An internet platform monitoring data transmission exchange method and system

Abstract

The application discloses an internet platform monitoring data transmission exchange method and system, belongs to the technical field of data transmission, and aims to solve the problem of information verification in the internet platform monitoring data transmission exchange process; the method comprises a verification module, an encryption module, a data monitoring module, a server and a storage module; the verification module is used for information verification of data transmission parties, and the specific method comprises the following steps: an information verification library is established, the information verification library is used for storing user information needing to be monitored for data transmission, a username list for data transmission is set, a fake-proof mark is set on the corresponding user information, a fake-proof identification end for verification when the user information is received by the other party is set on the user information, and through the setting of the verification module, identity verification of the data transmission parties can be performed, data transmission errors and receiving errors are avoided, a large amount of useless data caused by receiving errors is avoided, and unnecessary troubles caused by the operation of the work are avoided.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of data transmission, and particularly relates to an internet platform monitoring data transmission exchange method and system. BACKGROUND

[0002] Internet, also known as international network, refers to a huge network formed by connecting networks with each other, and the networks are connected with each other through a group of common protocols to form a single huge international network in logic. In the process of internet platform monitoring data transmission exchange, information verification of both exchange parties is needed to avoid data transmission errors and receiving errors, because when receiving errors occur, a large amount of useless data will be generated, which brings unnecessary troubles to the operation of work, and if information verification is not performed, the loophole will be easily used by illegal persons to attack users, which has great security risks. SUMMARY

[0003] The application aims to provide an internet platform monitoring data transmission exchange method and system, and solve the problem of information verification in the process of internet platform monitoring data transmission exchange.

[0004] The application can be realized by the following technical scheme.

[0005] An internet platform monitoring data transmission exchange system comprises a verification module, an encryption module, a server and a storage module; the verification module is used for information verification of both data transmission parties, and the specific method comprises the following steps: an information verification library is established, the information verification library is used for storing user information of monitored data transmission, a user list for monitored data transmission is set, a false-proof mark is set on the corresponding user information, a false-proof identification end for verification when data is received by the other party is set on the user information, the user list is sent to the information verification library for storage, when a user needs to send monitored data, a false-proof identification end for receiving monitored data is acquired, the acquired false-proof identification end is set on the user information, when a user sends monitored data, user information and the corresponding false-proof identification end are acquired, the acquired user information is matched with the user information in the information verification library, when no matching is successful, the received monitored data is not received; when the matching is successful, the corresponding false-proof mark is obtained, the acquired false-proof identification end is verified through the false-proof mark, when the verification fails, the received monitored data is not received; when the verification succeeds, the monitored data sent by the corresponding user is received.

[0006] Further, the method for setting the anti-fake mark comprises: establishing an anti-fake model, the anti-fake model comprising a plurality of verification rings and a verification center, the verification rings being provided with delay blocks, the verification center being provided with a signal receiving block, and a rotating speed adjusting unit being arranged, the rotating speed adjusting unit being used for setting the rotating speeds of each verification ring and the verification center, when the anti-fake mark needs to be set, the rotating speed adjusting unit randomly generates the rotating speeds of the verification rings and the verification center, and generates a rotating speed statistical table, the verification rings and the verification center start to rotate, when the rotating speeds are set, the anti-fake model generates a corresponding anti-fake mark, an anti-fake identification end is set according to the rotating speed statistical table, the anti-fake identification end sends a plurality of verification signals according to the rotating speeds of the verification rings and the verification center and the delay time t of the delay blocks, when the verification signals are received by the delay blocks, the verification rings stop rotating for t seconds, the remaining verification signals pass through the corresponding delay blocks, the verification rings rotate again after t seconds, the corresponding delay blocks no longer receive the verification signals in this verification process, and when the remaining verification signals hit the verification rings or the delay blocks, the verification fails; the verification signals passing through the delay blocks verify the next verification ring, and when the verification signals passing through all the verification rings are received by the signal receiving block arranged on the verification center, the verification succeeds.

