Data processing method and terminal based on distributed virtual simulation

Abstract

The invention discloses a distributed virtual simulation-based data processing method and a terminal. The method comprises the following steps of: establishing an analysis virtual machine in a distributed system; obtaining target data, and controlling the analysis virtual machine to carry out risk detection on the target data according to a system preset detection rule and a user preset detection rule; and according to a risk detection result, judging whether the target data enters a circulation process, if so, judging whether the target data accords with a preset trust data matching rule of the corresponding user node, and if so, receiving the target data by the user node. According to the invention, the target data is isolated from the main system by means of virtual simulation, the data uploaded to the system is accurately identified, multiple checkout of transferring the target data to the user node in the system is completed, the user node is ensured to accurately receive reliable data, and the security and specificity of the data are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed data interaction, and in particular to a distributed virtual simulation data processing method and terminal. Background Art

[0002] The design and implementation of distributed systems are relatively complex, and they need to deal with multiple issues such as communication between nodes, data consistency, and fault recovery. This complexity increases the difficulty of system development and maintenance. As the number of users continues to grow and the data components become more complex, the scale of data transmitted on the system becomes larger and larger; distributed systems require large-scale processing and identification, which greatly increases the difficulty of the system to identify and manage risk data. In addition, different user nodes have different requirements for the data they receive. While effectively identifying risk data, it is also necessary to meet the data requirements of user nodes and ensure normal data flow functions. Summary of the invention

[0003] The technical problem to be solved by the present invention is to propose a distributed virtual simulation data processing method and terminal to meet the user's data flow needs while performing data risk control and improving the security and specificity of the data.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] A distributed virtual simulation data processing method comprises the following steps:

[0006] S1. Establish a parsing virtual machine in a distributed system;

[0007] S2. Obtain target data, and control the analysis virtual machine to perform risk detection on the target data according to system preset detection rules and user preset detection rules;

[0008] S3. According to the result of the risk detection, determine whether the target data enters the circulation process. If so, execute step S4;

[0009] S4. Determine whether the target data meets the preset trust data matching rule of the corresponding user node. If so, the user node receives the target data.

[0010] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0011] A distributed virtual simulation data processing terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0012] S1. Establish a parsing virtual machine in a distributed system;

[0013] S2. Obtain target data, and control the analysis virtual machine to perform risk detection on the target data according to system preset detection rules and user preset detection rules;

[0014] S3. According to the result of the risk detection, determine whether the target data enters the circulation process. If so, execute step S4;

[0015] S4. Determine whether the target data meets the preset trust data matching rule of the corresponding user node. If so, the user node receives the target data.

[0016] The beneficial effects of the present invention are: providing a distributed virtual simulation data processing method and terminal, providing a completely isolated operating environment by establishing an analytical virtual machine, effectively avoiding some security risks, and parsing the target data in the environment, completing risk detection in combination with system preset detection rules and user preset detection rules, identifying and filtering certain data, and then determining when the user node receives the target data based on the processing flow configured by the user node, relying on virtual simulation to isolate the target data from the main system, accurately identifying the data uploaded to the system, completing multiple checks on the target data from the flow within the system to the user node, ensuring that the user node accurately receives reliable data, and improving the security and specificity of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of the steps of a distributed virtual simulation data processing method of the present invention;

[0018] Figure 2 A flowchart of a distributed virtual simulation data processing method according to an embodiment of the present invention;

[0019] Figure 3 A schematic diagram of data type identification and storage based on a distributed virtual simulation data processing method according to an embodiment of the present invention;

[0020] Figure 4 The system block diagram of the present invention is based on a distributed virtual simulation data processing terminal.

[0021] Description of labels:

[0022] 1. A distributed virtual simulation data processing terminal; 2. Memory; 3. Processor. DETAILED DESCRIPTION

[0023] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0024] Please refer to Figures 1 to 3 , a distributed virtual simulation data processing method, comprising the following steps:

[0025] S1. Establish a parsing virtual machine in a distributed system;

[0026] S2. Obtain target data, and control the analysis virtual machine to perform risk detection on the target data according to system preset detection rules and user preset detection rules;

[0027] S3. According to the result of the risk detection, determine whether the target data enters the circulation process. If so, execute step S4;

[0028] S4. Determine whether the target data meets the preset trust data matching rule of the corresponding user node. If so, the user node receives the target data.

[0029] From the above description, it can be seen that the beneficial effects of the present invention are: by establishing a parsing virtual machine to provide a completely isolated operating environment, some security risks are effectively avoided, and the target data is parsed in this environment, risk detection is completed in combination with system preset detection rules and user preset detection rules, certain data is identified and filtered, and then the user node is determined to receive the target data based on the processing flow configured by the user node, the target data is isolated from the main system by relying on virtual simulation, the data uploaded to the system is accurately identified, and multiple checks are completed on the target data from the flow within the system to the user node, ensuring that the user node accurately receives reliable data and improving the security and specificity of the data.

