A method and system for backup and recovery of computing power network data based on unitary transformation

Abstract

This invention discloses a method and system for data backup and recovery of computing power networks based on unitary transformation. The backup and recovery method includes the following steps: S1 Dividing the original data file into blocks and representing them as symbol sequences, and establishing an index for the data blocks; S2 Mapping the symbol sequences of the data blocks to orthogonal basis vectors; S3 Generating random permutations by combining the master seed with the data blocks and version numbers, and applying random permutations to the quantum states of the data blocks to obtain backup data; S4 Compressing the backup data and storing it in a first storage area, and storing the seed parameters used for the permutations in a second secure storage area; S5 Searching the index based on the query tags input by the user to obtain a list of all data block IDs containing the query tags; S6 Reading and decompressing the backup data, obtaining the inverse permutation from the hardware security module, performing an inverse unitary transformation on each symbol, and restoring the original symbol sequence; S7 Observing and determining the symbol values ​​of the original symbol sequence, converting them back to binary data, merging them, and outputting the original file.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information security and data protection, in particular, especially relates to a kind of computing power network data backup and recovery method and system based on unitary transformation. BACKGROUND

[0002] As a new type of information infrastructure, computing power network connects dispersed computing resources through network to form a unified computing power pool, which can realize flexible scheduling and collaborative sharing of computing, storage and network resources. In its normal operation process, the backup and recovery of core data are crucial. Once these data are lost or tampered with, it will directly affect the scheduling accuracy, task execution reliability and overall security of computing power network.

[0003] Currently, the existing computing power network data backup and recovery technology has the following problems: the backup data security protection capability is insufficient, the encryption and backup process operation is complex, in addition, there is a lack of effective verification of legality and integrity in the recovery process, and there is a great risk of leakage.

[0004] Therefore, starting from the physical level of quantum information coding, a new data backup and recovery method that can make backup data no longer directly readable in simple form, deeply integrate security protection and backup operation instead of "external", and eliminate the risk of plaintext exposure in the recovery process, has become a technical problem to be solved by the technical personnel in the field. SUMMARY

[0005] To solve the above technical problems, the present application provides a kind of computing power network data backup and recovery method and system based on unitary transformation, adds a new type of data backup and recovery method that can integrate quantum security principle, backup flexibility and security recovery capability to existing data backup system, to improve its resilience to known and unknown attacks.

[0006] The technical scheme provided by the present application is as follows: This invention provides a method for data backup and recovery of a computing network based on unitary transformation, comprising the following steps: S1 Dividing the original data into multiple data blocks and representing each data block as a symbol sequence; S2 Encoding the symbol sequence into a quantum state; S3 Generating a random permutation based on a master seed, data block identifier, and version number, constructing a unitary matrix corresponding to the random permutation, applying the unitary matrix to the quantum state, and permuting each symbol in the symbol sequence to obtain a backup symbol sequence; S4 Storing the backup symbol sequence in a first storage area and storing the seed parameters used to generate the random permutation in a second secure storage area, the second secure storage area being physically isolated from the first storage area; S5 Responding to a data recovery request, obtaining the backup symbol sequence of the data block to be recovered and the corresponding seed parameters; S6 Regenerating a random permutation based on the seed parameters and determining the inverse permutation of the regenerated random permutation; Performing an inverse unitary transformation on the obtained backup symbol sequence using the inverse permutation to obtain a recovered symbol sequence; S7 Converting the recovered symbol sequence back to binary data to reconstruct the original data.

[0007] Furthermore, in a preferred embodiment of the present invention, step S1 specifically includes: Let the original data size be |F| bytes. Choose a fixed block size L and divide the original data into M consecutive data blocks, where:

[0008] For the i-th data block (i=0,1,…,M) 1) Its binary content is defined as:

[0009] The data block is divided into k symbols, each symbol being m bits, with the symbol set Σ={0,1}. m Data blocks are represented as sequences of symbols:

[0010] For the data block D i Define metadata tag set T i Each label t is a string of finite length used in plaintext. Construct an inverted index table Index: .

