Cloud warehouse management method, system and program product

Abstract

The invention belongs to the technical field of cloud storage, and particularly discloses a cloud warehouse management method and system and a program product, and the method comprises the steps: extracting verification request information of a request end, carrying out the feature extraction and feature combination, obtaining a dynamic feature vector, and carrying out the matching verification of the dynamic feature vector, the cloud warehouse information management method comprises the steps of verifying the cloud warehouse information, receiving operation request information of a request end for analysis after verification is passed, obtaining an operation instruction and an operation type, finally performing permission matching according to the operation type, and responding to the operation instruction after permission matching is passed to perform management operation of a target cloud warehouse, so as to realize efficient and reliable cloud warehouse information management. Through a dual security verification mechanism of request verification and permission matching, the access permission of the request end can be strictly controlled, the sensitive data of the cloud warehouse can be effectively prevented from being leaked or tampered while the management operation of the cloud warehouse is efficiently completed, and the security of the cloud warehouse information of an enterprise is ensured.

Description

Technical Field

[0001] The present invention belongs to the field of cloud storage technology, and specifically relates to a cloud warehouse management method, system and program product. Background Art

[0002] Cloud warehousing is a modern warehousing management model based on cloud computing and big data technologies. By integrating distributed warehousing resources with intelligent management systems, it provides enterprises with one-stop services from cargo storage to order delivery. Its core advantage lies in reducing the cost of self-built warehouses, improving logistics efficiency, and relying on data analysis to achieve precise inventory allocation.

[0003] Cloud warehouse management systems store large amounts of sensitive data, including inventory information and supply chain data. Centralized data storage in the cloud increases the likelihood of data leaks. If this data is accessed by unauthorized personnel, it could cause severe financial losses and reputational damage to the company. Therefore, when choosing a cloud warehouse management system, companies must ensure it has robust data security management and access control mechanisms.

[0004] However, most existing cloud warehouse management systems rely on simple authentication and authorization access control methods. This involves verifying user identities through a combination of usernames, passwords, and mobile phone verification codes, and assigning access rights based on the principle of least privilege. This cloud warehouse management approach needs to be strengthened in terms of access control strength and data security. Summary of the Invention

[0005] The purpose of the present invention is to provide a cloud warehouse management method, system and program product to solve the above-mentioned problems existing in the prior art.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, a cloud warehouse management method is provided, comprising:

[0008] Obtaining verification request information sent by the requesting end, and extracting the warehouse number and the requesting end information set from the verification request information, wherein the requesting end information set includes biometric verification information, requesting end website information, and verification credential information;

[0009] Match the corresponding target cloud warehouse according to the warehouse number, and retrieve the verification vector set of the target cloud warehouse, where the verification vector set includes several verification vectors;

[0010] Vectorize the biometric verification information, the requesting end URL information, and the verification credential information to obtain a biometric feature vector, an address feature vector, and a credential feature vector;

[0011] A dynamic feature vector is formed using the biometric feature vector, the address feature vector, and the credential feature vector, and the matching degree between the dynamic feature vector and each verification vector in the verification vector set is calculated;

[0012] When the matching degree between the dynamic feature vector and a verification vector in the verification vector set reaches the set matching degree condition, the permission type table associated with the corresponding verification vector is retrieved, and the verification request is determined to be passed, and the verification request passing information is fed back to the requesting end;

[0013] Receive the operation request information sent by the requesting end, parse the operation request information, and obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction;

[0014] When the operation type code is consistent with a certain permission type code in the permission type table, a corresponding management operation is performed on the target cloud warehouse in response to the warehouse operation instruction.

[0015] In one possible design, the biometric verification information, the requesting end URL information, and the verification credential information are vectorized to obtain a biometric feature vector, an address feature vector, and a credential feature vector, including:

[0016] Extracting biometric features from the biometric verification information to obtain biometric parameters, and performing feature mapping on the biometric parameters using principal component analysis to obtain a biometric vector;

[0017] Performing linear transformation on each segment of the URL data of the requesting end URL information to obtain mapping data corresponding to each segment of the URL data, and combining each mapping data in sequence to obtain an address feature vector;

[0018] Perform encoding conversion processing on each character of the verification credential information to obtain the encoding data corresponding to each character, and combine the encoding data in sequence to obtain the credential feature vector.