[0030] Furthermore, the step S1 further includes:

[0031] Storing different types of data on the parsing virtual machine, and setting corresponding system preset detection rules and user preset detection rules for each type of data;

[0032] The step S2 is specifically as follows:

[0033] The parsing virtual machine is controlled to identify the data type of the target data, and the corresponding system preset detection rule and the user preset detection rule are called according to the data type of the target data to perform risk detection on the target data.

[0034] From the above description, it can be seen that by parsing different types of data pre-stored on the virtual machine and setting corresponding system preset detection rules and user preset detection rules for each data type, when parsing the target data, the corresponding risk detection rules are selected according to the target data type to achieve accurate and targeted detection, and it is highly configurable to meet the different needs of the system and users.

[0035] Furthermore, the different types of data stored on the parsing virtual machine are specifically:

[0036] A data type memory is provided on the parsing virtual machine, and different types of data type features are stored in the data type memory, wherein the data type features correspond to the data types in a one-to-one manner.

[0037] It can be seen from the above description that when different types of data are pre-stored, they are stored specifically according to the data type characteristics of the different data types, thereby improving recognition accuracy.

[0038] Furthermore, after the user node receives the target data, the method further includes:

[0039] The risk detection result corresponding to the target data is sent to the user node, so that the user node can adjust the corresponding user preset detection rule.

[0040] From the above description, it can be seen that when the user node obtains the target data, the risk detection result of the target data is also sent to the user, so that the user can adjust the user preset detection rules as needed, making the data flow more reasonable and flexible.

[0041] Furthermore, the step S4 is specifically as follows:

[0042] The node virtual machine corresponding to the user node is controlled to match the target data according to the corresponding trusted data matching rule. If the match is successful, the user node receives and processes the target data.

[0043] From the above description, it can be seen that a node virtual machine is established on the user node, and the trusted data matching rules are used in the node virtual machine to match the target data, thereby establishing a transmission interaction between the user node and the trusted data, thereby improving the security and specificity of the data.

[0044] Please refer to Figure 4 A distributed virtual simulation data processing terminal 1 includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, the following steps are implemented:

[0045] S1. Establish a parsing virtual machine in a distributed system;

[0046] S2. Obtain target data, and control the analysis virtual machine to perform risk detection on the target data according to system preset detection rules and user preset detection rules;

[0047] S3. According to the result of the risk detection, determine whether the target data enters the circulation process. If so, execute step S4;

[0048] S4. Determine whether the target data meets the preset trust data matching rule of the corresponding user node. If so, the user node receives the target data.

[0049] From the above description, it can be seen that the beneficial effects of the present invention are: by establishing a parsing virtual machine to provide a completely isolated operating environment, some security risks are effectively avoided, and the target data is parsed in this environment, risk detection is completed in combination with system preset detection rules and user preset detection rules, certain data is identified and filtered, and then the user node is determined to receive the target data based on the processing flow configured by the user node, the target data is isolated from the main system by relying on virtual simulation, the data uploaded to the system is accurately identified, and multiple checks are completed on the target data from the flow within the system to the user node, ensuring that the user node accurately receives reliable data and improving the security and specificity of the data.

[0050] Furthermore, the step S1 further includes:

[0051] Storing different types of data on the parsing virtual machine, and setting corresponding system preset detection rules and user preset detection rules for each type of data;

[0052] The step S2 is specifically as follows:

[0053] The parsing virtual machine is controlled to identify the data type of the target data, and the corresponding system preset detection rule and the user preset detection rule are called according to the data type of the target data to perform risk detection on the target data.

[0054] From the above description, it can be seen that by parsing different types of data pre-stored on the virtual machine and setting corresponding system preset detection rules and user preset detection rules for each data type, when parsing the target data, the corresponding risk detection rules are selected according to the target data type to achieve accurate and targeted detection, and it is highly configurable to meet the different needs of the system and users.

[0055] Furthermore, the different types of data stored on the parsing virtual machine are specifically:

[0056] A data type memory is provided on the parsing virtual machine, and different types of data type features are stored in the data type memory, wherein the data type features correspond to the data types in a one-to-one manner.

[0057] It can be seen from the above description that when different types of data are pre-stored, they are stored specifically according to the data type characteristics of the different data types, thereby improving recognition accuracy.

[0058] Furthermore, after the user node receives the target data, the method further includes:

[0059] The risk detection result corresponding to the target data is sent to the user node, so that the user node can adjust the corresponding user preset detection rule.

[0060] From the above description, it can be seen that when the user node obtains the target data, the risk detection result of the target data is also sent to the user, so that the user can adjust the user preset detection rules as needed, making the data flow more reasonable and flexible.