[0007] Further, the encryption module is used for encrypting the transmitted monitoring data, and the specific method comprises the following steps: identifying the data type and the encryption mark, not performing encryption when no encryption mark is identified, performing encryption when the encryption mark is identified, when the data type is non-text, creating a new folder, moving the non-text data into the new folder, performing zip compression, performing encryption after compression, and transmitting the encrypted folder; when the data type is text, setting a password library for storing password symbols, obtaining monitoring data, setting a segmentation model, inputting the monitoring data into the segmentation model for segmentation, obtaining a plurality of data segments, inputting the data segments into the password library for matching, obtaining corresponding password symbols, and transmitting the password symbols; both parties for transmitting the detection data are provided with decryption units for real-time password updating of the monitoring data receiving party.

[0008] Further, the method for establishing the segmentation model comprises the following steps: obtaining a plurality of groups of historical segmentation data, the historical segmentation data being monitoring data, setting a preset segmentation condition for providing a segmentation basis for data segmentation, constructing an artificial intelligence model, inputting the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, dividing the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a verification set according to a set proportion; the set proportion comprises 4:2:1, 4:3:1 and 3:2:2; training, testing and verifying the artificial intelligence model through the training set, the test set and the verification set, and marking the trained artificial intelligence model as a segmentation model.

[0009] An internet platform monitoring data transmission exchange method, the specific method comprises:

[0010] Step one: identify data type and encryption mark, encrypt data that needs to be encrypted;

[0011] Step two: before data transmission, information verification is carried out between data transmission parties;

[0012] Step three: monitoring data transmission is carried out;

[0013] Step four: the sent monitoring data is monitored.

[0014] The beneficial effects of the present application are: by establishing an information verification library, setting a user list for monitoring data transmission, setting an anti-fake mark on the corresponding user information, the anti-fake mark is used for verifying the user information of the sent monitoring data, and an anti-fake identification end is set on the user information for verification when the other party receives data, so that the monitoring data transmission parties can carry out identity verification, avoid data transmission errors and receiving errors, avoid a large amount of useless data generated when receiving errors, and unnecessary trouble and danger to the operation of work; by identifying data type and encryption mark, when no encryption mark is identified, no encryption is carried out; when the encryption mark is identified, encryption operation is carried out, the transmission data is encrypted, and the confidentiality of the monitoring data is ensured. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0016] Fig. 1 It is a principle diagram of the present application;

[0017] Fig. 2 It is a schematic diagram of the anti-fake model of the present application. DETAILED DESCRIPTION

[0018] The technical solutions of the present application will be described below in conjunction with the embodiments, obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0019] As Figs. 1-2As shown, an Internet platform monitoring data transmission exchange system includes a verification module, an encryption module, a data monitoring module, a server and a storage module;

[0020] The verification module is used for information verification of both parties of data transmission. The specific method includes: establishing an information verification library, the information verification library is used for storing user information of monitored data transmission, setting a user list of monitored data transmission, setting an anti-fake mark on the corresponding user information, the anti-fake mark is used for verifying the user information of the sent monitoring data, setting an anti-fake identification end on the user information for verification when the other party receives data, the anti-fake identification end is used for verifying the anti-fake mark; the user list is sent to the information verification library for storage, when a user needs to send monitoring data, the anti-fake identification end of the user receiving the monitoring data is obtained, the obtained anti-fake identification end is set on the user information, this user information is the user information of sending data, when a user sends monitoring data, the user information and the corresponding anti-fake identification end are obtained, the obtained user information is matched with the user information in the information verification library, when there is no matching success, the monitoring data is not received; when the matching is successful, the corresponding anti-fake mark is obtained, the obtained anti-fake identification end is verified through the anti-fake mark, when the verification fails, the monitoring data is not received; when the verification is successful, the monitoring data sent by the corresponding user is received;

[0021] Through the setting of the verification module, the identity verification of both parties of monitoring data transmission can be realized, the data transmission error and receiving error can be avoided, a large amount of useless data generated when the receiving error occurs is avoided, and unnecessary trouble is brought to the operation of work;