[0019] In one possible design, the dynamic feature vector is composed of a biometric feature vector, an address feature vector, and a credential feature vector, including:

[0020] Combine the biometric feature vector, the address feature vector, and the credential feature vector in sequence in the row direction or the column direction to obtain an initial combination vector;

[0021] The components of the initial combination vector are subjected to data normalization to obtain the dynamic feature vector.

[0022] In one possible design, calculating the matching degree between the dynamic feature vector and each verification vector in the verification vector set includes:

[0023] Substitute the dynamic feature vector and the corresponding verification vector into the preset matching degree formula to calculate the matching degree between the dynamic feature vector and the corresponding verification vector. The matching degree formula is:

[0024]

[0025] Among them, P represents the matching degree between the dynamic feature vector and the verification vector, i is the vector component number of the dynamic feature vector and the verification vector, n is the number of components of the dynamic feature vector and the verification vector, x i Characterizes the i-th component of the dynamic eigenvector, y i Represents the i-th component of the validation vector.

[0026] In one possible design, when the matching degree between the dynamic feature vector and a verification vector in the verification vector set reaches a set matching degree condition, the permission type table associated with the corresponding verification vector is retrieved, including:

[0027] When the matching degree between the dynamic feature vector and a verification vector in the verification vector set exceeds a set matching degree threshold, the number of the corresponding verification vector is determined, and the permission type table associated with the number of the corresponding verification vector is retrieved, wherein the permission type table includes several permission type codes.

[0028] In one possible design, the operation request information is parsed to obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction, including:

[0029] Perform hash calculation on the verification credential information to obtain the corresponding hash value, and use the calculated hash value as the decryption key;

[0030] The operation request information is decrypted using the decryption key to obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction.

[0031] In one possible design, the method further includes:

[0032] After completing the management operation on the target cloud warehouse in response to the warehouse operation instruction, the verification operation completion information is fed back to the requesting end, and the connection with the requesting end is disconnected after receiving the request end information sent by the requesting end.

[0033] In a second aspect, a cloud warehouse management system is provided, comprising a data acquisition unit, a warehouse matching unit, a feature extraction unit, a feature matching unit, a request verification unit, an operation parsing unit, and an operation execution unit, wherein:

[0034] A data acquisition unit is used to acquire the verification request information sent by the requesting end, and extract the warehouse number and the requesting end information set from the verification request information, wherein the requesting end information set includes biometric verification information, requesting end website information and verification credential information;

[0035] A warehouse matching unit, configured to match a corresponding target cloud warehouse according to the warehouse number and retrieve a verification vector set of the target cloud warehouse, wherein the verification vector set includes a plurality of verification vectors;

[0036] A feature extraction unit is used to vectorize the biometric verification information, the requesting end URL information and the verification credential information to obtain a biometric feature vector, an address feature vector and a credential feature vector;

[0037] a feature matching unit, configured to form a dynamic feature vector using the biometric feature vector, the address feature vector, and the credential feature vector, and to calculate a matching degree between the dynamic feature vector and each verification vector in the verification vector set;

[0038] A request verification unit is configured to retrieve the permission type table associated with the corresponding verification vector when the matching degree between the dynamic feature vector and a verification vector in the verification vector set meets a set matching degree condition, determine whether the verification request is passed, and feedback the verification request passing information to the requesting end;

[0039] An operation parsing unit is used to receive the operation request information sent by the requesting end, parse the operation request information, and obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction;

[0040] The operation execution unit is used to perform corresponding management operations on the target cloud warehouse in response to the warehouse operation instruction when the operation type code is consistent with a permission type code in the permission type table.

[0041] In a third aspect, a cloud warehouse management system is provided, comprising:

[0042] a memory for storing instructions;

[0043] A processor is used to read the instructions stored in the memory and execute the cloud warehouse management method described in any one of the first aspects above according to the instructions.

