Server data whole-process monitoring system based on artificial intelligence

Abstract

The invention discloses a server data full-process monitoring system based on artificial intelligence, and relates to the technical field of data monitoring. Management information data is set through a management platform, a request instruction is generated according to the management information data and sent to a process data acquisition module, and request data corresponding to a server is acquired according to the request instruction; preprocessing the request data by using a data preprocessing unit arranged in the data processing module to obtain pre-response request data; encryption is carried out through a transmission encryption model set by the transmission encryption unit to obtain a response key; the response sending module responds to the to-be-responded request data to the corresponding client according to the client information, and obtains an abnormal state signal according to the response key; the monitoring and early warning module monitors the abnormal state signal; and the data security of the internal server is effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data monitoring, and in particular to an artificial intelligence-based full-process monitoring system for server data. Background Art

[0002] Servers typically have hardware components such as high-performance processors, large-capacity memory, high-speed storage devices, and powerful network interfaces. These hardware components provide the basic computing, storage, and communication capabilities for the operation of the server. A server is a specific IT device that provides computing power and runs software applications in a network environment. It provides computing or application services to other clients (such as personal computers, smartphones, ATMs, and other terminal devices) in the network. Generally speaking, a server has the ability to respond to service requests, provide services, and guarantee services. For other client-server data, the entire process mainly includes receiving requests, request processing, and response sending. Among them, the server listens to a specific port through the network interface and waits for the client to send a request. When the client (such as a browser, mobile application, etc.) sends a request to the server, the server's network interface receives the request data and passes it to the corresponding software module for processing. The server performs corresponding processing based on the type and content of the request. The server encapsulates the processed result into a response message and sends it back to the client through the network interface. Among them, within enterprises, departments, etc., since a server faces users of the entire internal network, a large amount of server data and full-process data will be generated, and a large amount of server data needs to be transmitted securely; but in the existing technology, the server data required internally is not securely protected during the transmission process, resulting in leakage, which in turn leads to failure to be discovered in time; again, the client privacy is involved in the whole process; but many security monitoring focuses on external network attacks, while the monitoring of abnormal behavior or malicious operations of internal users is relatively weak; which in turn causes data leakage and other problems; therefore, in order to solve the above technical problems, the present invention provides a server data full-process monitoring system based on artificial intelligence. Summary of the Invention

[0003] In order to solve the above technical problems, the present invention provides a server data full-process monitoring system based on artificial intelligence; The object of the present invention can be achieved by the following technical solutions: an artificial intelligence-based server data full-process monitoring system, comprising a management platform, wherein the management platform is connected to a process data acquisition module, a data processing module, a response sending module, and a monitoring and early warning module; The management platform is provided with management information data for generating a request instruction according to the management information data, wherein the management information data includes client information and user information; The process data acquisition module is used to collect the request data corresponding to the server according to the request instruction; The data processing module is provided with a data preprocessing unit and a transmission encryption unit; the data preprocessing unit is provided with a preprocessing strategy for preprocessing the request data according to the preprocessing strategy to obtain pre-response request data; the transmission encryption unit is provided with a transmission encryption model, and the pre-response request data is encrypted according to the transmission encryption model to obtain a response key; The response sending module is used to respond to the request data to be responded to the corresponding client according to the client information, and obtain the abnormal status signal according to the response key; The monitoring and early warning module is used to monitor abnormal status signals.

[0004] Furthermore, the process of the management platform setting management information data includes: Setting the internal network environment corresponding to the server, wherein the internal network environment includes the internal network and the client address range; The client information includes the client network, IP address and specific port; the user information includes basic personal information and internal information; The client whose network and IP address belong to the internal network and client address range corresponding to the internal network environment is marked as an authorized client; and the basic personal information is graded and authorized according to the internal information, and marked as a graded authorized user; and then the request content range corresponding to the graded authorized user is set.

[0005] Furthermore, the process of generating a request instruction according to the management information data includes: The client is authorized to send a request instruction through a specific port; the request instruction includes a request time, a keyword request data type; the request instruction is connected with the corresponding client information and sent to the process data acquisition module.