[0022] The method for setting the anti-fake mark comprises: establishing an anti-fake model, the anti-fake model comprising a plurality of verification rings and a verification center, the verification rings being provided with delay blocks, the delay blocks being used to pause the rotation of the verification rings for t seconds when a verification signal is received, t being a preset value which can be set by the user as required, the next verification signal directly passing through the delay blocks of the stopped verification rings within t seconds, the verification center being provided with a signal receiving block, a rotation speed adjusting unit being provided, the rotation speed adjusting unit being used to set the rotation speeds of each verification ring and the verification center, when the anti-fake mark needs to be set, the rotation speed adjusting unit randomly generates the rotation speeds of the verification rings and the verification center, the rotation speeds of each verification ring and the verification center can be the same or different, however, the rotation speeds of each verification ring and the verification center will not all be the same, and a rotation speed statistical table is generated, the verification rings and the verification center start to rotate, when the rotation speeds are set, the anti-fake model generates a corresponding anti-fake mark, the anti-fake mark being the verification rings and the verification center with the rotation speeds, and the delay blocks and the signal receiving block provided thereon, an anti-fake identification end is set according to the rotation speed statistical table, the anti-fake identification end sends a plurality of verification signals according to the rotation speeds of the verification rings and the verification center and the delay time t of the delay blocks, when a verification signal is received by the delay blocks, the verification rings stop rotating for t seconds, the remaining verification signals pass through the corresponding delay blocks, the verification rings rotate again after t seconds, the corresponding delay blocks no longer receive verification signals in this verification process, when the remaining verification signals hit the verification rings or the delay blocks, the verification fails; the verification signals passing through the delay blocks verify the next verification ring, until the verification signals passing through all the verification rings are received by the signal receiving block provided on the verification center, the verification succeeds;

[0023] The encryption module is used for encrypting the transmitted monitoring data, and the specific method comprises the following steps: identifying the data type and the encryption mark, the encryption mark being set by the user, the data type being what type of data, such as image type, text type, audio type and the like, and no encryption being performed when no encryption mark is identified; when the encryption mark is identified, an encryption operation is performed, when the data type is a non-text type, a new folder is created, the non-text type data is moved to the new folder, and then zip compression is performed, and after compression, encryption is performed, and the encrypted folder is transmitted; when the data type is a text type, a password library is set, the password library being used to store password symbols, the password symbols being randomly set, for example, a, ac, hu, 1d, -k and disclosure as and the like, the monitoring data is acquired, a segmentation model is set, the monitoring data is input into the segmentation model for segmentation, a plurality of data segments are obtained, the data segments are input into the password library for matching, corresponding password symbols are obtained, and the password symbols are transmitted; both parties for transmitting the detection data are provided with a decryption unit, the decryption password in the decryption unit is updated by the corresponding data transmission party, that is, the decryption password in the decryption unit of the other party is updated by our party, and the monitoring data receiving party is updated in real time;

[0024] The method for establishing the segmentation model comprises: obtaining a plurality of sets of historical segmentation data, the historical segmentation data being the monitoring data, setting a preset segmentation condition, the preset segmentation condition being used to provide a segmentation basis for data segmentation, for example, setting a sentence as the preset segmentation condition, and the segmentation data being segmented into "Guo" "some" "some" or "Guo" "some" according to the segmentation result of the sentence, constructing an artificial intelligence model, the artificial intelligence model comprising an error back propagation neural network, an RBF neural network and a deep convolutional neural network, inputting the plurality of sets of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, and dividing the plurality of sets of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a verification set according to a set proportion; the set proportion comprising 4:2:1, 4:3:1 and 3:2:2; training, testing and verifying the artificial intelligence model through the training set, the test set and the verification set, and marking the trained artificial intelligence model as a segmentation model.

[0025] The data monitoring module is used for monitoring the data receiving party to monitor the monitoring data in real time, and the specific method comprises: obtaining the monitoring data, the network working time length and the network working environment in real time, integrating and marking as input data, and obtaining a prediction model; inputting the input data into the prediction model to obtain an output result and marking as a prediction label, the prediction label being a state label corresponding to the input data;

[0026] The specific steps for obtaining the prediction model comprise: obtaining monitoring historical data; the monitoring historical data comprising the monitoring data, the network working time length and the network working environment; the network working time length comprising a link working time length and a device working time length, and the network working environment comprising temperature, humidity and wind speed; setting a state label for the monitoring historical data; the state label comprising 01 and 02, when the state label is 01, the monitoring data is normal, and when the state label is 02, the monitoring data is abnormal; constructing an artificial intelligence model; the artificial intelligence model comprising an error back propagation neural network, an RBF neural network and a deep convolutional neural network; dividing the monitoring historical data and the corresponding state label into a training set, a test set and a verification set according to a set proportion; the set proportion comprising 2:1:1, 3:2:1 and 3:2:1; training, testing and verifying the artificial intelligence model through the training set, the test set and the verification set; and marking the trained artificial intelligence model as a prediction model.

