Computer data remote security management system based on block chain encryption

Abstract

The invention discloses a computer data remote security management system based on block chain encryption, relates to the technical field of data security, and solves the problems that an existing verification mechanism is difficult to resist man-in-the-middle attack, and an attacker can bypass detection by tampering data and forging a verification code. According to the invention, through feature matching and dynamic interval feature calculation of the block chain storage node, dual binding of the transmission channel and the storage node is realized; in combination with randomization processing of virtual data positions, check codes have high uniqueness and reverse cracking resistance, man-in-the-middle attack and data forgery risks are effectively resisted, and a dual check code comparison mechanism before and after data transmission is realized; the verification code is generated before transmission, the identification code is generated after transmission, whether the data is tampered or lost can be accurately detected through consistency verification of the verification code and the identification code, and the integrity of the data in the remote transmission process is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of data security, and specifically to a remote security management system for computer data based on blockchain encryption. Background Art

[0002] With the rapid development of technologies such as cloud computing and the Internet of Things, the demand for remote management of computer data has surged, and the security of data during transmission and storage has become a core challenge; traditional data security management technologies mainly rely on means such as symmetric / asymmetric encryption algorithms and hash checks.

[0003] An application with the publication number CN114844673A discloses a data security management method, including: receiving the database access request of the user terminal, and through password verification confirmation, the database sends a level determination request to the permission authentication system; according to the user access level confirmed by the permission authentication system, the database calls data at the corresponding access level to the data encryption system; the data encryption system has several pairs of data encryption rules built in, and determines the selected encryption rule according to the time point to encrypt the data; the user terminal has a decryption rule adapted to the data encryption system built in, and determines the selected decryption rule according to the time point to decrypt the data sent by the data encryption system; this invention controls the outflow channel of highly confidential data, and it is also difficult to crack the data after interception during the process of transmitting the data to the user terminal.

[0004] Existing verification mechanisms (such as fixed hash values) are difficult to resist man-in-the-middle attacks. Attackers can bypass detection by tampering with data and forging verification codes, encrypt or decrypt during the actual transmission process, which will affect the efficiency of data transmission at the same time. Fixed verification methods and encryption methods are easily vulnerable to pattern attacks, and during the actual transmission process, it cannot be known in time whether the data has been tampered with or lost. Therefore, based on such data security verification problems during the transmission process, this application conducts security verification, which can not only ensure the stable reading and writing of the corresponding blockchain nodes, but also ensure the fast verification rate during the data transmission process and improve the accuracy of its data verification. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides a remote security management system for computer data based on blockchain encryption, which solves the problem that existing verification mechanisms are difficult to resist man-in-the-middle attacks, and attackers can bypass detection by tampering with data and forging verification codes.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: A remote security management system for computer data based on blockchain encryption, including:

[0007] The encryption feature locking end confirms the encryption channel between the computer and the blockchain from the transmission protocol, locks the data transmission channel of the computer and the blockchain storage node associated with this data transmission channel. Its transmission protocol has been constructed by the system itself before data transmission. Each different data interaction party has a different transmission protocol. Since this part of the content of the transmission protocol is relatively common in the prior art, it will not be elaborated here;

[0008] The feature preliminary processing end, according to the blockchain storage node associated with the data transmission channel, identifies the historical processing data generated by other storage nodes with the same feature parameters from the historical storage cloud data of the blockchain in the past, and locks the interval feature of this blockchain storage node. The specific method is as follows:

[0009] Based on the blockchain storage node associated with the data transmission channel, directly extract the storage read-write speed associated with this blockchain storage node, and then identify other blockchain storage nodes with the same storage read-write speed in this blockchain and record them as secondary nodes. From the historical storage cloud data of the blockchain in the past, lock the historical processing data associated with the secondary nodes. The locked time period is the preset period. Identify the data capacity processed during each interval of the corresponding secondary node from the historical processing data, and perform mean processing on the processed data capacities of several groups, and record it as the storage feature of the corresponding secondary node. Then perform mean processing on the storage features associated with several groups of secondary nodes, and use the processed mean value as the interval feature of this blockchain storage node;

