Cloud computing management system and cloud computing management method

Abstract

The invention discloses a cloud computing management system and a cloud computing management method.The cloud computing management system comprises a cloud client data end, a data acquisition system, a cloud resource management system and a cloud computing center management security system, and the cloud client data end is used for summarizing and storing related data of local clients; cloud resource data stored in the cloud client data end is collected to form a cloud resource data set, the collected data set is subjected to security analysis, and when it is detected that data in the cloud resource data set is security data, the data is transmitted to a cloud computing center management security system; the cloud computing center management security system carries out distributed storage and processing on security data of the cloud resource data set; according to the method, the observation analysis model of the cloud resource management system is constructed, the data processing state of the cloud nodes and the proportion degree information of the data can be effectively monitored in real time, malicious data is improved for optimization analysis, and the use efficiency, the safety and the cost effectiveness of the cloud resources are further improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a cloud computing management system and a cloud computing management method. Background Art

[0002] Cloud computing management system can be a management system under the network function virtualization architecture; cloud computing management entities can be deployed in management, automation and network orchestration. Although the existing cloud computing management system can realize a variety of cloud management functions, cloud management is the control and supervision of the infrastructure, services and applications run by the organization in the cloud. However, it is difficult to effectively monitor the data processing status of cloud nodes and the proportion of data in real time, and there is a lack of optimization analysis of malicious data, which easily leads to problems such as data redundancy, high cost and low processing effect. Summary of the invention

[0003] In view of the above problems existing in the existing cloud computing management system, the present invention is proposed.

[0004] Therefore, one of the objects of the present invention is to provide a cloud computing management system and a cloud computing management method, which can effectively monitor the data processing status of cloud nodes and data proportion information in real time by constructing an observation and analysis model of the cloud resource management system, and improve the optimization analysis of malicious data, thereby further improving the utilization efficiency, security and cost-effectiveness of cloud resources.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] On the one hand, the present invention provides a cloud computing management system, including a cloud customer data terminal, a data collection system, a cloud resource management system and a cloud computing center management security system, wherein the cloud customer data terminal is used to aggregate and store relevant data of local customers, collect cloud resource data stored in the cloud customer data terminal to form a cloud resource data set, and perform security analysis on the collected data set. When the data in the cloud resource data set is detected to be security data, it is transmitted to the cloud computing center management security system, and the cloud computing center management security system performs distributed storage and processing on the security data of the cloud resource data set;

[0007] The data acquisition system is used to obtain the local data of the cloud customer data terminal and the total information of the configuration information and file information of the cloud computing center management security system server, and at the same time obtain the system data changes of the cloud computing center management security system server when executing tasks, and generate an observation model based on the changes in the system data, and record and store the changes in the observation model according to the changes;

[0008] The cloud resource management system performs data information evaluation on the collected data set, and the data information evaluation obtains the ratio of the change amount information in the observation model to the matched configuration information and file information, and clusters the data set based on the data clustering algorithm, and collects the configuration information and file information whose ratio exceeds a threshold and is marked to form a malicious target data set, and generates a safe data set after screening; the cloud resource management system also includes a security optimization analysis unit, which is used to optimize and analyze the malicious data in the malicious target data set, and perform deep learning optimization analysis on the ratio of the configuration information and the file information based on a deep learning neural network model, that is, obtain the network connection status, network broadband status, network service status, computing service status and storage service status, to generate and output the analysis results of the malicious target data set;

[0009] The cloud computing center management security system includes a cloud computing center data security management unit and a cloud computing center equipment security management unit; wherein the cloud computing center data security management unit is used for pre-configured resource management, private cloud resource management, dynamic configuration resource management, and hybrid cloud resource management of security data in the security data center.

[0010] As a preferred solution of the present invention, the observation model of the data acquisition system is specifically to calculate the matching value of the network topology structure of different nodes of the cloud customer data terminal, as shown below:

[0011]

[0012] Where m is the number of cloud nodes i at the cloud customer data end, score(Q) i is the comprehensive score of cloud customer data end cloud node i, α i is the weight correction coefficient of cloud node i, β i is the attribute value of cloud node i, w i is the weight coefficient of cloud node i, score(q) i is the predicted value of cloud node i.

[0013] As a preferred solution of the present invention, wherein: the storage threshold of the number of data blocks stored in each cloud node of the cloud customer data end is defined as H by the cloud resource management system, and the storage threshold Hi corresponding to the cloud node i is as follows:

[0014]

[0015] Among them, L represents the total number of divided data blocks, C i is the storage priority of cloud node i calculated above, C j is the storage priority of cloud node j, and μ is the adjustment parameter.