[0027] An internet platform monitoring data transmission exchange method, the specific method comprising:

[0028] Step one: identifying data types and encryption marks, and encrypting data that needs to be encrypted;

[0029] When no encryption flag is identified, no encryption is performed; when an encryption flag is identified, an encryption operation is performed, when the data type is a non-text type, a new folder is created, the non-text type data is moved to the new folder, and then zip compression is performed, after compression, encryption is performed, and the encrypted folder is transmitted; when the data type is a text type, a password library is set, the password library is used to store password symbols, monitoring data is obtained, a segmentation model is set, the monitoring data is input into the segmentation model for segmentation, a plurality of data segments are obtained, the data segments are input into the password library for matching, corresponding password symbols are obtained, and the password symbols are transmitted; both parties of the detection data transmission are provided with a decryption unit, and the password of the monitoring data receiving party is updated in real time;

[0030] The method for establishing the segmentation model comprises: obtaining a plurality of groups of historical segmentation data, the historical segmentation data being the monitoring data, setting a preset segmentation condition, the preset segmentation condition being used to provide a segmentation basis for data segmentation, for example, setting a sentence as the preset segmentation condition, constructing an artificial intelligence model, inputting the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, and dividing the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a verification set according to a set proportion; the set proportion comprises 4:2:1, 4:3:1 and 3:2:2; the artificial intelligence model is trained, tested and verified through the training set, the test set and the verification set, and the trained artificial intelligence model is marked as a segmentation model;

[0031] Step 2: Before data transmission, both parties of the data transmission perform information verification;

[0032] An information verification library is established, a user list for monitoring data transmission is set, a fake-proof flag is set on the corresponding user information, a fake-proof identification end for data receiving of the other party is set on the user information, the user list is sent to the information verification library for storage, when a user needs to send monitoring data, the user fake-proof identification end for receiving the monitoring data is obtained, the obtained fake-proof identification end is set on the user information, when a user sends monitoring data, the user information and the corresponding fake-proof identification end are obtained, the obtained user information is matched with the user information in the information verification library, when no matching is successful, the monitoring data is not received; when the matching is successful, the corresponding fake-proof flag is obtained, the obtained fake-proof identification end is verified through the fake-proof flag, when the verification fails, the monitoring data is not received; when the verification is successful, the monitoring data sent by the corresponding user is received;

[0033] The method for setting the anti-fake mark comprises: establishing an anti-fake model, the anti-fake model comprising a plurality of verification rings and a verification center, the verification rings being provided with delay blocks, the verification center being provided with a signal receiving block, a rotating speed adjusting unit being provided, the rotating speed adjusting unit being used for setting the rotating speed of each verification ring and the verification center, when the anti-fake mark needs to be set, the rotating speed adjusting unit randomly generates the rotating speed of the verification rings and the verification center, and generates a rotating speed statistical table, the verification rings and the verification center start to rotate, when the rotating speed is set, the anti-fake model generates a corresponding anti-fake mark, an anti-fake identification end is set according to the rotating speed statistical table, the anti-fake identification end sends a plurality of verification signals according to the rotating speed of the verification rings and the verification center and the delay time t of the delay blocks, when the verification signals are received by the delay blocks, the verification rings stop rotating for t seconds, the remaining verification signals pass through the corresponding delay blocks, the verification rings rotate again after t seconds, the corresponding delay blocks no longer receive the verification signals in the current verification process, when the remaining verification signals hit the verification rings or the delay blocks, the verification fails, the verification signals passing through the delay blocks verify the next verification ring, until the verification signals passing through all the verification rings are received by the signal receiving block provided on the verification center, the verification succeeds;

[0034] Step three: monitoring data transmission is performed;

[0035] Step four: the transmitted monitoring data is monitored.