[0006] Furthermore, the process of the process data acquisition module acquiring the request data corresponding to the server according to the request instruction includes: The server obtains the keywords and request data types corresponding to each request instruction, filters the type content corresponding to the authorized client according to the request data type, and then retrieves the key content corresponding to the type content according to the keyword and marks it as request data.

[0007] Furthermore, the process of the data preprocessing unit setting the preprocessing strategy includes: The preprocessing strategy is used to number the request data corresponding to a specific port, denoted as i, where i=1, 2, ..., j; and j is a positive integer; then split each request data into subject content and data content; open the subject content; set the subpacket data capacity, subpacketize the data content according to the subpacket data capacity, obtain all subpacket data corresponding to the data content, and number them, denoted as n, where n=1, 2, ..., m; and m is a positive integer; then encode the subpacket data, denoted as in.

[0008] Furthermore, the process of obtaining the pre-response request data includes: The corresponding request data is encrypted according to the sub-packet data encoding to generate the corresponding encryption code, which is recorded as TLkininin...; where T represents the request time; Lk represents the number K corresponding to the request data type L; The encryption code is concatenated with the corresponding request data to generate pre-response request data.

[0009] Furthermore, the process of the transmission encryption unit setting the transmission encryption model includes: Set a server interface transmission rule, which is used to encrypt the subpackage data according to the encryption code of the pre-response request data and the corresponding coding order of the encryption code to obtain the response key, and transmit it to the corresponding specific port in sequence to generate a transmission encryption model.

[0010] Furthermore, the process of obtaining the response key includes: Step S1: Set up a sub-contract key database, schedule different sub-contract data keys in the sub-contract key database according to the sub-contract data transmission sequence, perform symmetrical encryption on the sub-contract data in sequence, and obtain the initial sub-contract data key; Step S2: Setting a transmission update period, and updating the initial sub-package data key according to the sub-package data key in the sub-package key database according to the transmission update period to obtain the latest sub-package data key; Step S3: The latest sub-packet data key transmitted to the specific port is connected according to the sub-packet data transmission sequence to generate a response key.

[0011] Furthermore, the process of the response sending module acquiring the abnormal status signal includes: The client receives several pre-response request data and selects the corresponding pre-response request data according to the subject content; then inputs the corresponding user information and determines whether the subject content meets the request content range of the user authorized by the corresponding level of the user information; if it meets the range, the client obtains the corresponding encryption code and obtains the pre-response request data according to the encryption code; otherwise, a user abnormal status signal is generated; Input the response password for the pre-response request data and determine whether it matches. If it matches, obtain the request data; otherwise, generate a response abnormal status signal.

[0012] Furthermore, the process of the monitoring and early warning module monitoring the abnormal status signal includes: Upon receiving a user abnormal status signal, the corresponding user information is obtained and a warning is issued to the user based on the user information; When a response abnormal status signal is received, the corresponding user information is obtained, and a response failure warning is performed on the user based on the user information.

[0013] Compared with the prior art, the present invention has the following beneficial effects:

[0014] 1. The subcontracted data keys of the subcontracted key database are sequentially scheduled in the order of subcontracted data transmission to perform symmetrical encryption on the subcontracted data, and the subcontracted data keys are updated according to the subcontracted key database according to the transmission update cycle; and the latest subcontracted data keys are obtained by symmetrical encryption according to the coding order, and the latest subcontracted data keys are concatenated to generate a response key according to the coding order; further, the subcontracted data is updated to improve the security of the subcontracted data transmission; and the pre-response request data is subcontracted for data transmission to improve the speed of data transmission.

[0015] 2. The present invention sets management information data through a management platform, generates a request instruction according to the management information data and sends it to the process data acquisition module, and collects the request data corresponding to the server according to the request instruction; uses the data preprocessing unit set by the data processing module to preprocess the request data to obtain pre-response request data; and then encrypts it through the transmission encryption model set by the transmission encryption unit to obtain a response key; and then the response sending module responds to the request data to be responded to the corresponding client according to the client information, and obtains the abnormal status signal according to the response key; and then the monitoring and early warning module monitors the abnormal status signal, effectively improving the security of internal server data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction to the drawings required for use in the embodiments will be given below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0017] Figure 1 This is a system principle diagram of the present invention.