[0016] As a preferred solution of the present invention, the security optimization analysis unit is used to optimize and analyze the malicious data in the malicious target data set, wherein the analysis result ratio parameter of the malicious target data set is generated, and the deep learning neural network model for judging the resource ratio is used as the deep learning neural network model to perform the optimization analysis of the deep learning of the malicious target data set, which is specifically analyzed by the following formula, as follows:

[0017]

[0018] Among them, U(xi) e k+1 represents the proportion parameter output of malicious data of neuron e in the k+1th layer, d represents the total number of neurons in the kth layer, represents the connection weight between neuron d in the kth layer and neuron e in the k+1th layer, U(xi) k represents the malicious target data ratio parameter of neuron d in the kth layer, represents the bias term of the e-term neuron in the k+1th layer, and sig[*] represents the activation function.

[0019] As a preferred solution of the present invention, the security optimization analysis unit also includes an optimization analysis of the malicious data. According to the proportion of the malicious data and a preset threshold, it is determined whether the data in each category is malicious data exceeding the proportion. When malicious data exceeding the proportion is detected, the malicious data exceeding the proportion in the category will be deleted.

[0020] As a preferred solution of the present invention, the cloud computing center equipment security management unit includes an environment monitoring module, a dynamic monitoring module, and an anti-theft monitoring module.

[0021] As a preferred solution of the present invention, the environment monitoring module includes: a temperature and humidity sensor for real-time monitoring of temperature and humidity changes in the environment, a camera for visual monitoring and capturing dynamic image information, and a dust concentration sensor for detecting smoke and dust content in the air;

[0022] The dynamic monitoring module includes: a liquid leakage warning device for the wireless flood alarm group that can sense liquid leakage and issue an alarm in time, an intelligent power detector for monitoring and managing the energy consumption of the equipment, and a power status monitoring device for the power failure detector group that is responsible for monitoring the power status and ensuring that the equipment can respond in time in the event of a power failure;

[0023] The anti-theft monitoring module includes: an anti-theft sensor group for detecting illegal intrusion behavior and a door access manager group responsible for managing entry and exit permissions.

[0024] As a preferred solution of the present invention, the access methods of the business access system of the cloud computing management system include Web access, computer access, smart terminal access, E-mail access, and kiosk access.

[0025] In one aspect, the present invention provides a cloud computing management method, comprising:

[0026] Obtain the total information of the local data of the cloud customer data terminal and the configuration information and file information of the cloud computing center management security system server;

[0027] At the same time, the system data changes of the cloud computing center management security system server when executing the task are obtained, and an observation model is generated based on the changes of the system data, and the changes are recorded and stored according to the observation model;

[0028] Performing data information evaluation on the collected data set, wherein the data information evaluation obtains the ratio of the amount of change information in the observation model to the amount of configuration information and the amount of file information matched, and clusters the data set based on a data clustering algorithm, and collects the data sets marked with the ratio of the amount of configuration information and the amount of file information exceeding a threshold to form a malicious target data set, and generates a safe data set after screening;

[0029] Optimizing and analyzing the malicious data in the malicious target data set, performing deep learning optimization analysis on the ratio of the configuration information volume to the file information volume based on the deep learning neural network model, that is, obtaining the network connection status, network bandwidth status, network service status, computing service status and storage service status, generating and outputting the analysis results of the malicious target data set;

[0030] The cloud computing center data security management unit is used for pre-configured resource management, private cloud resource management, dynamic configuration resource management, and hybrid cloud resource management of security data in the security data center.

[0031] Compared with the prior art, the present invention has the following beneficial effects: by constructing an observation and analysis model of the cloud resource management system, the present invention can effectively monitor the data processing status of cloud nodes and the proportion of data in real time, and improve the optimization analysis of malicious data, thereby further improving the utilization efficiency, security and cost-effectiveness of cloud resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0033] in:

[0034] Figure 1 It is a schematic diagram of the modular structure of the cloud computing management system of the present invention;

[0035] Figure 2 It is a flowchart of the cloud computing management method of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0037] Reference Figure 1-Figure 2 , is an embodiment of the present invention, which provides a cloud computing management system and a cloud computing management method thereof, wherein the cloud computing management system comprises a cloud customer data terminal 100, a data collection system 101, a cloud resource management system 102 and a cloud computing center management security system 103, wherein the cloud customer data terminal 100 is used to aggregate and store relevant data of local customers, collect cloud resource data stored in the cloud customer data terminal 100 to form a cloud resource data set, and perform security analysis on the collected data set, and when the data in the cloud resource data set is detected to be secure data, it is transmitted to the cloud computing center management security system 103, and the cloud computing center management security system 103 performs distributed storage and processing on the security data of the cloud resource data set;