[0036] In use, the data type and encryption mark are identified, and the data to be encrypted is encrypted; when no encryption mark is identified, no encryption is performed; when the encryption mark is identified, the encryption operation is performed, when the data type is non-text, a new folder is created, the non-text data is moved to the new folder, then zip compression is performed, and after compression, encryption is performed, the encrypted folder is transmitted; when the data type is text, a password library is set, the password library is used for storing password symbols, monitoring data is acquired, a segmentation model is set, the monitoring data is input into the segmentation model for segmentation, a plurality of data segments are obtained, the data segments are input into the password library for matching, corresponding password symbols are obtained, and the password symbols are transmitted; both parties for transmitting the detection data are provided with decryption units, and the password of the monitoring data receiving party is updated in real time;

[0037] Obtain a plurality of sets of historical segmentation data, the historical segmentation data being monitoring data, set a preset segmentation condition, the preset segmentation condition being used to provide a segmentation basis for data segmentation, for example, set a sentence as the preset segmentation condition, construct an artificial intelligence model, input the plurality of sets of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, divide the plurality of sets of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a verification set according to a set proportion; the set proportion includes 4:2:1, 4:3:1 and 3:2:2; train, test and verify the artificial intelligence model through the training set, the test set and the verification set, and mark the trained artificial intelligence model as a segmentation model;

[0038] Before data transmission, both parties of data transmission perform information verification; an information verification library is established, a user list for monitoring data transmission is set, a fake-proof mark is set on the corresponding user information, a fake-proof identification end for verification when the other party receives data is set on the user information, the user list is sent to the information verification library for storage, when a user needs to send monitoring data, the fake-proof identification end of the user receiving the monitoring data is obtained, the obtained fake-proof identification end is set on the user information, when a user sends monitoring data, the user information and the corresponding fake-proof identification end are obtained, the obtained user information is matched with the user information in the information verification library, when no matching is successful, the monitoring data is not received; when the matching is successful, the corresponding fake-proof mark is obtained, the obtained fake-proof identification end is verified through the fake-proof mark, when the verification fails, the monitoring data is not received; when the verification is successful, the monitoring data sent by the corresponding user is received;

[0039] A fake-proof model is established, the fake-proof model includes a plurality of verification rings and a verification center, a delay block is arranged on the verification ring, a signal receiving block is arranged on the verification center, a rotating speed adjusting unit is arranged, the rotating speed adjusting unit is used to set the rotating speed of each verification ring and the verification center, when a fake-proof mark needs to be set, the rotating speed adjusting unit randomly generates the rotating speed of the verification ring and the verification center, and generates a rotating speed statistical table, the verification ring and the verification center start to rotate, when the rotating speed is set, the fake-proof model generates a corresponding fake-proof mark, the fake-proof identification end is set according to the rotating speed statistical table, the fake-proof identification end sends a plurality of verification signals according to the rotating speed of the verification ring and the verification center and the delay time t of the delay block, when the verification signal is received by the delay block, the verification ring stops rotating for t seconds, the remaining verification signals pass through the corresponding delay block, the verification ring rotates again after t seconds, the corresponding delay block no longer receives the verification signal in this verification process, when the remaining verification signals hit the verification ring or the delay block, the verification fails; the verification signal passing through the delay block verifies the next verification ring, until the verification signal passing through all the verification rings is received by the signal receiving block arranged on the verification center, the verification is successful; monitoring data transmission is performed; the sent monitoring data is monitored.

[0040] In the description of the specification, the description of the terms "one embodiment", "an example", "a specific example" and the like means that the specific feature, structure, material or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In the specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Also, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in an appropriate manner.

[0041] In addition, the terms "first", "second", "third", etc. are used only for the purpose of description, and should not be construed as indicating or implying relative importance or implying the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless specifically limited otherwise.

[0042] The above is only an example and description of the structure of the present application, and those skilled in the art can make various modifications or supplements to the described specific embodiments or use similar ways to replace them, as long as they do not deviate from the structure of the application or exceed the scope defined by the claims.

