Material flow management method, device, equipment and storage medium based on big data

Abstract

The present invention relates to the field of data management, and discloses a material circulation management method, device, equipment and storage medium based on big data. The method includes: when a circulation instruction exists at the current level, determining a target task according to the circulation instruction; obtaining a user identifier of the current level, and generating material query information based on the user identifier and the target task; judging whether the current level meets the permission conditions of a preset access control tree according to the material query information; if so, judging the current level to be an execution level, and pushing the material data corresponding to the target task to the execution level. Since the present invention generates material query information by combining the determined target task with the user identifier, and then can judge whether it meets the permission conditions of the preset access control tree according to the material query information, and pushes the material data when the current level is judged to be the execution level, it can realize the permission control of each circulation level and ensure the security of the data during the material circulation process.

Description

Technical Field

[0001] The present invention relates to the field of data management technology, and in particular to a material flow management method, device, equipment and storage medium based on big data. Background Art

[0002] The material circulation process covers multiple links such as the procurement, production, transportation, storage and sales of goods. The purpose of material circulation is to achieve the liquidity of goods or products, so it requires the coordinated cooperation of multiple links to promote the circulation of materials.

[0003] Each of these links can be considered a different level of circulation. However, due to differences in the users at each level, the available material data must also differ to ensure data privacy and prevent data leakage. The existing material circulation process simply transmits data level by level, failing to account for the differences in data access permissions among different users and posing certain security risks.

[0004] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is related technology. Summary of the Invention

[0005] The main purpose of the present invention is to provide a material flow management method, device, equipment and storage medium based on big data, aiming to solve the technical problem that the existing material flow process only transmits data step by step, is difficult to take into account the differences in data acquisition permissions of different users, and has certain security risks.

[0006] To achieve the above objectives, the present invention provides a material flow management method based on big data, which includes the following steps:

[0007] When a transfer instruction exists at the current level, determining the target task according to the transfer instruction;

[0008] Obtaining a user identifier of the current level, and generating material query information based on the user identifier and the target task;

[0009] Determining whether the current level meets the permission conditions of the preset access control tree according to the material query information;

[0010] If so, the current level is determined to be the execution level, and the material data corresponding to the target task is pushed to the execution level.

[0011] Optionally, before determining whether the current level meets the permission conditions of a preset access control tree according to the material query information, the method includes:

[0012] Get the hierarchical division information of the current system;

[0013] generating a task execution plan according to the hierarchical division information, wherein the task execution plan includes a plurality of flow levels;

[0014] Based on each of the flow levels, a preset access control tree corresponding to each of the flow levels is generated.

[0015] Optionally, generating a preset access control tree corresponding to each of the flow levels based on each of the flow levels includes:

[0016] Obtaining a basic property set of the current system;

[0017] Based on the flow levels, the basic attribute set is updated to obtain a level attribute set corresponding to each flow level;

[0018] The preset access control tree is constructed according to the hierarchical attribute set.

[0019] Optionally, the preset access control tree includes a root node, non-leaf nodes, and leaf nodes, and constructing the preset access control tree according to the hierarchical attribute set includes:

[0020] Determining an authority key of the transfer level, and defining the root node according to the authority key;

[0021] Defining the non-leaf node according to a preset threshold condition;

[0022] Acquire active attribute information in the hierarchical attribute set, and define the leaf node according to the active attribute information;

[0023] The preset access control tree is determined according to the root node, the non-leaf nodes, and the leaf nodes.

[0024] Optionally, judging whether the current level meets the permission conditions of a preset access control tree according to the material query information includes:

[0025] Generate a plurality of hierarchical attribute tags according to the material query information;

[0026] Comparing each of the hierarchical attribute labels with the leaf nodes in the preset access control tree;

[0027] It is determined whether the current level meets the permission conditions based on the comparison result.

[0028] Optionally, if yes, determining that the current level is the execution level, and pushing the material data corresponding to the target task to the execution level includes:

[0029] When the current level meets the permission condition, determining that the current level is an execution level;

[0030] The material data corresponding to the target task is pushed to the execution layer, so that the execution layer obtains the material data through the authority key.