[0044] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to execute any one of the cloud warehouse management methods described in the first aspect. Also provided is a computer program product that, when executed on a computer, executes any one of the cloud warehouse management methods described in the first aspect.

[0045] Beneficial effects: The present invention extracts the verification request information of the requesting end to perform feature extraction and feature combination to obtain a dynamic feature vector, then performs matching verification on the dynamic feature vector, and after the verification is passed, receives the operation request information of the requesting end to parse it to obtain the operation instruction and operation type, and finally performs permission matching according to the operation type, and responds to the operation instruction to perform the management operation of the target cloud warehouse after the permission matching is passed, so as to achieve efficient and reliable cloud warehouse information management. The present invention can achieve strict control of the access rights of the requesting end through the dual security verification mechanism of request verification and permission matching, and can effectively prevent the leakage or tampering of sensitive data in the cloud warehouse while efficiently completing the cloud warehouse management operation, thereby ensuring the security of the enterprise cloud warehouse information. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 Schematic diagram of the steps of the method in Example 1 of the present invention;

[0048] Figure 2 Schematic diagram of the system structure in Example 2 of the present invention;

[0049] Figure 3 This is a schematic diagram of the system structure in Example 3 of the present invention. DETAILED DESCRIPTION

[0050] It should be noted that the description of these embodiments is intended to help understand the present invention, but does not constitute a limitation of the present invention. The specific structural and functional details disclosed herein are merely intended to describe exemplary embodiments of the present invention. However, the present invention may be embodied in a variety of alternative forms, and should not be construed as being limited to the embodiments set forth herein.

[0051] It should be understood that, unless otherwise expressly specified or limited, the corresponding terms should be understood in a broad sense. For example, "connection" can refer to a fixed connection, a detachable connection, or an integral connection; it can refer to a direct connection, an indirect connection through an intermediate medium, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the embodiments based on specific circumstances.

[0052] In the following description, certain details are provided to facilitate a thorough understanding of the example embodiments. However, one skilled in the art will appreciate that the example embodiments may be practiced without these specific details. For example, devices may be shown in block diagrams to avoid obscuring the examples with unnecessary detail. In other embodiments, well-known processes, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.

[0053] Example 1:

[0054] This embodiment provides a cloud warehouse management method, which can be applied to corresponding cloud management systems, such as Figure 1 As shown, the method includes the following steps:

[0055] S1. Obtain the verification request information sent by the requesting end, and extract the warehouse number and the requesting end information set from the verification request information, wherein the requesting end information set includes biometric verification information, requesting end website information and verification credential information.

[0056] In specific implementations, when a requester needs to access the cloud management system through the requesting end to manage a cloud warehouse, they first send a verification request message to the cloud management system through the requesting end. After receiving the verification request message, the cloud management system can parse it to extract the warehouse number and the requesting end information set. The requesting end information set includes biometric verification information, requesting end website information, and verification credential information. The biometric verification information can include fingerprint recognition information or facial recognition information, the requesting end website information can include an IP address, and the verification credential information can include the applicant's identity credential code.

[0057] S2. Match the corresponding target cloud warehouse according to the warehouse number, and retrieve the verification vector set of the target cloud warehouse, where the verification vector set includes several verification vectors.

[0058] During specific implementation, the cloud management system can match the corresponding target cloud warehouse according to the warehouse number, and then retrieve the verification vector set associated with the target cloud warehouse from the database. The verification vector set contains several verification vectors, each of which corresponds to different requester information verification requirements.

[0059] S3. Vectorize the biometric verification information, the requesting end URL information, and the verification credential information respectively to obtain a biometric feature vector, an address feature vector, and a credential feature vector.