[0038] The data acquisition system 101 of this embodiment is used to obtain the local data of the cloud client data terminal 100 and the total information of the configuration information and file information of the cloud computing center management security system 103 server, and at the same time obtain the system data changes of the cloud computing center management security system 103 server when executing tasks, and generate an observation model based on the changes in the system data, and record and store the changes in the observation model;

[0039] The cloud resource management system 102 of this embodiment performs data information evaluation on the collected data set. The data information evaluation obtains the ratio of the change amount information in the observation model to the matched configuration information and file information, and clusters the data set based on the data clustering algorithm. The configuration information and file information ratio exceeding the threshold are marked and collected to form a malicious target data set, and a safe data set is generated after screening; the cloud resource management system 102 also includes a security optimization analysis unit, which is used to optimize and analyze the malicious data in the malicious target data set, and perform deep learning optimization analysis on the ratio of the configuration information and the file information based on the deep learning neural network model, that is, obtain the network connection status, network broadband status, network service status, computing service status and storage service status, generate and output the analysis results of the malicious target data set;

[0040] The cloud computing center management security system 103 of this embodiment includes a cloud computing center data security management unit and a cloud computing center equipment security management unit; wherein the cloud computing center data security management unit is used for pre-configured resource management of security data in the security data center, private cloud resource management, dynamically configured resource management, and hybrid cloud resource management.

[0041] Specifically, in this embodiment, the observation model of the data collection system 101 is specifically to calculate the matching value of the network topology structure of different nodes of the cloud customer data terminal 100, as shown below:

[0042]

[0043] Where m is the number of cloud nodes i at the cloud customer data end 100, score(Q) i is the comprehensive score of 100 cloud nodes i at the cloud customer data end, α i is the weight correction coefficient of cloud node i, β i is the attribute value of cloud node i, w i is the weight coefficient of cloud node i, score(q) i is the predicted value of cloud node i.

[0044] In this embodiment, based on the above further description, the cloud resource management system 102 defines the storage threshold of the number of data blocks stored in each cloud node of the cloud client data terminal 100 as H, and the storage threshold Hi corresponding to the cloud node i is as follows:

[0045]

[0046] Among them, L represents the total number of divided data blocks, C i is the storage priority of cloud node i calculated above, C j is the storage priority of cloud node j, and μ is the adjustment parameter.

[0047] It should be emphasized in this embodiment that the security optimization analysis unit is used to optimize and analyze the malicious data in the malicious target data set, wherein the analysis result ratio parameter of the malicious target data set is generated, and the deep learning neural network model for judging the resource ratio is used as the deep learning neural network model to perform optimization analysis of the deep learning of the malicious target data set, which is specifically analyzed and obtained through the following formula, as follows:

[0048]

[0049] Among them, U(xi) e k+1 represents the proportion parameter output of malicious data of neuron e in the k+1th layer, d represents the total number of neurons in the kth layer, represents the connection weight between neuron d in the kth layer and neuron e in the k+1th layer, U(xi) k represents the malicious target data ratio parameter of neuron d in the kth layer, represents the bias term of the e-term neuron in the k+1th layer, and sig[*] represents the activation function.

[0050] At the same time, the security optimization analysis unit of this embodiment also includes optimization analysis of malicious data. According to the proportion of malicious data and a preset threshold, it is determined whether the data in each category is malicious data that exceeds the proportion. When malicious data that exceeds the proportion is detected, the malicious data that exceeds the proportion in the category will be deleted.

[0051] In addition, the cloud computing center equipment security management unit of this embodiment includes an environment monitoring module, a dynamic monitoring module, and an anti-theft monitoring module.

[0052] Specifically, in this embodiment, the environment monitoring module includes: a temperature and humidity sensor for real-time monitoring of temperature and humidity changes in the environment, a camera for visual monitoring and capturing dynamic image information, and a dust concentration sensor for detecting smoke and dust content in the air;

[0053] The dynamic monitoring module includes: a liquid leakage alarm for the wireless flood alarm group that can sense liquid leakage and issue an alarm in time, an intelligent power detector for monitoring and managing the energy consumption of the equipment, and a power status monitoring device for the power failure detector group that is responsible for monitoring the power status and ensuring that the equipment can respond in time in the event of a power failure;

[0054] The anti-theft monitoring module includes: an anti-theft sensor group for detecting illegal intrusion and an access control manager group responsible for managing entry and exit permissions.