[0061] Furthermore, the step S4 is specifically as follows:

[0062] The node virtual machine corresponding to the user node is controlled to match the target data according to the corresponding trusted data matching rule. If the match is successful, the user node receives and processes the target data.

[0063] From the above description, it can be seen that a node virtual machine is established on the user node, and the trusted data matching rules are used in the node virtual machine to match the target data, thereby establishing a transmission interaction between the user node and the trusted data, thereby improving the security and specificity of the data.

[0064] Please refer to Figures 1 to 3 , Embodiment 1 of the present invention is:

[0065] A distributed virtual simulation data processing method, such as Figure 1 and Figure 2 As shown, the following steps are included:

[0066] S1. Establish a parsing virtual machine in a distributed system, store different types of data on the parsing virtual machine, and set corresponding system preset detection rules and user preset detection rules for each data type;

[0067] In this embodiment, if Figure 3 As shown, a data type memory is set on the parsing virtual machine, and different data type features are stored in the data type memory. The data type features correspond to the data types one by one. Different data types will be parsed with the corresponding data type features. For example, DOC cannot be parsed by notepad, and it is garbled when parsed. Another example is type disguise: the type is disguised, the executable program is disguised as JPG format to trick users into downloading, and the user is tricked into running after modifying the suffix. Regarding data type features, examples are as follows:

[0068] 1. Suffix-type characteristics such as: TXT-establish corresponding regional data (because the data encoding of each country is slightly different, the default format is UNICODE) (letters, numbers, punctuation marks, etc.) and there is no binary data, it is a text file.

[0069] 2. If there is binary data, obtain the binary data part and convert it into 16-HEX data, and enter other types of feature interval comparison until a match is found, otherwise it is marked as unknown. HEX is an ASCI text file composed of lines of text that conform to the InteI HEX file format; for example, in HEX, "47, 49, 46, 18, 39, 61, 14.....GIF89A...." appears; this line of data, 47 49 46 is the image GIF feature, and for another example: when a text is merged with an image, half of the data is text and the other half is image, so it needs to be segmented by feature.

[0070] In addition, the data type storage format is also set on the parsing virtual machine. Corresponding to the above example, the storage format of the binary text file is: TXT-data features such as: GIF-474946.

[0071] It should be noted that the identification of data types is only one part of the virtual identification of parsing. The data type is determined according to the format feature process. The role of the virtual machine of parsing is to let users know: what is in the file, that is, the file components; what the file type is, such as mp3, txt, exe, dll and other types of files; what its behavior is, such as whether it disguises the above files; what type of file it is, such as whether it has a signature, exedll and other digital signatures, mp3 / mp4 refers to copyright signatures, and different types have different attribute parsing solutions. Moreover, even if the determined data type is not found in the format feature process, it will also enter the next step of risk detection.

[0072] S2. Obtain target data and control the parsing virtual machine to perform risk detection on the target data according to system preset detection rules and user preset detection rules;

[0073] In this embodiment, the control parsing virtual machine identifies the data type of the target data, and calls the corresponding system preset detection rules and user preset detection rules according to the data type of the target data to perform risk detection on the target data. Among them, the system preset detection rules are the system's own analysis and control rules for the target data, for example:

[0074] 1. Data type-risk control: File format exe-risk control, such as the distributed program with file format exe must have a digital signature;

[0075] 2. Audio file: mp3 - can only store songs of a certain singer.

[0076] The user-preset detection rules are the user's own control rules for the target data, for example:

[0077] 1. The degree of trust in the data, for example: only trusting audio files, only accepting data with corresponding data signatures, etc.

[0078] 2. Processing of additional data: When the parsing virtual machine detects that the target data contains multiple files, and some of the files do not comply with the control rules of the user node, the target data is listed and released to the client, waiting for the user node to authorize the operation.

[0079] S3. According to the result of risk detection, determine whether the target data enters the circulation process. If so, execute step S4;

[0080] In this embodiment, the risk detection results may include at least the following four situations:

[0081] 1. If the target data meets both the system preset detection rules and the user preset detection rules, it means that the target data does not have risks and can enter the circulation process;

[0082] 2. If the target data meets the system preset detection rules but does not meet the user preset detection rules, it means that the target data is not accepted by the corresponding user node and cannot enter the circulation process;

[0083] 3. If the target data does not meet the system preset detection rules, but meets the user preset detection rules, it means that the user node may have special receiving requirements for the data. It can enter the flow process, but the user node needs to be informed of the risk that the target data does not meet the system preset detection rules.

[0084] 4. If the target data does not meet the system preset detection rules and the user preset detection rules, it means that the target data is risky and will not enter the circulation process, but will be filtered out;

[0085] S4. Determine whether the target data meets the preset trust data matching rules of the corresponding user node. If so, the user node receives the target data; and, when dealing with the above situation 3, send the risk detection result of the corresponding target data to the user node so that the user node can adjust the corresponding user preset detection rules.