[0010] Then, based on the determined interval feature, perform data column separation on the computer data to be transmitted, determine the feature for each group of data column separation, and lock the check code for this computer data. The specific method is as follows:

[0011] Confirm the total capacity ZR of the computer data to be transmitted this time from the data transmission channel, and calibrate the interval feature associated with this blockchain storage node as JG. Use ZR÷JG = Fg to confirm the segmentation feature value Fg;

[0012] If the processed segmentation feature value Fg is an integer, evenly divide the computer data this time into Fg groups of data columns, and the data capacity of each group of data columns is the same. If Fg is not an integer, synchronously divide the computer data into Fg groups of data columns, where the total data capacity of (Fg - 1) groups is the same and is ZR, and use the last remaining data as the last group of data columns;

[0013] Keep the internal sorting method of computer data unchanged, sort the divided multiple groups of data columns, add virtual data at different positions within each group of data columns, label the data on the left side of the virtual data in the corresponding data column as the left data segment, label the data on the right side of the virtual data as the right data segment, change the position of the virtual data in each data column, execute several change processes, and confirm the process characteristics associated with each change process:

[0014] In the corresponding change process, label the data capacity of several left data segments as R1 i , label the data capacity of several right data segments as R2 i , where i represents different data columns, perform variance processing on several groups of R1 i to confirm the left data segment variance, then perform variance processing on several groups of R2 i to confirm the right data segment variance, then perform mean processing on the left data segment variance and the right data segment variance, and use the confirmed mean as the process characteristic of this change process;

[0015] From the process characteristics associated with several change processes, select the change process associated with the minimum process characteristic as the optimal process. If there are different change processes with the same process characteristics, they will not participate in the evaluation of the optimal process;

[0016] According to the confirmed optimal process, confirm the sorting position of the virtual data in each data column and label it as W i , where W i ≥2 and is a positive integer, and sort the confirmed several W i before and after according to the sorting method of the data column to confirm the check code belonging to this computer data. After the check code is generated, delete the associated virtual data in each group of data columns, and transmit the confirmed check code to the check code recording end for recording;

[0017] The data storage end, after the check code is generated, receives the computer data that has completed data separation and confirms the identification code of the received data column. The specific method is as follows:

[0018] After all the groups of data columns divided from the computer data are received, use the feature preliminary processing end to generate the identification code associated with this receiving process in the same way as the generation method of the same check code;

[0019] The check center then based on the recorded check code and the generated identification code, identifies whether the check code and the identification code are exactly the same. If they are exactly the same, it feeds back a correct signal. If they are not exactly the same, it directly generates an error signal and synchronously transmits the error signal to the computer end;

[0020] When the received feedback signal is an error-free signal, the data columns of this time are integrated to obtain computer data, which is stored in the block node cloud library;

[0021] When the received feedback signal is an error signal, several groups of data columns of this time are deleted.

[0022] Preferably, it further includes:

[0023] The secondary encryption end, based on the error-free signal, confirms the storage location of this computer data in the block node cloud library, locks the storage path node based on the confirmed storage location, divides the associated computer data evenly according to this storage path node, and stores the multiple evenly divided data packets after the evenly dividing process through the data storage end at the corresponding storage locations. The specific method is as follows:

[0024] Based on the storage path node associated with the corresponding storage location, identify the number of storage levels G associated with this storage path node;

[0025] Divide this computer data into G pieces, and the data capacity of each divided evenly divided data packet increases sequentially from front to back;

[0026] Transmit the multiple evenly divided data packets divided to the storage locations associated with the storage path nodes, and the specific storage execution process is executed by the data storage end.

[0027] Preferably, before storage, the data storage end needs to be encrypted and confirmed by the secondary encryption end before storage.