[0011] Furthermore, in a preferred embodiment of the present invention, step S2 specifically includes: Each symbol s j basis vectors |s mapped to N-dimensional Hilbert space j The quantum state is defined as the tensor product of the basis vectors:

[0012] Furthermore, in a preferred embodiment of the present invention, step S3 specifically includes: Read the master seed (Seed∈{0,1}) from the secure transmission platform. 256 Combining the data block ID and backup version number v, a random seed r is generated using a key derivation function. i,v Then generate random permutation π i,v ∈S N The corresponding unitary matrix U i,v Defined as:

[0013] For U i,v Each symbol is subjected to a permutation independently:

[0014] The backup data obtained after the permutation is a symbol sequence:

[0015] Furthermore, in a preferred embodiment of the present invention, steps S4 and S5 specifically include: The backup data C is losslessly compressed and denoted as C0. comp , will the C comp Write to the first storage area, along with metadata such as data block ID, version number, backup time, compression method, and data length; The parameters for generating permutation π are stored in the second secure storage area. For a full backup, the complete parameters of π are stored; for an incremental backup, the differential permutation δ is stored, satisfying:

[0016] Search the inverted index table Index for a list of data block IDs containing the label Q:

[0017] Furthermore, in a preferred embodiment of the present invention, step S6 specifically includes: Backup data is read from the first storage area. If the backup data is compressed, it is decompressed to obtain the backup symbol sequence C. i,v If it's an incremental version, start with the full baseline backup data, apply incremental updates sequentially, and reconstruct the complete C++ version of the target version. i,v ; Obtain the permutation π for the corresponding version v i,vIf it is an incremental backup, then starting from the full base version, the difference substitution δ in the version chain is applied sequentially to reconstruct the complete π of the target version. i,v And calculate its inverse permutation π 1 ; Backup data and inverse permutation π 1 They are all sent into the trusted operating environment, where an inverse unitary transformation is performed on each symbol:

[0018] The recovered symbol sequence is obtained:

[0019] Furthermore, in a preferred embodiment of the present invention, step S7 specifically includes: In the computation basis {∣s Projection measurements are performed under the following conditions, and the measurements are performed by a set of projection operators Ms=|s s | Description. | ψ recovered These are the eigenstates under the computational basis, and the measurement results yield the original symbol s. j Convert sj' back to binary data in m bits per symbol:

[0020] In addition, the present invention also provides another technical solution: The present invention also provides a computing network data backup and recovery system based on unitary conversion, comprising: a classical computing subsystem, a quantum simulation subsystem, and a storage subsystem; The classical computing subsystem includes: a data segmentation module, which is responsible for segmenting and symbolizing the original data; a tag indexing module, which is used to build and manage plaintext tag indexes to support subsequent selective recovery; and a quantum encoding module, which is used to convert the symbol sequence output by the data segmentation module into a matrix form that can be processed by the quantum simulator. The quantum simulation subsystem includes: a unitary matrix generation module, used to generate a random unitary matrix for each data block, i.e., random permutation; a unitary transformation module, used for the core calculation of backup operation; an inverse matrix calculation module, used for the recovery process; and an inverse transformation module, used for the core calculation of recovery operation. The storage subsystem includes: a storage database for storing backup data after unitary conversion and its associated metadata; and a parameter management module for storing all sensitive parameters and providing secure injection, query, update and deletion functions for parameters.