[0086] In this embodiment, the node virtual machine corresponding to the user node is controlled to match the target data according to the corresponding trusted data matching rule. If the match is successful, the user node receives and processes the target data.

[0087] On the node virtual machine corresponding to the user node, the trusted data matching rules are stored to indicate the degree of trust of the user node on the target data, such as trust in audio / video files, trust in image files, or trust in other types of files; and when considering whether to receive the target data, the trusted data matching rules are used for matching. For example:

[0088] 1. Trust the audio and match the audio file

[0089] 2. Perform virtual machine operations on trusted type files to prevent data from spreading in disguised formats.

[0090] Please refer to Figure 4 , Embodiment 2 of the present invention is:

[0091] A distributed virtual simulation data processing terminal 1 includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, a distributed virtual simulation data processing method as described in Example 1 is implemented.

[0092] To summarize, the present invention provides a distributed virtual simulation data processing method and terminal, which provides a completely isolated operating environment by establishing an analytical virtual machine, effectively avoiding some security risks, and analyzing the target data in the environment, and completes risk detection in combination with system preset detection rules and user preset detection rules, identifies and filters certain data, and then determines when the user node receives the target data based on the processing flow configured by the user node, relies on virtual simulation to isolate the target data from the main system, accurately identifies the data uploaded to the system, and completes multiple checks on the target data from the flow within the system to the user node, ensuring that the user node accurately receives reliable data and improving the security and specificity of the data.

[0093] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A distributed virtual simulation data processing method, characterized in that: The steps include: S1. Establish a parsing virtual machine in a distributed system; S2. Obtain target data, and control the analysis virtual machine to perform risk detection on the target data according to system preset detection rules and user preset detection rules; S3. According to the result of the risk detection, determine whether the target data enters the circulation process. If so, execute step S4; S4. Determine whether the target data meets the preset trust data matching rule of the corresponding user node. If so, the user node receives the target data.

2. A distributed virtual simulation data processing method according to claim 1, characterized in that: The step S1 further comprises: Storing different types of data on the parsing virtual machine, and setting corresponding system preset detection rules and user preset detection rules for each type of data; The step S2 is specifically as follows: The parsing virtual machine is controlled to identify the data type of the target data, and the corresponding system preset detection rule and the user preset detection rule are called according to the data type of the target data to perform risk detection on the target data.

3. A distributed virtual simulation data processing method according to claim 2, characterized in that: The different types of data stored on the parsing virtual machine are specifically: A data type memory is provided on the parsing virtual machine, and different types of data type features are stored in the data type memory, wherein the data type features correspond to the data types in a one-to-one manner.

4. A distributed virtual simulation data processing method according to claim 1, characterized in that: After the user node receives the target data, the method further includes: The risk detection result corresponding to the target data is sent to the user node, so that the user node can adjust the corresponding user preset detection rule.

5. The method for processing data based on distributed virtual simulation according to claim 1, characterized in that: The step S4 is specifically as follows: The node virtual machine corresponding to the user node is controlled to match the target data according to the corresponding trusted data matching rule. If the match is successful, the user node receives and processes the target data.

6. A distributed virtual simulation data processing terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: S1. Establish a parsing virtual machine in a distributed system; S2. Obtain target data, and control the analysis virtual machine to perform risk detection on the target data according to system preset detection rules and user preset detection rules; S3. According to the result of the risk detection, determine whether the target data enters the circulation process. If so, execute step S4; S4. Determine whether the target data meets the preset trust data matching rule of the corresponding user node. If so, the user node receives the target data.

7. A distributed virtual simulation data processing terminal according to claim 6, characterized in that: The step S1 further comprises: Storing different types of data on the parsing virtual machine, and setting corresponding system preset detection rules and user preset detection rules for each type of data; The step S2 is specifically as follows: The parsing virtual machine is controlled to identify the data type of the target data, and the corresponding system preset detection rule and the user preset detection rule are called according to the data type of the target data to perform risk detection on the target data.

8. A distributed virtual simulation data processing terminal according to claim 7, characterized in that: The different types of data stored on the parsing virtual machine are specifically: A data type memory is provided on the parsing virtual machine, and different types of data type features are stored in the data type memory, wherein the data type features correspond to the data types in a one-to-one manner.

9. A distributed virtual simulation data processing terminal according to claim 6, characterized in that: After the user node receives the target data, the method further includes: The risk detection result corresponding to the target data is sent to the user node, so that the user node can adjust the corresponding user preset detection rule.

10. The distributed virtual simulation data processing terminal according to claim 6, characterized in that: The step S4 is specifically as follows: The node virtual machine corresponding to the user node is controlled to match the target data according to the corresponding trusted data matching rule. If the match is successful, the user node receives and processes the target data.

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