[0018] Figure 2 This is a flow chart of obtaining a response key according to the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0020] like Figure 1 As shown, an artificial intelligence-based server data full-process monitoring system includes a management platform connected to a process data acquisition module, a data processing module, a response sending module, and a monitoring and early warning module; The management platform is provided with management information data for generating a request instruction according to the management information data, wherein the management information data includes client information and user information; The process data acquisition module is used to collect the request data corresponding to the server according to the request instruction; The data processing module is provided with a data preprocessing unit and a transmission encryption unit; the data preprocessing unit is provided with a preprocessing strategy for preprocessing the request data according to the preprocessing strategy to obtain pre-response request data; the transmission encryption unit is provided with a transmission encryption model, and the pre-response request data is encrypted according to the transmission encryption model to obtain a response key; The response sending module is used to respond to the request data to be responded to the corresponding client according to the client information, and obtain the abnormal status signal according to the response key; The monitoring and early warning module is used to monitor abnormal status signals.

[0021] It should be further explained that the management platform is provided with management information data and generates a request instruction according to the management information data; including: Setting the internal network environment corresponding to the server, wherein the internal network environment includes the internal network and the client address range; The client information includes the client network, IP address and specific port; the user information includes basic personal information and internal information; the basic personal information includes name and ID number; the internal information includes department type, position type and position code; Mark clients whose client networks and IP addresses fall within the internal network and client address ranges corresponding to the internal network environment as authorized clients; and perform graded authorization on basic personal information based on internal information, marking them as graded authorized users; the graded authorized users include at least first-level authorized users, second-level authorized users, and third-level authorized users; and then set the request content range corresponding to the graded authorized users; In the above embodiment, it should be further explained that the client network includes but is not limited to parameters such as a subnet mask and a gateway address; the level of authorized users is determined based on internal information; the higher the level, the smaller the authorization scope; further, the first-level authorized user is greater than the second-level authorized user, which is greater than the third-level authorized user, and so on; The authorized client sends a request instruction through a specific port; the request instruction includes a request time, a keyword, and a request data type; the request data type includes at least a file, a table, and an image; and the request instruction is connected with the corresponding client information; and then sent to the process data acquisition module; In the above embodiment, it should be further explained that the keywords include but are not limited to content keywords, department keywords, name keywords, etc.; It should be further explained that the process data acquisition module acquires the request data corresponding to the server according to the request instruction; including: The server obtains the keywords and request data types corresponding to each request instruction, filters the type content corresponding to the authorized client according to the request data type, and then retrieves the key content corresponding to the type content according to the keyword and marks it as the request data; In the above embodiment, it needs to be further explained that a wide range of contents are screened according to the requested data type, and then the screened contents are searched according to keywords to obtain the requested data.

[0022] It should be further explained that the data preprocessing unit is provided with a preprocessing strategy, and preprocesses the request data according to the preprocessing strategy to obtain pre-response request data; including: The preprocessing strategy is used to number the request data corresponding to a specific port, denoted as i, where i=1, 2, ..., j; and j is a positive integer; then split each request data into subject content and data content; open the subject content; set the sub-packet data capacity, sub-packetize the data content according to the sub-packet data capacity, obtain all sub-packet data corresponding to the data content, and number them, denoted as n, where n=1, 2, ..., m; and m is a positive integer; then encode the sub-packet data, denoted as in; In the above embodiment, it should be further explained that the subject content includes but is not limited to a subject, a department, an enterprise, etc.; The corresponding request data is encrypted according to the sub-packet data encoding to generate the corresponding encryption code, which is recorded as TLkininin...; where T represents the request time; Lk represents the number K corresponding to the request data type L; The encryption code is concatenated with the corresponding request data to generate pre-response request data.

[0023] In the above embodiment, it needs to be further explained that, for example, the subpacket data m=3 corresponding to the request data of the first request data type of image L1 at the request time of 12:21, then n=1, 2, 3, and the corresponding encryption code is 12:21L1111213; the request data is first encrypted at the first layer according to the encryption code to ensure the authenticity and integrity of the data; at the same time, the request data is subpacketized for data transmission process, which reduces the additional processing links of the data during the transmission process and improves the efficiency and stability of data transmission.