[0060] In specific implementations, the cloud management system can extract biometric features from biometric verification information to obtain biometric parameters, and then use principal component analysis to perform feature mapping on the biometric parameters to obtain a biometric feature vector. Linear transformation processing can be performed on each segment of the requesting URL information to obtain mapping data corresponding to each segment of the URL data, and the mapping data can be sequentially combined to obtain an address feature vector. Encoding conversion processing can be performed on each character of the verification credential information to obtain the corresponding encoding data, and the encoding data can be sequentially combined to obtain a credential feature vector.

[0061] S4. Use the biometric feature vector, the address feature vector, and the credential feature vector to form a dynamic feature vector, and calculate the matching degree between the dynamic feature vector and each verification vector in the verification vector set.

[0062] During specific implementation, the cloud management system combines the biometric feature vector, address feature vector and credential feature vector in sequence in the row direction or column direction to obtain an initial combination vector, and then performs data normalization processing on each component of the initial combination vector to obtain a dynamic feature vector.

[0063] After obtaining the dynamic feature vector, the cloud management system substitutes the dynamic feature vector and the corresponding verification vector into a preset matching degree formula to calculate the matching degree between the dynamic feature vector and the corresponding verification vector. The matching degree formula is:

[0064]

[0065] Among them, P represents the matching degree between the dynamic feature vector and the verification vector, i is the vector component number of the dynamic feature vector and the verification vector, n is the number of components of the dynamic feature vector and the verification vector, x i Characterizes the i-th component of the dynamic eigenvector, y i Represents the i-th component of the validation vector.

[0066] S5. When the matching degree between the dynamic feature vector and a verification vector in the verification vector set reaches the set matching degree condition, the permission type table associated with the corresponding verification vector is retrieved, and the verification request is determined to be passed, and the verification request passing information is fed back to the requesting end.

[0067] In specific implementations, when the match between the dynamic feature vector and a verification vector in the verification vector set exceeds a set match threshold, the cloud management system determines that the verification request has been approved and sends feedback to the requesting end. Simultaneously, the corresponding verification vector number is determined and the permission type table associated with that verification vector number is retrieved, which contains several permission type codes.

[0068] S6. Receive the operation request information sent by the requesting end, parse the operation request information, and obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction.

[0069] During specific implementation, the cloud management system first performs hash calculation on the verification credential information to obtain the corresponding hash value, and uses the calculated hash value as the decryption key; then the decryption key is used to decrypt the operation request information to obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction.

[0070] S7. When the operation type code is consistent with a certain permission type code in the permission type table, perform corresponding management operations on the target cloud warehouse in response to the warehouse operation instruction.

[0071] In specific implementations, when the operation type code matches a permission type code in the permission type table, the requester's warehouse operation instruction is deemed to have passed permission verification. The cloud management system then responds to the warehouse operation instruction and performs corresponding management operations on the target cloud warehouse, such as modifying, adding, or deleting inventory information and supply chain data in the target cloud warehouse, to achieve efficient and reliable cloud warehouse information management. After completing the management operation on the target cloud warehouse in response to the warehouse operation instruction, the cloud management system sends back verification completion information to the requester and disconnects from the requester upon receiving the request completion information sent by the requester.

[0072] This method uses a dual security verification mechanism of request verification and permission matching to strictly control the access rights of the requesting end. While efficiently completing cloud warehouse management operations, it can effectively prevent the leakage or tampering of sensitive data in the cloud warehouse and ensure the security of enterprise cloud warehouse information.

[0073] Example 2:

[0074] This embodiment provides a cloud warehouse management system, such as Figure 2 As shown, it includes a data acquisition unit, a warehouse matching unit, a feature extraction unit, a feature matching unit, a request verification unit, an operation parsing unit and an operation execution unit, wherein:

[0075] A data acquisition unit is used to acquire the verification request information sent by the requesting end, and extract the warehouse number and the requesting end information set from the verification request information, wherein the requesting end information set includes biometric verification information, requesting end website information and verification credential information;

[0076] A warehouse matching unit, configured to match a corresponding target cloud warehouse according to the warehouse number and retrieve a verification vector set of the target cloud warehouse, wherein the verification vector set includes a plurality of verification vectors;