[0028] The present invention provides a remote security management system for computer data based on blockchain encryption. Compared with the prior art, it has the following beneficial effects:

[0029] The encryption feature locking end realizes the double binding of the transmission channel and the storage node through the feature matching of the blockchain storage node and the dynamic interval feature calculation; combined with the randomization processing of the virtual data position, the verification code has high uniqueness and anti-reverse cracking ability, effectively resists the man-in-the-middle attack and the risk of data forgery, and realizes the double verification code comparison mechanism before and after data transmission; generates a verification code before transmission and an identification code after transmission. Through the consistency verification of the two, it can accurately detect whether the data has been tampered with or lost, and ensure the integrity of the data during the remote transmission process;

[0030] The secondary encryption end adopts a dynamic equal division storage strategy driven by the number of storage levels (G value), and disperses the data in different path nodes in an increasing capacity manner; this "block + weight distribution" storage mechanism not only ensures the recombination efficiency when extracting data, but also enhances the data anti-theft ability through the asymmetric storage structure. Even if part of the data is leaked, it is difficult to restore the original content. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0032] Figure 2 It is a schematic diagram of the generation of the feedback signal of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0034] First Embodiment

[0035] Please refer to Figure 1 , this application provides a computer data remote security management system based on blockchain encryption, including an encryption feature locking end, a feature preliminary processing end, a verification code recording end, a secondary encryption end, a data storage end, a verification center, and a block node cloud library;

[0036] Among them, the encryption feature locking end is electrically connected to the input node of the feature preliminary processing end, and the feature preliminary processing end is respectively electrically connected to the input node of the verification code recording end or the data storage end, and the data storage end is respectively electrically connected to the input node of the verification center or the block node cloud library, and the block node cloud library, the secondary encryption end, and the data storage end are electrically connected in sequence from the output node to the input node:

[0037] Among them, the encryption feature locking end confirms the encryption channel between the computer and the blockchain from the transmission protocol, and locks the data transmission channel of the computer and the blockchain storage node associated with this data transmission channel;

[0038] Among them, the feature preliminary processing end, according to the blockchain storage nodes associated with the data transmission channel, identifies the historical processing data generated by other storage nodes with the same feature parameters from the historical storage cloud data of the blockchain in the past, locks the interval features of this blockchain storage node, and then based on the determined interval features, splits the computer data to be transmitted, determines the features for each group of data splitting, locks the check code for this computer data. Specifically, its check code is to confirm a group before the data is transmitted, and then confirm another group after the data is specifically transmitted, and identify whether the two confirmed check codes are exactly the same. If they are exactly the same, it means that the computer data transmitted this time has not been tampered with and belongs to accurate data. If there is relevant tampering, it means that such computer data has been tampered with, and a data security signal needs to be generated for display to give a security warning to the remote transmission process of the computer;

[0039] First of all, the feature preliminary processing end needs to determine the interval features of this blockchain storage node. The specific method for its determination is as follows:

[0040] Based on the blockchain storage node associated with the data transmission channel, directly extract the storage read and write speed associated with this blockchain storage node (the speed data is a preset value and can be directly extracted), and then identify other blockchain storage nodes with the same storage read and write speed in this blockchain and record them as secondary nodes. The selected secondary nodes do not exceed three groups (to avoid excessive data calculation volume, the number of groups needs to be limited). From the historical storage cloud data of the blockchain in the past, lock the historical processing data associated with the secondary nodes. The locked time period is a preset period, generally 48h, that is, the data generated within the past 48h. Identify the data volume processed during each interval of the corresponding secondary node from the historical processing data (for each storage node, after receiving a certain data volume of data, in order to avoid processing congestion or transmission congestion, it will have a certain time interval to complete the storage process of the corresponding data. Then the data volume it stores is relatively consistent in value and is determined according to the read and write speed of the corresponding storage node), and perform mean processing on the processed data volumes of several groups, record it as the storage feature of the corresponding secondary node, and then perform mean processing on the storage features associated with several groups of secondary nodes. Take the processed mean value (the mean value is a data volume value) as the interval feature of this blockchain storage node;

[0041] Example: The blockchain is relatively large, and the number of blockchain nodes it contains is countless. Therefore, after this blockchain node is completed, based on the associated storage read and write speed, other secondary nodes with the same features can be quickly locked. Based on the storage features generated by other secondary nodes in the past historical data, the corresponding numerical features of this blockchain node can be determined to conduct relevant verification and evaluation on the subsequent numerical coding;

[0042] Secondly, at the feature preliminary processing end, according to the interval feature of this blockchain storage node, the specific method for locking the verification code of this computer data is as follows:

[0043] Confirm the total capacity ZR of the computer data to be transmitted this time from the data transmission channel, and label the interval feature associated with this blockchain storage node as JG. Use ZR÷JG = Fg to confirm the segmentation feature value Fg;

[0044] If the processed segmentation feature value Fg is an integer, divide the computer data into Fg groups of data columns this time, and the data capacity of each group of data columns is the same. If Fg is not an integer, synchronously divide the computer data into Fg groups of data columns, where the total data capacity of (Fg - 1) groups is the same and is ZR, and use the last remaining data as the last group of data columns. Specifically, although the data capacity of the data columns is the same, the internal data lengths are different, and different types of data have different capacity values;

[0045] Keep the sorting method inside the computer data unchanged, sort the divided multiple groups of data columns, and add virtual data at different positions within each group of data columns. Label the data to the left of the virtual data in the corresponding data column as the left data segment, and label the data to the right of the virtual data as the right data segment. The position of the virtual data within each data column is different. Change the position of the virtual data in each data column, execute several change processes, and confirm the process features associated with each change process:

[0046] Label the data capacity of several left data segments in the corresponding change process as R1 i , label the data capacity of several right data segments as R2 i , where i represents different data columns, and perform variance processing on several groups of R1 i to confirm the left data segment variance, then perform variance processing on several groups of R2 i to confirm the right data segment variance, and then perform mean processing on the left data segment variance and the right data segment variance. Use the confirmed mean as the process feature of this change process;

[0047] From the process characteristics associated with several changing processes, the changing process associated with the minimum process characteristic is selected as the best process. If there are different changing processes with the same process characteristics, they will not be considered and will be eliminated. That is, the best process is confirmed only for the changing processes with different process characteristics (the best process is that the virtual data added in all data columns are in a relatively middle state, and the data capacity associated with the left and right sides of the virtual data is relatively even, and it is also relatively even on the whole. That is, the virtual data is not only in a relatively middle state in a single data column, but also in a state of equal distribution in the middle of the data when multiple data columns are combined. The reason for this kind of processing here is to ensure the uniqueness of the checksum code, which is distributed to each data column to ensure whether the corresponding data column has been tampered with during the transmission process, which can effectively ensure the comprehensiveness of the monitoring of the entire computer data and Accuracy, fully guarantee the remote security of computer data during transmission. For example, a computer data is divided into three groups of data columns, namely A{1234}, B{1A34F6} and C{1A3B5C7D}. The data style is only an example. Then, virtual data is added. The virtual data is assumed to be "body". After adding the position, A is changed to {12body34}, B is changed to {1A3body4F6}, and C is changed to {1A3Bbody5C7D}. After numerical analysis, a process feature associated with this change process is confirmed, and then other change processes are executed. Assuming that this change process only changes the virtual data position of A: A{1body234}, B{1A3body4F6} and C{1A3Bbody5C7D}, then the process feature associated with this change process can be confirmed. By analogy, the most balanced state is confirmed.

[0048] According to the confirmed optimal process, the sorting position of the virtual data in each data column is determined and marked as W. i , where W i ≥2, and is a positive integer, and the confirmed W i Sort forward and backward to confirm the check code belonging to this computer data. After the check code is generated, delete the virtual data associated with each group of data columns, and transmit the confirmed check code to the check code recording terminal for recording. For example, based on the above-mentioned related examples, the best process is determined as: A{1 body 234}, B{1A3 body 4F6} and C{1A3B body 5C7D}. Then, according to the location of the virtual data body, confirm the corresponding sorting position W. i , in the A data column, its body is ranked second, then the W of this body i =2, the W of B and C i If they are 4 and 5 respectively, then the generated check code is 245.