[0024] like Figure 2 As shown, it needs to be further explained that the transmission encryption unit is provided with a transmission encryption model, and the pre-response request data is encrypted according to the transmission encryption model to obtain a response key; including: Setting a server interface transmission rule, wherein the server interface transmission rule is used to encrypt the sub-package data according to the encryption code of the pre-response request data and in the coding order corresponding to the encryption code to obtain a response key, and transmit it to the corresponding specific port in sequence to generate a transmission encryption model; The process of obtaining the response key includes: Step S1: Set up a sub-contract key database, schedule different sub-contract data keys in the sub-contract key database according to the sub-contract data transmission sequence, perform symmetrical encryption on the sub-contract data in sequence, and obtain the initial sub-contract data key; Step S2: Setting a transmission update period, and updating the initial sub-package data key according to the sub-package data key in the sub-package key database according to the transmission update period to obtain the latest sub-package data key; Step S3: The latest sub-packet data key transmitted to the specific port is connected according to the sub-packet data transmission sequence to generate a response key.

[0025] In the above embodiment, it needs to be further explained that the subpackage key database contains several different subpackage data keys; the subpackage data keys of the subpackage key database are scheduled in sequence according to the subpackage data transmission order to perform symmetric encryption on the subpackage data, and the subpackage data keys are updated according to the subpackage key database according to the transmission update cycle; it needs to be further explained that the updated latest subpackage data keys are different; for example, the encryption codes are 12:21L1111213 and 12:21L121222324 corresponding to the pre-response request data; according to the coding order, the subpackage data is transmitted in the coding order of 1-1, 1-2, 1-3, 2-1, 2-1, 2-3 and 2-4, and symmetric encryption is performed in the coding order to obtain the latest subpackage data key, and the latest subpackage data keys are recently connected according to the coding order to generate a response key; further, the subpackage data is updated to improve the security of subpackage data transmission; subpackage data transmission of the pre-response request data is performed to improve the speed of data transmission.

[0026] It should be further explained that the response sending module is used to respond to the request data to be responded to the corresponding client according to the client information, and obtain the abnormal status signal according to the response key; including: The client receives several pre-response request data and selects the corresponding pre-response request data according to the subject content; then inputs the corresponding user information and determines whether the subject content meets the request content range of the user authorized by the corresponding level of the user information; if it meets the range, the client obtains the corresponding encryption code and obtains the pre-response request data according to the encryption code; otherwise, a user abnormal status signal is generated; Input the response password for the pre-response request data and determine whether it matches. If it matches, obtain the request data; otherwise, generate a response abnormal status signal.

[0027] In the above embodiment, it needs to be further explained that this process avoids the usual query of the requested data and the direct viewing and modification of the requested data according to the user information; the double encryption effectively improves the security of the requested data.

[0028] It should be further explained that the monitoring and early warning module monitors abnormal status signals, including: Upon receiving a user abnormal status signal, the corresponding user information is obtained and a warning is issued to the user based on the user information; When a response abnormal status signal is received, the corresponding user information is obtained, and a response failure warning is performed on the user based on the user information.

[0029] The features and exemplary embodiments of various aspects of the present application are described in detail above. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The above description of the embodiments is merely to provide a better understanding of the present application by showing examples of the present application.

[0030] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An artificial intelligence-based server data full-process monitoring system, including a management platform, characterized in that: The management platform is connected to a process data acquisition module, a data processing module, a response sending module and a monitoring and early warning module; The management platform is provided with management information data for generating a request instruction according to the management information data, wherein the management information data includes client information and user information; The process data acquisition module is used to collect the request data corresponding to the server according to the request instruction; The data processing module is provided with a data preprocessing unit and a transmission encryption unit; the data preprocessing unit is provided with a preprocessing strategy for preprocessing the request data according to the preprocessing strategy to obtain pre-response request data; the transmission encryption unit is provided with a transmission encryption model, and the pre-response request data is encrypted according to the transmission encryption model to obtain a response key; The response sending module is used to respond to the request data to be responded to the corresponding client according to the client information, and obtain the abnormal status signal according to the response key; The monitoring and early warning module is used to monitor abnormal status signals.