[0077] A feature extraction unit is used to vectorize the biometric verification information, the requesting end URL information and the verification credential information to obtain a biometric feature vector, an address feature vector and a credential feature vector;

[0078] a feature matching unit, configured to form a dynamic feature vector using the biometric feature vector, the address feature vector, and the credential feature vector, and to calculate a matching degree between the dynamic feature vector and each verification vector in the verification vector set;

[0079] A request verification unit is configured to retrieve the permission type table associated with the corresponding verification vector when the matching degree between the dynamic feature vector and a verification vector in the verification vector set meets a set matching degree condition, determine whether the verification request is passed, and feedback the verification request passing information to the requesting end;

[0080] An operation parsing unit is used to receive the operation request information sent by the requesting end, parse the operation request information, and obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction;

[0081] The operation execution unit is used to perform corresponding management operations on the target cloud warehouse in response to the warehouse operation instruction when the operation type code is consistent with a permission type code in the permission type table.

[0082] Example 3:

[0083] This embodiment provides a cloud warehouse management system, such as Figure 3 As shown, at the hardware level, it includes:

[0084] Data interface, used to establish data connection between the processor and the request end;

[0085] a memory for storing instructions;

[0086] The processor is used to read the instructions stored in the memory and execute the cloud warehouse management method in Example 1 according to the instructions.

[0087] Optionally, the system further includes an internal bus, through which the processor, memory, and data interface can be interconnected. The internal bus can be a PCIe (Peripheral Component Interconnect Express) bus, and the bus can be divided into an address bus, a data bus, a control bus, etc. The memory can include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in first-out memory (FIFO), and / or first-in last-out memory (FILO). The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0088] Example 4:

[0089] This embodiment provides a computer-readable storage medium having instructions stored thereon. When the instructions are executed on a computer, the computer is caused to execute the cloud warehouse management method of Embodiment 1. The computer-readable storage medium refers to a data storage medium, which may include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash drive, and / or a memory stick. The computer may be a general-purpose computer, a dedicated computer, a computer network, or other programmable device.

[0090] This embodiment further provides a computer program product, which, when executed on a computer, executes the cloud warehouse management method in Embodiment 1. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0091] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A cloud warehouse management method, characterized in that: include: Obtaining verification request information sent by the requesting end, and extracting the warehouse number and the requesting end information set from the verification request information, wherein the requesting end information set includes biometric verification information, requesting end website information, and verification credential information; Match the corresponding target cloud warehouse according to the warehouse number, and retrieve the verification vector set of the target cloud warehouse, where the verification vector set includes several verification vectors; Vectorize the biometric verification information, the requesting end URL information, and the verification credential information to obtain a biometric feature vector, an address feature vector, and a credential feature vector; A dynamic feature vector is formed using the biometric feature vector, the address feature vector, and the credential feature vector, and the matching degree between the dynamic feature vector and each verification vector in the verification vector set is calculated; When the matching degree between the dynamic feature vector and a verification vector in the verification vector set reaches the set matching degree condition, the permission type table associated with the corresponding verification vector is retrieved, and the verification request is determined to be passed, and the verification request passing information is fed back to the requesting end; Receive the operation request information sent by the requesting end, parse the operation request information, and obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction; When the operation type code is consistent with a certain permission type code in the permission type table, a corresponding management operation is performed on the target cloud warehouse in response to the warehouse operation instruction.

2. A cloud warehouse management method according to claim 1, characterized in that: The biometric verification information, the requesting end website information and the verification credential information are respectively vectorized to obtain a biometric feature vector, an address feature vector and a credential feature vector, including: Extracting biometric features from the biometric verification information to obtain biometric parameters, and performing feature mapping on the biometric parameters using principal component analysis to obtain a biometric vector; Performing linear transformation on each segment of the URL data of the requesting end URL information to obtain mapping data corresponding to each segment of the URL data, and combining each mapping data in sequence to obtain an address feature vector; Perform encoding conversion processing on each character of the verification credential information to obtain the encoding data corresponding to each character, and combine the encoding data in sequence to obtain the credential feature vector.

