uniformly managed using a database, which can adapt to more different application scenarios and simplify the configuration process of different services on each node under the same cluster. It can update the configuration information in real time, make the configuration information effective without restarting the service, achieve the effect of hot configuration, and make operation and maintenance more intuitive, convenient and fast. In addition, an automatic configuration rollback mechanism has been added, which enables the trusted computing platform to operate normally even in the event of a configuration error, thereby improving the platform's stability and fault tolerance.

[0086] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A method for adaptively configuring a trusted computing platform, comprising the following steps: 1) Configure the configuration information of different services on each node in the same cluster in the same target terminal; 2) performing adaptive configuration and installation package deployment in the target terminal according to the operating system type and system architecture type respectively; 3) After the setting is completed, enter the pre-start environment through the boot file and enter the virtual system; 4) After entering the virtual system, configure the silent installation file to complete the deployment of the trusted innovation platform.

2. According to claim 1, a method for adaptively configuring a trusted computing platform is characterized in that: The step 1) comprises: Call the underlying commands of the Xinchuang platform through the API management configuration unit to configure the configuration information of different services on each node in the same cluster in the same target terminal; Deploy the configuration platform and create a target terminal for storing configuration information; Add initial configuration information through the management interface of the configuration platform and store the initial configuration information in the target terminal; Add, delete, modify or query the configuration information stored in the target terminal; The configuration information and the target terminal perform data interaction via ORM.

3. According to claim 1, a method for adaptively configuring a trusted computing platform is characterized in that: The step 2) comprises: The installation package deployment is targeted at the Loongson architecture, and the source code is packaged into a deb installation package in the source code packaging environment under the Loongson architecture to deploy the installation package in the Loongson environment; For the Loongson architecture, determine whether the deployment test function is currently available. If so, package the source code into a deb installation package to deploy the installation package in the Loongson environment. If the deployment test function is currently unavailable, automatically call the backup implementation method to re-determine whether the deployment test function is currently available.

4. According to claim 1, a method for adaptively configuring a trusted computing platform is characterized in that: The step 2) also includes: if the service on the corresponding node of the information innovation platform runs successfully, it is determined that the configuration is correct, and the configuration state in the corresponding configuration information is configured as the first state; If the service on the corresponding node of the trusted innovation platform runs abnormally, it is determined that there is a configuration error, and the configuration status in the corresponding configuration information is configured to the second status, and the configuration information with the most recent configuration time and the configuration status of the first status is re-obtained to configure the trusted innovation platform; After entering the virtual system, it is necessary to set the configuration system related information of the silent installation file in advance, and the related information includes the user password and the pre-installation package.

5. According to claim 1, a method for adaptively configuring a trusted computing platform is characterized in that: The file classification model adaptively configured in step 2) includes the following steps: S1. Construct file reference network data. First, construct a node feature matrix, then construct an adjacency matrix describing the topological structure of the file reference network, and finally divide it into training set, validation set, and test set; S2. Build an improved graph convolutional neural network and perform training; S3. Use the model trained in step S2 to classify the files. The prediction method uses the model trained in step S2 to classify the files.

6. According to claim 5, a method for adaptively configuring a trusted computing platform is characterized in that: In step S2, the model construction specifically includes the following steps: a) Calculate the Laplacian matrix L, where D is the degree matrix of the adjacency matrix A and I is the N-dimensional identity matrix; b) Initialize the node similarity matrix B as an N*N zero matrix; c) Calculate the edge weight matrix C, which is a matrix of size N*N. The element c in the matrix ij Indicates the similarity between the feature vectors of node i and node j. The more similar they are, the closer c ij The larger the value of ; C=softmax(B)#(2) d) Extract the features of the graph network, where Θ is the parameter matrix to be learned of size d*m, d is the dimension of the node features, and m is the dimension of the output H; H=CLXΘ#(3) e) By edge weight c ij Calculate the new feature vector expression s of the current node j , and compress it using the squash function to obtain the final feature vector expression v of the current node j , where W in Formula 3 is ij is a parameter matrix to be learned of size N*N*d; the squash function can compress the vector, making the vector with small modulus smaller and the vector with large modulus larger; u j|i =W ij A i #(4) f) Calculate u j|i With v j Similarity, update the edge weight matrix, where k represents all neighboring points of node i; b ij =b ij +u j|i ·v j #(7) g) Calculate the value of the loss function, where H is the prediction result of GCN on the category to which the file belongs, as shown in Formula 3, V is the prediction result of the dynamic routing algorithm on the category to which the file belongs, as shown in Formula 6, y is the actual category of the file, and crossenrtopy is the cross entropy loss function; loss=0.8*crossentropy(H,y)+0.2*crossentropy(V,y)#(9) Repeat steps d, e, f, and g until the model converges.

7. A self-adaptive configuration system for an information and innovation platform as described in claim 1 includes a configuration platform, a target terminal and an information and innovation platform deployed in the same cluster, wherein: Configuration platform, used to generate configuration information for different services on each node in the same cluster; The target terminal is used to store the configuration information configured by the configuration platform; The trusted computing platform is used to obtain configuration information from the target terminal to run different services on each node.

8. According to claim 7, the adaptive configuration system of the information innovation platform is characterized by: Also includes: The API management configuration unit is used to configure the configuration information of different services on each node in the same cluster in the same database through the management interface of the configuration platform; Or, it is used to call the underlying commands of the cloud platform to configure the configuration information of different services on each node in the same cluster in the same database.

9. According to claim 7, the adaptive configuration system of the information innovation platform is characterized by: The configuration information includes configuration service name, configuration node name, configuration type, configuration value, configuration variable name, configuration time and configuration status.

10. According to claim 7, the adaptive configuration system of the information innovation platform is characterized in that: When the service on the corresponding node of the trusted innovation platform runs successfully, it is determined that the configuration is correct, and the configuration status in the corresponding configuration information is configured to the first state; when the service on the corresponding node of the trusted innovation platform runs abnormally, it is determined that the configuration is wrong, and the configuration status in the corresponding configuration information is configured to the second state, and the configuration information with the most recent configuration time and the first configuration status is re-obtained to configure the cloud platform.

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