2. The artificial intelligence-based server data full-process monitoring system according to claim 1 is characterized in that: The process of setting management information data on the management platform includes: Setting the internal network environment corresponding to the server, wherein the internal network environment includes the internal network and the client address range; The client information includes the client network, IP address and specific port; the user information includes basic personal information and internal information; The client whose network and IP address belong to the internal network and client address range corresponding to the internal network environment is marked as an authorized client; and the basic personal information is graded and authorized according to the internal information, and marked as a graded authorized user; and then the request content range corresponding to the graded authorized user is set.

3. The artificial intelligence-based server data full-process monitoring system according to claim 2 is characterized in that: The process of generating a request instruction based on management information data includes: The client is authorized to send a request instruction through a specific port; the request instruction includes a request time, a keyword request data type; the request instruction is connected with the corresponding client information and sent to the process data acquisition module.

4. The artificial intelligence-based server data full-process monitoring system according to claim 3 is characterized in that: The process of the process data acquisition module acquiring the request data corresponding to the server according to the request instruction includes: The server obtains the keywords and request data types corresponding to each request instruction, filters the type content corresponding to the authorized client according to the request data type, and then retrieves the key content corresponding to the type content according to the keyword and marks it as request data.

5. The artificial intelligence-based server data full-process monitoring system according to claim 4 is characterized in that: The process of the data preprocessing unit setting the preprocessing strategy includes: The preprocessing strategy is used to number the request data corresponding to a specific port, denoted as i, where i=1, 2, ..., j; and j is a positive integer; then split each request data into subject content and data content; open the subject content; set the subpacket data capacity, subpacketize the data content according to the subpacket data capacity, obtain all subpacket data corresponding to the data content, and number them, denoted as n, where n=1, 2, ..., m; and m is a positive integer; then encode the subpacket data, denoted as in.

6. The artificial intelligence-based server data full-process monitoring system according to claim 5 is characterized in that: The process of obtaining pre-response request data includes: The corresponding request data is encrypted according to the sub-packet data encoding to generate the corresponding encryption code, which is recorded as TLkininin...; where T represents the request time; Lk represents the number K corresponding to the request data type L; The encryption code is concatenated with the corresponding request data to generate pre-response request data.

7. The artificial intelligence-based server data full-process monitoring system according to claim 6 is characterized in that: The process of the transmission encryption unit setting the transmission encryption model includes: Set a server interface transmission rule, which is used to encrypt the subpackage data according to the encryption code of the pre-response request data and the corresponding coding order of the encryption code to obtain the response key, and transmit it to the corresponding specific port in sequence to generate a transmission encryption model.

8. The artificial intelligence-based server data full-process monitoring system according to claim 7 is characterized in that: The process of obtaining a response key includes: Step S1: Set up a sub-contract key database, schedule different sub-contract data keys in the sub-contract key database according to the sub-contract data transmission sequence, perform symmetrical encryption on the sub-contract data in sequence, and obtain the initial sub-contract data key; Step S2: Setting a transmission update period, and updating the initial sub-package data key according to the sub-package data key in the sub-package key database according to the transmission update period to obtain the latest sub-package data key; Step S3: The latest sub-packet data key transmitted to the specific port is connected according to the sub-packet data transmission sequence to generate a response key.

9. The artificial intelligence-based server data full-process monitoring system according to claim 8, characterized in that: The process of the response sending module acquiring the abnormal status signal includes: The client receives several pre-response request data and selects the corresponding pre-response request data according to the subject content; then inputs the corresponding user information and determines whether the subject content meets the request content range of the user authorized by the corresponding level of the user information; if it meets the range, the client obtains the corresponding encryption code and obtains the pre-response request data according to the encryption code; otherwise, a user abnormal status signal is generated; Input the response password for the pre-response request data and determine whether it matches. If it matches, obtain the request data; otherwise, generate a response abnormal status signal.

10. The artificial intelligence-based server data full-process monitoring system according to claim 9, characterized in that: The process of the monitoring and early warning module monitoring abnormal status signals includes: Upon receiving a user abnormal status signal, the corresponding user information is obtained and a warning is issued to the user based on the user information; When a response abnormal status signal is received, the corresponding user information is obtained, and a response failure warning is performed on the user based on the user information.

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