[0021] This invention provides a method for data backup and recovery of a computing network based on unitary transformation, comprising the following steps: S1 Dividing the original data into multiple data blocks and representing each data block as a symbol sequence; S2 Encoding the symbol sequence into a quantum state; S3 Generating a random permutation based on a master seed, data block identifier, and version number, constructing a unitary matrix corresponding to the random permutation, applying the unitary matrix to the quantum state, and permuting each symbol in the symbol sequence to obtain a backup symbol sequence; S4 Storing the backup symbol sequence in a first storage area and storing the seed parameters used to generate the random permutation in a second secure storage area, the second secure storage area being physically isolated from the first storage area; S5 Responding to a data recovery request, obtaining the backup symbol sequence of the data block to be recovered and the corresponding seed parameters; S6 Regenerating a random permutation based on the seed parameters and determining the inverse permutation of the regenerated random permutation; Performing an inverse unitary transformation on the obtained backup symbol sequence using the inverse permutation to obtain a recovered symbol sequence; S7 Converting the recovered symbol sequence back to binary data to reconstruct the original data. In the solution described in this invention, the original data is segmented and a plaintext index is established. After the binary symbol sequence is mapped to a quantum state, a random permutation generated by reading the master seed from the hardware security module is applied to the quantum state. The resulting backup data no longer has a directly readable form. The generation and application of the random permutation are directly embedded in the backup process, eliminating the need for an external encryption module, thus reducing system complexity. The backup data is losslessly compressed and stored in ordinary storage media, while the seed parameters are stored separately in the hardware security module. During recovery, the data block is quickly located using the plaintext index, and the inverse permutation is obtained from the hardware security module to perform an inverse unitary transformation. The original symbol sequence is restored in a controlled environment, and the original file is output after quantum state observation. This avoids the risks of direct data reading due to backup media leakage and plaintext exposure during the recovery process. In summary, compared with existing technologies, this invention has significant advantages such as simple system operation, high recovery efficiency, and controllable data security. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Fig. 1 This is a flowchart illustrating the steps of a computing network data backup and recovery method based on unitary conversion, as described in an embodiment of the present invention.

[0024] Fig. 2This is a flowchart of a computing network data backup and recovery method based on unitary conversion, which is an embodiment of the present invention.

[0025] Fig. 3 This is a diagram of the computing power network data backup and recovery system architecture based on unitary conversion, which is an embodiment of the present invention.

[0026] Fig. 4 This is an operation flowchart of the computing power network data backup and recovery system based on unitary conversion involved in the embodiments of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0028] It should be noted that when a component is referred to as being "fixed to" or "set on" another component, it can be directly on or indirectly set on the other component; when a component is referred to as being "connected to" another component, it can be directly connected to or indirectly connected to the other component.

[0029] It should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "first", "second", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention.

[0030] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" or "several" means two or more, unless otherwise explicitly specified.

[0031] It should be noted that the structures, proportions, sizes, etc., shown in the accompanying drawings of this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed in the specification, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0032] like Figs. 1 to 4 As shown, this invention discloses a method and system for data backup and recovery of computing power networks based on unitary transformation. The backup and recovery method includes the following steps: S1 Dividing the original data into multiple data blocks and representing each data block as a symbol sequence; S2 Encoding the symbol sequence into a quantum state; S3 Generating a random permutation based on the master seed, data block identifier, and version number, and constructing a unitary matrix corresponding to the random permutation, applying the unitary matrix to the quantum state to permutate each symbol in the symbol sequence to obtain a backup symbol sequence; S4 Storing the backup symbol sequence in a first storage area and storing the seed parameters used to generate the random permutation in a second secure storage area, the second secure storage area being physically isolated from the first storage area; S5 Responding to a data recovery request, obtaining the backup symbol sequence of the data block to be recovered and the corresponding seed parameters; S6 Regenerating a random permutation according to the seed parameters and determining the inverse permutation of the regenerated random permutation; Performing an inverse unitary transformation on the obtained backup symbol sequence using the inverse permutation to obtain a recovered symbol sequence; S7 Converting the recovered symbol sequence back to binary data to reconstruct the original data. In the solution of this invention, the form of the backup data is changed by performing quantum encoding, random unitary transformation and inverse transformation on the backup data, thereby increasing the difficulty for attackers to crack it and enhancing the security of the backup data in the storage and recovery process.

[0033] The following detailed description of a computing network data backup and recovery method based on unitary conversion disclosed in this invention is illustrated with specific embodiments.