[0049] Its data storage end, after the verification code generation is completed, receives the computer data that has completed data column separation, and confirms the identification code of the received data columns. If so, it transmits the confirmed identification code to the verification center, and receives the feedback signal from the verification center. Based on the received feedback signal, it identifies whether to store the computer data received this time in the block node cloud library. The specific method for confirming the identification code is as follows:

[0050] After all the data columns divided from the computer data are received, the feature preliminary processing end uses the same generation method for the verification code to generate the identification code associated with this receiving process;

[0051] Combined with Figure 2 , its verification center then identifies whether the verification code and the generated identification code are exactly the same based on the recorded verification code and the generated identification code. If they are exactly the same, it feeds back a correct signal. If they are not exactly the same, it directly generates an error signal and synchronously transmits the error signal to the computer end. Based on this error signal, the relevant personnel at the computer end need to perform verification analysis on the current transmission process to determine the specific problems and whether there are data security risks;

[0052] When the received feedback signal is a correct signal, the data columns of this time are integrated to obtain computer data and stored in the block node cloud library (before storage, it needs to be encrypted and confirmed by the secondary encryption end and then stored);

[0053] When the received feedback signal is an error signal, the several groups of data columns of this time are deleted.

[0054] Specifically, through identification and verification, it can be determined whether the corresponding data is exactly the same before and after transmission. If it is exactly the same, then the generated verification code and identification code will also be exactly the same. If it is not the same, it means that there are specific problems with the corresponding data, which means that either there is data loss during the transmission process or the data has been tampered with by a third party. Relevant personnel need to make specific judgments on data security based on practical experience.

[0055] Second Embodiment

[0056] In the specific implementation process of this embodiment, compared with the above-mentioned embodiment, the first embodiment focuses on data security during the data transmission process, and this embodiment focuses on security during the data storage process. It belongs to the process of performing secondary encryption on the data that has been transmitted correctly and performing storage encryption;

[0057] Among them, the secondary encryption end, based on the error-free signal, confirms the storage location of the computer data of this computer in the block node cloud library, locks the storage path node based on the confirmed storage location, divides the associated computer data according to this storage path node, and stores the multiple evenly divided data packets after the even division process by the data storage end at the corresponding storage location. The specific method of even division is as follows:

[0058] Based on the storage path node associated with the corresponding storage location, identify the number G of storage levels associated with this storage path node. For example, if a storage path node is C drive / USERS / …… / …… / …… / this node, then the number of its storage levels is 6;

[0059] Divide this computer data into G parts, and the data capacity of each divided evenly divided data packet increases sequentially from front to back. That is, when dividing the computer data, start dividing from the front. The capacity of the first group of evenly divided data packets divided is lower than that of the subsequent group of evenly divided data packets, and so on. When dividing step by step backward, the divided data capacity gradually increases. The reason for such setting is to plan the data sufficiently for subsequent data extraction;

[0060] Transmit the divided multiple evenly divided data packets to the storage location associated with the storage path node, and the specific storage execution process is performed by the data storage end;

[0061] Specifically, it also includes: when extracting data from a specified storage path node later, first extract all the data packets of the corresponding storage path node, and then reorganize several data packets in the order of increasing data capacity from small to large to obtain the originally stored computer data.

[0062] Some of the data in the above formula are numerically calculated after removing their dimensions, and the content not described in detail in this specification belongs to the prior art well known to those skilled in the art.

[0063] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A computer data remote security management system based on blockchain encryption, characterized in that: include: The encryption feature locking terminal confirms the encryption channel between the computer and the blockchain from the transmission protocol, locks the computer's data transmission channel and the blockchain storage node associated with this data transmission channel; The feature preliminary processing end, according to the blockchain storage node associated with the data transmission channel, identifies the historical processing data generated by other storage nodes with the same feature parameters from the past storage history cloud data of the blockchain, locks the interval feature of this blockchain storage node, and then based on the determined interval feature, performs data segmentation on the computer data to be transmitted, determines the features of each group of data segmentation, and locks the checksum code about this computer data; After the verification code is generated, the data storage end receives the computer data with completed data column, and confirms the identification code of the received data column. If the confirmed identification code is transmitted to the verification center, the feedback signal of the verification center is received, and based on the received feedback signal, it is determined whether to store the computer data received this time in the block node cloud library.

2. According to claim 1, a computer data remote security management system based on blockchain encryption is characterized in that: The specific method of determining the interval characteristics of blockchain storage nodes at the feature preliminary processing end is: Based on the blockchain storage node associated with the data transmission channel, the storage read and write speed associated with this blockchain storage node is directly extracted, and then other blockchain storage nodes with the same storage read and write speed are identified from this blockchain and recorded as secondary nodes. From the past storage history cloud data of the blockchain, the historical processing data associated with the secondary node is locked, and the locked time period is a preset period. The data capacity processed by the corresponding secondary node in each interval process is identified from the historical processing data, and the processed data capacities are averaged and recorded as the storage characteristics of the corresponding secondary node. The storage characteristics associated with several groups of secondary nodes are averaged, and the processed average is used as the interval characteristic of this blockchain storage node.