3. A cloud warehouse management method according to claim 1, characterized in that: The dynamic feature vector is formed by using the biometric feature vector, the address feature vector and the credential feature vector, including: Combine the biometric feature vector, the address feature vector, and the credential feature vector in sequence in the row direction or the column direction to obtain an initial combination vector; The components of the initial combination vector are subjected to data normalization to obtain the dynamic feature vector.

4. A cloud warehouse management method according to claim 1, characterized in that: The calculating of the matching degree between the dynamic feature vector and each verification vector in the verification vector set includes: Substitute the dynamic feature vector and the corresponding verification vector into the preset matching degree formula to calculate the matching degree between the dynamic feature vector and the corresponding verification vector. The matching degree formula is: Among them, P represents the matching degree between the dynamic feature vector and the verification vector, i is the vector component number of the dynamic feature vector and the verification vector, n is the number of components of the dynamic feature vector and the verification vector, x i Characterizes the i-th component of the dynamic eigenvector, y i Represents the i-th component of the validation vector.

5. A cloud warehouse management method according to claim 1, characterized in that: When the matching degree between the dynamic feature vector and a verification vector in the verification vector set reaches a set matching degree condition, the permission type table associated with the corresponding verification vector is retrieved, including: When the matching degree between the dynamic feature vector and a verification vector in the verification vector set exceeds a set matching degree threshold, the number of the corresponding verification vector is determined, and the permission type table associated with the number of the corresponding verification vector is retrieved, wherein the permission type table includes several permission type codes.

6. A cloud warehouse management method according to claim 1, characterized in that: The operation request information is parsed to obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction, including: Perform hash calculation on the verification credential information to obtain the corresponding hash value, and use the calculated hash value as the decryption key; The operation request information is decrypted using the decryption key to obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction.

7. A cloud warehouse management method according to claim 1, characterized in that: The method further comprises: After completing the management operation on the target cloud warehouse in response to the warehouse operation instruction, the verification operation completion information is fed back to the requesting end, and the connection with the requesting end is disconnected after receiving the request end information sent by the requesting end.

8. A cloud warehouse management system, characterized in that: It includes a data acquisition unit, a warehouse matching unit, a feature extraction unit, a feature matching unit, a request verification unit, an operation parsing unit, and an operation execution unit, wherein: A data acquisition unit is used to acquire the verification request information sent by the requesting end, and extract the warehouse number and the requesting end information set from the verification request information, wherein the requesting end information set includes biometric verification information, requesting end website information and verification credential information; A warehouse matching unit, configured to match a corresponding target cloud warehouse according to the warehouse number and retrieve a verification vector set of the target cloud warehouse, wherein the verification vector set includes a plurality of verification vectors; A feature extraction unit is used to vectorize the biometric verification information, the requesting end URL information and the verification credential information to obtain a biometric feature vector, an address feature vector and a credential feature vector; a feature matching unit, configured to form a dynamic feature vector using the biometric feature vector, the address feature vector, and the credential feature vector, and to calculate a matching degree between the dynamic feature vector and each verification vector in the verification vector set; A request verification unit is configured to retrieve the permission type table associated with the corresponding verification vector when the matching degree between the dynamic feature vector and a verification vector in the verification vector set meets a set matching degree condition, determine whether the verification request is passed, and feedback the verification request passing information to the requesting end; An operation parsing unit is used to receive the operation request information sent by the requesting end, parse the operation request information, and obtain the warehouse operation instruction and the operation type code corresponding to the warehouse operation instruction; The operation execution unit is used to perform corresponding management operations on the target cloud warehouse in response to the warehouse operation instruction when the operation type code is consistent with a permission type code in the permission type table.

9. A cloud warehouse management system, characterized in that: include: a memory for storing instructions; A processor is used to read the instructions stored in the memory and execute the cloud warehouse management method according to any one of claims 1 to 7 according to the instructions.

10. A computer program product, characterized in that When the computer program product is run on a computer, the cloud warehouse management method according to any one of claims 1 to 7 is executed.

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