[0034] Specifically, in a specific embodiment of the present invention, step S1 includes: Let the original data size be |F| bytes. Choose a fixed block size L and divide the original data into M consecutive data blocks, where:

[0035] For the i-th data block (i=0,1,…,M) 1) Its binary content is defined as:

[0036] The data block is divided into k symbols, each symbol being m bits, with the symbol set Σ={0,1}. m Data blocks are represented as sequences of symbols:

[0037] For the data block D i Define metadata tag set T i Each label t is a string of finite length used in plaintext. Construct an inverted index table Index: .

[0038] In a specific embodiment of the present invention, in step S1, by constructing data blocks and plaintext inverted indexes, the target data block can be quickly located during recovery without traversing or decrypting all backup data, thereby greatly improving recovery efficiency; at the same time, the index and backup data are separated, and the backup data itself is unreadable, so the overall security is acceptable.

[0039] It should also be noted that in step S1, if the last data block is less than the fixed block size L bytes, it is padded with zero bits to the length L; each symbol takes m bits, m=8, and the symbol set radix is ​​256; the inverted index table is stored in a secure storage area and is separate from the backup data.

[0040] Specifically, in a specific embodiment of the present invention, the specific steps of S2 include: Each symbol s j basis vectors |s mapped to N-dimensional Hilbert space j The quantum state is defined as the tensor product of the basis vectors:

[0041] In a specific embodiment of the present invention, in step S2, classical data is encoded into quantum states and run in a trusted execution environment, which can ensure the confidentiality of data during encoding and transmission, and provide a standardized quantum state input format for subsequent unitary transformations.

[0042] It should also be noted that in step S2, the quantum state described in the classical computer is simulated as a symbol array [s1, s2, ..., s k Each element is an integer from 0 to N-1; this symbol array is fed into a quantum simulator.

[0043] Specifically, in a specific embodiment of the present invention, step S3 includes: Read the master seed (Seed∈{0,1}) from the secure transmission platform. 256Combining the data block ID and backup version number v, a random seed r is generated using a key derivation function. i,v Then generate random permutation π i,v ∈S N The corresponding unitary matrix U i,v Defined as:

[0044] For U i,v Each symbol is subjected to a permutation independently:

[0045] The backup data obtained after the permutation is a symbol sequence:

[0046] In a specific embodiment of the present invention, in step S3, a unitary matrix is ​​constructed by randomly and uniformly selecting permutations and applied to the quantum state, so that the backup data presents a pseudo-random distribution and is completely unreadable, integrating backup and encryption into one, without the need to call an additional encryption library, thereby effectively defending against local physical attacks against the storage system.

[0047] It should also be noted that in step S3, the master seed is generated by a true random number generator and permanently stored inside the secure transmission platform; the unitary matrix satisfies U i,v † U i,v =I N The function of this matrix is ​​U i,v |s =∣π i,v (s) The random permutation π i,v From the symmetry group S N The samples were randomly selected evenly from the middle.

[0048] Specifically, in a specific embodiment of the present invention, step S4 includes: The backup data C is losslessly compressed and denoted as C0. comp , will the C comp Write to the first storage area, along with metadata such as data block ID, version number, backup time, compression method, and data length; The parameters for generating permutation π are stored in the second secure storage area. For a full backup, the complete parameters of π are stored; for an incremental backup, the differential permutation δ is stored, satisfying:

[0049] In a specific embodiment of the present invention, in step S4, the backup data and the permutation generation parameters are placed in two physically isolated storage areas, so that even if the backup medium is stolen, the plaintext cannot be restored, which significantly enhances security; at the same time, lossless compression is performed by utilizing the characteristic that permutation does not change the symbol frequency distribution, and only the changed part is stored for the incremental version, which effectively optimizes storage efficiency.

[0050] It should also be noted that in step S4, when performing lossless compression on the backup symbol sequence, sequences of consecutive identical symbols are encoded as (symbol, repetition count) pairs; for data without obvious repetition, compression can be skipped or other general compression algorithms can be used; the first storage area is a normal backup storage medium; the metadata attached to the storage record includes block ID, version number, backup time, compression method, and data length; for incremental backups, only the symbol positions and new values ​​that have changed since the previous version are stored; the second secure storage area is a secure transmission platform that provides tamper-proof key storage and a secure computing environment.