[0055] Specifically, in this embodiment, the access modes of the service access system of the cloud computing management system include Web access, computer access, smart terminal access, E-mail access, and kiosk access.

[0056] At the same time, this embodiment also provides a cloud computing management method as follows:

[0057] Obtain the total information of the local data of the cloud client data terminal 100 and the configuration information and file information of the server of the cloud computing center management security system 103;

[0058] At the same time, the system data changes of the cloud computing center management security system 103 server when executing the task are obtained, and an observation model is generated based on the changes in the system data, and the changes are recorded and stored according to the observation model;

[0059] Perform data information evaluation on the collected data set. The data information evaluation obtains the ratio of the change amount information in the observation model to the matched configuration information and file information, and clusters the data set based on the data clustering algorithm. The data sets with the ratio of configuration information and file information exceeding the threshold are marked and collected to form a malicious target data set, and then a safe data set is generated after screening.

[0060] Optimize and analyze the malicious data in the malicious target data set, and perform deep learning optimization analysis on the ratio of configuration information volume and file information volume based on the deep learning neural network model, that is, obtain the network connection status, network bandwidth status, network service status, computing service status and storage service status, generate and output the analysis results of the malicious target data set;

[0061] The cloud computing center data security management unit is used for pre-configured resource management of security data in the security data center, private cloud resource management, dynamically configured resource management, and hybrid cloud resource management.

[0062] Specifically, the system improves the efficiency, security and cost-effectiveness of cloud resource use through the following aspects: Real-time monitoring and analysis: The system can monitor the data processing status of cloud nodes in real time, analyze the data proportion information, and provide real-time data support for cloud resource management. Malicious data optimization: By identifying and optimizing malicious data, the system can reduce security threats and improve the security of cloud resources. Improve resource utilization efficiency: The system optimizes resource allocation and reduces resource waste through intelligent analysis models, thereby improving the efficiency of cloud resource use. Cost-benefit analysis: The system can help enterprises optimize costs by monitoring and analyzing the use of cloud resources, identifying inefficient resources, and adjusting and optimizing them to reduce costs.

[0063] To sum up, the cloud resource management system 102 of the present invention not only improves the efficiency and security of cloud resource utilization, but also optimizes cost-effectiveness through the observation and analysis model. The above-mentioned cloud computing management system and method scheme, by constructing an observation and analysis model of the cloud resource management system 102, can effectively monitor the data processing status of cloud nodes and data proportion information in real time, and improve the optimization analysis of malicious data, thereby further improving the efficiency, security and cost-effectiveness of cloud resource utilization.

[0064] It should be understood that the various parts of the present application can be implemented with hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the above embodiment method can be completed by instructing the relevant hardware through a program, which can be stored in a computer-readable storage medium, and when the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0065] In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a disk or an optical disk, etc.

[0066] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. Cloud computing management system, characterized by: It includes a cloud customer data terminal, a data collection system, a cloud resource management system and a cloud computing center management security system. The cloud customer data terminal is used to aggregate and store relevant data of local customers, collect cloud resource data stored in the cloud customer data terminal to form a cloud resource data set, and perform security analysis on the collected data set. When the data in the cloud resource data set is detected to be secure data, it is transmitted to the cloud computing center management security system, and the cloud computing center management security system performs distributed storage and processing on the security data of the cloud resource data set; The data acquisition system is used to obtain the local data of the cloud customer data terminal and the total information of the configuration information and file information of the cloud computing center management security system server, and at the same time obtain the system data changes of the cloud computing center management security system server when executing tasks, and generate an observation model based on the changes in the system data, and record and store the changes in the observation model according to the changes; The cloud resource management system performs data information evaluation on the collected data set, and the data information evaluation obtains the ratio of the change amount information in the observation model to the matched configuration information and file information, and clusters the data set based on the data clustering algorithm, and collects the configuration information and file information whose ratio exceeds a threshold and is marked to form a malicious target data set, and generates a safe data set after screening; the cloud resource management system also includes a security optimization analysis unit, which is used to optimize and analyze the malicious data in the malicious target data set, and perform deep learning optimization analysis on the ratio of the configuration information and the file information based on a deep learning neural network model, that is, obtain the network connection status, network broadband status, network service status, computing service status and storage service status, to generate and output the analysis results of the malicious target data set; The cloud computing center management security system includes a cloud computing center data security management unit and a cloud computing center equipment security management unit; The cloud computing center data security management unit is used for pre-configured resource management, private cloud resource management, dynamic configuration resource management, and hybrid cloud resource management of security data in the security data center.