3. A computer data remote security management system based on blockchain encryption according to claim 2, characterized in that: The selected secondary nodes are no more than three groups, and the interval characteristic is a data capacity value.

4. A computer data remote security management system based on blockchain encryption according to claim 2, characterized in that: The specific method of locking the verification code at the feature preliminary processing end is: Confirm the total capacity ZR of the computer data to be transmitted this time from the data transmission channel, and mark the interval feature associated with this blockchain storage node as JG, and use ZR÷JG=Fg to confirm the segmentation feature value Fg; If the processed segmentation feature value Fg is an integer, the computer data is divided into Fg groups of data columns, and the data capacity of each group of data columns is the same. If Fg is not an integer, the computer data is divided into Fg groups of data columns, where the total data capacity of (Fg-1) groups is the same and is ZR, and the remaining data is taken as the last group of data columns; Keep the sorting method inside the computer data unchanged, sort the divided multiple groups of data columns, add virtual data at different positions in each group of data columns, mark the data on the left side of the virtual data in the corresponding data column as the left data segment, mark the data on the right side of the virtual data as the right data segment, change the position of the virtual data in each data column, execute several change processes, and confirm the process characteristics associated with each change process: The data capacity of several left data segments in the corresponding change process is marked as R1 i , mark the data capacity of several right data segments as R2 i , where i represents different data columns, and several groups of R1 i Perform variance processing to confirm the variance of the left data segment, and then divide several groups of R2 i Perform variance processing to confirm the variance of the right data segment, then perform mean processing on the variance of the left data segment and the variance of the right data segment, and use the confirmed mean as the process characteristic of this change process; From the process characteristics associated with several change processes, the change process associated with the minimum process characteristic is selected as the best process. If there are different change processes with the same process characteristics, they will not participate in the evaluation of the best process. According to the confirmed optimal process, the sorting position of the virtual data in each data column is determined and marked as W. i , where W i ≥2, and is a positive integer, and the confirmed W i Perform forward and backward sorting to confirm the check code belonging to this computer data. After the check code is generated, delete the virtual data associated with each group of data columns, and transmit the confirmed check code to the check code recording terminal for recording.

5. A computer data remote security management system based on blockchain encryption according to claim 4, characterized in that: The specific method of confirming the identification code at the data storage end is: After receiving all the data columns divided by the computer data, the identification code associated with this receiving process is generated by using the same generation method of the check code as that of the feature preliminary processing end; The verification center determines whether the verification code and the identification code are completely consistent based on the recorded verification code and the generated identification code. If they are completely consistent, a correct signal is fed back. If they are not completely consistent, an error signal is directly generated and synchronously transmitted to the computer end. When the received feedback signal is a correct signal, the data column is integrated to obtain computer data and stored in the block node cloud library; When the received feedback signal is an error signal, the several groups of data columns are deleted.

6. A computer data remote security management system based on blockchain encryption according to claim 5, characterized in that: Also includes: The secondary encryption end, based on the error-free signal, confirms the storage location of the computer data in the block node cloud library, and locks the storage path node based on the confirmed storage location, divides the associated computer data according to the storage path node, and stores the multiple divided data packets processed by the data storage end in the corresponding storage location.

7. A computer data remote security management system based on blockchain encryption according to claim 6, characterized in that: The specific method of equally dividing the computer data at the secondary encryption end is: Based on the storage path node associated with the corresponding storage location, identifying the number of storage levels G associated with the storage path node; The computer data is divided into G data packets, and the data capacity of each divided equally divided data packet increases from the front to the back; The divided multiple equally divided data packets are transmitted to the storage location associated with the storage path node, and the specific storage execution process is executed by the data storage end.

8. A computer data remote security management system based on blockchain encryption according to claim 6, characterized in that: Before storing, the data storage end needs to be encrypted and confirmed by the secondary encryption end before storing.

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