[0051] Specifically, in a specific embodiment of the present invention, step S5 includes: Search the inverted index table Index for a list of data block IDs containing the label Q:

[0052] In a specific embodiment of the present invention, in step S5, a tag query is performed based on the plaintext inverted index. The entire search process is completed in a classic computing environment. The list of data blocks to be restored can be obtained quickly without decrypting any backup data, which greatly shortens the recovery preparation time.

[0053] It should also be noted that in step S5, in response to a data recovery request, the inverted index table is searched based on the query tag submitted by the user to obtain a list of data block identifiers containing that tag.

[0054] Specifically, in a specific embodiment of the present invention, step S6 includes: Backup data is read from the first storage area. If the backup data is compressed, it is decompressed to obtain the backup symbol sequence C. i,v If it's an incremental version, start with the full baseline backup data, apply incremental updates sequentially, and reconstruct the complete C++ version of the target version. i,v ; Obtain the permutation π for the corresponding version v i,v If it is an incremental backup, then starting from the full base version, the difference substitution δ in the version chain is applied sequentially to reconstruct the complete π of the target version. i,v And calculate its inverse permutation π 1 ; Backup data and inverse permutation π 1 They are all sent into the trusted operating environment, where an inverse unitary transformation is performed on each symbol:

[0055] The recovered symbol sequence is obtained:

[0056] In a specific embodiment of the present invention, in step S6, the inverse transformation operation is performed entirely in a secure and trusted environment, and the external operating system cannot access the intermediate results, ensuring that plaintext data is not leaked during the recovery process; and because the inverse permutation accurately restores the original symbol sequence, the recovered symbol sequence is completely consistent with the original symbol sequence, with no information loss.

[0057] It should also be noted that in step S6, for each data block ID i∈I that needs to be recovered rec The system reads backup data from ordinary storage media; if it is an incremental version, it applies incremental updates sequentially starting from the full baseline backup data; it obtains the corresponding version's permutation from the secure transmission platform and calculates its inverse permutation within a secure and trusted environment; the entire inverse conversion process is completed within a secure space, and the external operating system cannot access the intermediate results.

[0058] Specifically, in a specific embodiment of the present invention, step S7 includes: In the computation basis {∣s Projection measurements are performed under the following conditions, and the measurements are performed by a set of projection operators Ms=|s s | Description. | ψ recovered These are the eigenstates under the computational basis, and the measurement results yield the original symbol s. j Convert sj' back to binary data in m bits per symbol:

[0059] In a specific embodiment of the present invention, in step S7, the recovered quantum state is the eigenstate under the computational basis. The projection measurement result deterministically gives each original symbol without the need for probabilistic repeated measurement. After converting the symbol sequence back to binary, the original file can be reconstructed without loss.

[0060] It should also be noted that in step S7, the recovered quantum state is projected and measured under the computational basis. The measurement results deterministically give each original symbol. The symbol sequence is converted back to binary data in m bits per symbol. All data blocks are merged and assembled into the original file and output.

[0061] This invention discloses a computing network data backup and recovery system based on unitary conversion, comprising: a classical computing subsystem, a quantum simulation subsystem, and a storage subsystem; The classical computing subsystem includes: a data segmentation module, which is responsible for segmenting and symbolizing the original data; a tag indexing module, which is used to build and manage plaintext tag indexes to support subsequent selective recovery; and a quantum encoding module, which is used to convert the symbol sequence output by the data segmentation module into a matrix form that can be processed by the quantum simulator. The quantum simulation subsystem includes: a unitary matrix generation module, used to generate a random unitary matrix for each data block, i.e., random permutation; a unitary transformation module, used for the core calculation of backup operation; an inverse matrix calculation module, used for the recovery process; and an inverse transformation module, used for the core calculation of recovery operation. The storage subsystem includes: a storage database for storing backup data after unitary conversion and its associated metadata; and a parameter management module for storing all sensitive parameters and providing secure injection, query, update and deletion functions for parameters.