2. The cloud computing management system according to claim 1, characterized in that: The observation model of the data acquisition system is specifically to calculate the matching value of the network topology structure of different nodes of the cloud customer data end, as shown below: in, m is the number of cloud nodes i at the cloud customer data end, score(Q) i is the comprehensive score of cloud customer data end cloud node i, α i is the weight correction coefficient of cloud node i, β i is the attribute value of cloud node i, w i is the weight coefficient of cloud node i, score(q) i is the predicted value of cloud node i.

3. The cloud computing management system according to claim 2, characterized in that: The cloud resource management system defines the storage threshold of the number of data blocks stored in each cloud node of the cloud customer data end as H, and the storage threshold Hi corresponding to the cloud node i is as follows: Among them, L represents the total number of divided data blocks, C i is the storage priority of cloud node i calculated above, C j is the storage priority of cloud node j, and μ is the adjustment parameter.

4. The cloud computing management system according to claim 1, characterized in that: The security optimization analysis unit is used to optimize and analyze the malicious data in the malicious target data set, wherein the analysis result ratio parameter of the malicious target data set is generated, and the deep learning neural network model for judging the resource ratio is used as the deep learning neural network model to perform optimization analysis of the deep learning of the malicious target data set, which is specifically analyzed and obtained through the following formula: Among them, U(xi) e k+1 represents the proportion parameter output of malicious data of neuron e in the k+1th layer, d represents the total number of neurons in the kth layer, represents the connection weight between neuron d in the kth layer and neuron e in the k+1th layer, U(xi) k represents the malicious target data ratio parameter of neuron d in the kth layer, represents the bias term of the e-term neuron in the k+1th layer, and sig[*] represents the activation function.

5. The cloud computing management system according to claim 4, characterized in that: The security optimization analysis unit also includes an optimization analysis of the malicious data. According to the proportion of the malicious data and a preset threshold, it is determined whether the data in each category is malicious data that exceeds the proportion. When malicious data that exceeds the proportion is detected, the malicious data that exceeds the proportion in the category is deleted.

6. The cloud computing management system according to claim 1, characterized in that: The cloud computing center equipment security management unit includes an environment monitoring module, a dynamic monitoring module, and an anti-theft monitoring module.

7. The cloud computing management system according to claim 6, characterized in that: The environmental monitoring module includes: a temperature and humidity sensor for real-time monitoring of temperature and humidity changes in the environment, a camera for visual monitoring and capturing dynamic image information, and a dust concentration sensor for detecting smoke and dust content in the air; The dynamic monitoring module includes: a liquid leakage warning device for the wireless flood alarm group that can sense liquid leakage and issue an alarm in time, an intelligent power detector for monitoring and managing the energy consumption of the equipment, and a power status monitoring device for the power failure detector group that is responsible for monitoring the power status and ensuring that the equipment can respond in time in the event of a power failure; The anti-theft monitoring module includes: an anti-theft sensor group for detecting illegal intrusion behavior and a door control manager group responsible for managing entry and exit permissions.

8. The cloud computing management system according to claim 1, wherein: The access methods of the business access system of the cloud computing management system include Web access, computer access, smart terminal access, E-mail access, and kiosk access.

9. A cloud computing management method applied to the cloud computing management system according to claim 1, characterized in that: include: Obtain the total information of the local data of the cloud customer data terminal and the configuration information and file information of the cloud computing center management security system server; At the same time, the system data changes of the cloud computing center management security system server when executing the task are obtained, and an observation model is generated based on the changes of the system data, and the changes are recorded and stored according to the observation model; Performing data information evaluation on the collected data set, wherein the data information evaluation obtains the ratio of the amount of change information in the observation model to the amount of configuration information and the amount of file information matched, and clusters the data set based on a data clustering algorithm, and collects the data sets marked with the ratio of the amount of configuration information and the amount of file information exceeding a threshold to form a malicious target data set, and generates a safe data set after screening; Optimizing and analyzing the malicious data in the malicious target data set, performing deep learning optimization analysis on the ratio of the configuration information volume to the file information volume based on the deep learning neural network model, that is, obtaining the network connection status, network bandwidth status, network service status, computing service status and storage service status, generating and outputting the analysis results of the malicious target data set; The cloud computing center data security management unit is used for pre-configured resource management, private cloud resource management, dynamic configuration resource management, and hybrid cloud resource management of security data in the security data center.

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