Claims

1. An Internet platform monitoring data transmission exchange system, characterized by, The application relates to a data transmission system, which comprises a verification module, an encryption module, a server and a storage module; the verification module is used for information verification of data transmission parties, and the specific method comprises the following steps: establishing an information verification library, the information verification library is used for storing user information needing to be monitored for data transmission, setting a user list needing to be monitored for data transmission, setting an anti-fake mark on the corresponding user information, setting an anti-fake identification end for verifying when the user information receives data, sending the user list to the information verification library for storage, obtaining the anti-fake identification end of the user receiving the monitoring data when the user needs to send the monitoring data, setting the obtained anti-fake identification end on the user information, obtaining the user information and the corresponding anti-fake identification end when the user sends the monitoring data, matching the obtained user information with the user information in the information verification library, not receiving the monitoring data when the matching is unsuccessful, obtaining the corresponding anti-fake mark when the matching is successful, verifying the obtained anti-fake identification end through the anti-fake mark, not receiving the monitoring data when the verification fails, and receiving the monitoring data sent by the corresponding user when the verification succeeds. The method for setting the anti-fake mark comprises the following steps: establishing an anti-fake model, the anti-fake model comprises a plurality of verification rings and a verification center, the verification rings are provided with delay blocks, the verification center is provided with a signal receiving block, a rotating speed adjusting unit is arranged, the rotating speed adjusting unit is used for setting the rotating speeds of the verification rings and the verification center, the rotating speed adjusting unit randomly generates the rotating speeds of the verification rings and the verification center and generates a rotating speed statistical table when the anti-fake mark needs to be set, the verification rings and the verification center start rotating, the anti-fake model generates the corresponding anti-fake mark when the rotating speeds are set, the anti-fake identification end is set according to the rotating speed statistical table, the anti-fake identification end sends a plurality of verification signals according to the rotating speeds of the verification rings and the verification center and the delay time t of the delay blocks, the verification rings stop rotating for t seconds when the verification signals are received by the delay blocks, the remaining verification signals pass through the corresponding delay blocks, the verification rings rotate again after t seconds, the corresponding delay blocks do not receive the verification signals in the present verification process, the verification fails when the remaining verification signals impact the verification rings or the delay blocks, the verification signals passing through the delay blocks verify the next verification ring, and the verification is successful when the verification signals passing through all the verification rings are received by the signal receiving block arranged on the verification center.

2. The Internet platform monitoring data transmission exchange system according to claim 1, wherein, The encryption module is used for encrypting the transmitted monitoring data, and the specific method comprises the following steps: identifying the data type and the encryption mark, and not performing encryption when no encryption mark is identified; when the encryption mark is identified, performing encryption operation, when the data type is non-text type, creating a new folder, moving the non-text type data into the new folder, then performing zip compression, and after compression, performing encryption, and transmitting the encrypted folder; when the data type is text type, setting a password library for storing password symbols, obtaining monitoring data, setting a segmentation model, inputting the monitoring data into the segmentation model for segmentation, obtaining a plurality of data segments, inputting the data segments into the password library for matching, obtaining corresponding password symbols, and transmitting the password symbols; both parties for transmitting the detection data are provided with a decryption unit, and the password of the monitoring data receiving party is updated in real time.

3. The Internet platform monitoring data transmission exchange system according to claim 2, wherein, The method for establishing the segmentation model comprises the following steps: obtaining a plurality of groups of historical segmentation data, the historical segmentation data being the monitoring data, setting a preset segmentation condition, the preset segmentation condition being used for providing segmentation basis for data segmentation, constructing an artificial intelligence model, inputting the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into the artificial intelligence model for learning and training, and dividing the plurality of groups of historical segmentation data, the corresponding preset segmentation conditions and the corresponding segmentation results into a training set, a test set and a verification set according to a set proportion; the set proportion comprises 4:2:1, 4:3:1 and 3:2:2; training, testing and verifying the artificial intelligence model through the training set, the test set and the verification set, and marking the trained artificial intelligence model as a segmentation model.

4. The switching method of the Internet platform monitoring data transmission switching system according to claim 1, characterized by, The specific method comprises the following steps: Step one: identifying the data type and the encryption mark, and encrypting the data that needs to be encrypted; Step two: before data transmission, the two parties for data transmission perform information verification; Step three: transmitting the monitoring data; Step four: monitoring the transmitted monitoring data.

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