[0062] In summary, the present invention relates to a method and system for backing up and securely restoring core data in computing networks based on the quantum unitary transformation principle. This method is applicable to scenarios with high-security data backup and recovery requirements, such as computing networks, cloud computing, and big data centers. It overcomes the security problems and shortcomings of existing computing network data backup technologies, proposing a secure backup method based on unitary transformation, and providing a data backup system with compatible security performance, high cracking difficulty, and a high security coefficient. Its core idea is that the original data is segmented and a plaintext index is established. After mapping to quantum states, a random permutation generated by a hardware security module is applied to obtain backup data that cannot be directly read. This permutation is embedded in the backup process, eliminating the need for an external encryption module, reducing system complexity. The backup data is compressed and stored in ordinary media, while the seed parameters are stored separately in the hardware security module. During recovery, the plaintext index is used to locate the data, obtain the inverse permutation, restore the symbol sequence under controlled conditions, and output the original file, thereby avoiding the risk of backup media leakage and plaintext exposure during recovery. The process includes the following steps: S1. Divide the original data file into blocks and represent them as symbol sequences, creating an index for each block; S2. Map the symbol sequences of the data blocks to orthogonal basis vectors; S3. Combine the master seed with the data block and version number to generate random permutations, apply the random permutations to the quantum states of the data blocks to obtain backup data; S4. Compress the backup data and store it in the first storage area, storing the seed parameters used for the permutations in the second secure storage area; S5. Search the index based on the user-input query tag to obtain a list of all data block IDs containing the query tag; S6. Read and decompress the backup data, obtain the inverse permutation from the hardware security module, perform an inverse unitary transformation on each symbol, and restore the original symbol sequence; S7. Observe and determine the symbol values ​​of the original symbol sequence, convert them back to binary data, merge them, and output the original file. It is evident that the technical solution involved in this invention, compared with the prior art, can eliminate the problem of separation between backup and encryption, reduce system complexity; the backup data presents a dynamic and random form, realizing high-strength security protection of "one backup and one encryption"; the risk of leakage during the recovery process is reduced, and plaintext data does not appear in the external operating system, disk or network buffer during the entire recovery process, which has significant practical value.

[0063] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for data backup and recovery in a computing network based on unitary conversion, characterized in that, Includes the following steps: S1 divides the original data into multiple data blocks, and represents each data block as a symbol sequence; S2 encodes the symbol sequence into a quantum state; S3 generates random permutations based on the master seed, data block identifier, and version number, and constructs a unitary matrix corresponding to the random permutations; Applying the unitary matrix to the quantum state, and permuting each symbol in the symbol sequence, yields a backup symbol sequence; S4 stores the backup symbol sequence in a first storage area and stores the seed parameters used to generate the random permutation in a second secure storage area, the second secure storage area being physically isolated from the first storage area; S5 responds to the data recovery request by obtaining the backup symbol sequence of the data block to be recovered and the corresponding seed parameters; S6 regenerates a random permutation based on the seed parameters and determines the inverse permutation of the regenerated random permutation; the inverse permutation is used to perform an inverse unitary transformation on the obtained backup symbol sequence to obtain the restored symbol sequence. S7 converts the recovered symbol sequence back into binary data to reconstruct the original data.

2. The method for data backup and recovery of computing power networks based on unitary conversion according to claim 1, characterized in that, The specific steps of S1 include: Let the original data size be |F| bytes. Choose a fixed block size L and divide the original data into M consecutive data blocks, where: ； For the i-th data block (i=0,1,…,M) 1) Its binary content is defined as: ； The data block is divided into k symbols, each symbol being m bits, with the symbol set Σ={0,1}. m Data blocks are represented as sequences of symbols: ； For the data block D i Define metadata tag set T i Each label t is a string of finite length used in plaintext. Construct an inverted index table Index: 。 3. The method for data backup and recovery of computing power networks based on unitary conversion according to claim 2, characterized in that, The specific steps of S2 include: Each symbol s j basis vectors |s mapped to N-dimensional Hilbert space j The quantum state is defined as the tensor product of the basis vectors: 。 4. The method for data backup and recovery of computing power networks based on unitary conversion according to claim 3, characterized in that, The specific steps of S3 include: Read the master seed (Seed∈{0,1}) from the secure transmission platform. 256 Combining the data block ID and backup version number v, a random seed r is generated using a key derivation function. i,v Then generate random permutation π i,v ∈S N The corresponding unitary matrix U i,v Defined as: ； For U i,v Each symbol is subjected to a permutation independently: ； The backup data obtained after the permutation is a symbol sequence: 。 5. The method for data backup and recovery of computing power networks based on unitary conversion according to claim 4, characterized in that, The specific steps of S4 include: The backup data C is losslessly compressed and denoted as C0. comp , will the C comp Write to the first storage area, along with metadata such as data block ID, version number, backup time, compression method, and data length; The parameters for generating permutation π are stored in the second secure storage area. For a full backup, the complete parameters of π are stored; for an incremental backup, the differential permutation δ is stored, satisfying: ； The specific steps for obtaining the backup symbol sequence of the data block to be recovered in S5 include: Search the inverted index table Index for a list of data block IDs containing the label Q: 。 6. The method for data backup and recovery of computing power networks based on unitary conversion according to claim 5, characterized in that, The specific steps of S6 include: Backup data is read from the first storage area. If the backup data is compressed, it is decompressed to obtain the backup symbol sequence C. i,v If it's an incremental version, start with the full baseline backup data, apply incremental updates sequentially, and reconstruct the complete C++ version of the target version. i,v ; Obtain the permutation π for version v i,v If it is an incremental backup, then starting from the full base version, the difference substitution δ in the version chain is applied sequentially to reconstruct the complete π of the target version. i,v And calculate its inverse permutation π 1 ; Backup data and inverse permutation π 1 They are all sent into the trusted operating environment, where an inverse unitary transformation is performed on each symbol: ； The recovered symbol sequence is obtained: 。 7. The method for data backup and recovery of computing power networks based on unitary conversion according to claim 6, characterized in that, The specific steps in S7 for converting the recovered symbol sequence back to binary data include: performing projection measurements on the recovered quantum state within a safe space. ； Among them, in the calculation basis {∣s Projection measurements are performed under the following conditions, and the measurements are performed by a set of projection operators Ms=|s s | description; | ψ recovered To compute the eigenstates under the basis, the measurement results yield the original symbol s. j ', convert sj' back to binary data in m bits per symbol.

8. A computing network data backup and recovery system based on unitary conversion, used to execute the computing network data backup and recovery method based on unitary conversion as described in any one of claims 1 to 7, characterized in that, include: The classical computing subsystem is used for analyzing, segmenting, constructing plaintext indexes, and performing quantum coding preprocessing on the raw data. A quantum simulation subsystem is used to perform unitary transformation processing during backup and recovery in a trusted execution environment; The storage subsystem is used to securely and persistently store backup data, metadata, indexes, and key parameters.

9. The computing network data backup and recovery system based on unitary conversion according to claim 8, characterized in that: The classical computing subsystem includes: a data partitioning module, which is responsible for partitioning and symbolizing the original data; and a quantum encoding module, which converts the symbol sequence output by the data partitioning module into a matrix form that can be processed by the quantum simulator. The quantum simulation subsystem includes: a unitary matrix generation module, used to generate a random unitary matrix for each data block; a unitary transformation module, used for the core calculation of backup operations; an inverse matrix calculation module, used for the recovery process; and an inverse transformation module, used for the core calculation of recovery operations. The storage subsystem includes a storage database for storing backup data after unitary conversion and its associated metadata.

10. The computing network data backup and recovery system based on unitary conversion according to claim 9, characterized in that: The classical computing subsystem also includes a tag index module for building and managing plaintext tag indexes to support subsequent selective recovery; The storage subsystem also includes a parameter management module, which stores all sensitive parameters and provides secure injection, query, update, and deletion functions for the parameters.

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