[0031] Optionally, before pushing the material data corresponding to the target task to the execution layer so that the execution layer obtains the material data through the authority key, the process includes:

[0032] Obtaining a flow data set of the current system;

[0033] Determining material data corresponding to the target task in the circulation data set;

[0034] Encrypting the material data using a preset encryption method;

[0035] Accordingly, the pushing of the material data corresponding to the target task to the execution layer so that the execution layer obtains the material data through the authority key includes:

[0036] The encrypted material data is pushed to the execution layer, so that the execution layer decrypts the material data using the authority key to complete the target task.

[0037] In addition, to achieve the above-mentioned purpose, the present invention also proposes a material flow management device based on big data, the device comprising:

[0038] A task determination module, configured to determine a target task according to a transfer instruction when a transfer instruction exists at the current level;

[0039] an identification determination module, configured to obtain a user identification of the current level and generate material query information based on the user identification and the target task;

[0040] An authority judgment module is used to judge whether the current level meets the authority conditions of the preset access control tree according to the material query information;

[0041] The data acquisition module is used to determine that the current level is the execution level and push the material data corresponding to the target task to the execution level.

[0042] In addition, to achieve the above-mentioned purpose, the present invention also proposes a material flow management device based on big data, which includes: a memory, a processor, and a material flow management program based on big data stored on the memory and runnable on the processor, and the material flow management program based on big data is configured to implement the steps of the material flow management method based on big data as described above.

[0043] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a material flow management program based on big data is stored. When the material flow management program based on big data is executed by a processor, the steps of the material flow management method based on big data as described above are implemented.

[0044] When a transfer instruction exists at the current level, the present invention determines the target task according to the transfer instruction; obtains the user ID of the current level, and generates material query information based on the user ID and the target task; determines whether the current level meets the permission conditions of the preset access control tree according to the material query information; if so, determines that the current level is the execution level, and pushes the material data corresponding to the target task to the execution level. Because the present invention generates material query information by combining the determined target task with the user ID, and then determines whether it meets the permission conditions of the preset access control tree according to the material query information, and pushes the material data when the current level that meets the conditions is determined to be the execution level, it can achieve permission control of each transfer level and ensure the security of data during the material transfer process. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a schematic diagram of the structure of a material flow management device based on big data in the hardware operating environment involved in the embodiment of the present invention;

[0046] Figure 2 This is a flow chart of the first embodiment of the material flow management method based on big data of the present invention;

[0047] Figure 3 This is a flow chart of a second embodiment of the material flow management method based on big data of the present invention;

[0048] Figure 4 This is a flow chart of a third embodiment of the material flow management method based on big data of the present invention;

[0049] Figure 5 This is a structural block diagram of the first embodiment of the material flow management device based on big data of the present invention.

[0050] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0051] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0052] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a material flow management device based on big data in the hardware operating environment involved in the embodiment of the present invention.

[0053] like Figure 1 As shown, the material flow management device based on big data may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WI-FI) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM) or a stable non-volatile memory (NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0054] Those skilled in the art will understand that Figure 1 The structure shown in does not constitute a limitation on the material flow management equipment based on big data, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0055] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a material flow management program based on big data.

[0056] exist Figure 1 In the material circulation management device based on big data shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the material circulation management device based on big data of the present invention can be set in the material circulation management device based on big data, and the material circulation management device based on big data calls the material circulation management program based on big data stored in the memory 1005 through the processor 1001, and executes the material circulation management method based on big data provided by the embodiment of the present invention.

[0057] The embodiment of the present invention provides a material flow management method based on big data, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the material flow management method based on big data of the present invention.

[0058] In this embodiment, the material flow management method based on big data includes the following steps:

[0059] Step S10: When a transfer instruction exists at the current level, a target task is determined according to the transfer instruction.

[0060] It should be noted that the method of this embodiment can be applied to the scenario of authority control of each circulation level in the material circulation system, and can also be applied to other systems that require hierarchical data transmission. The execution subject of the method of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a mobile phone, tablet computer, personal computer, etc., and can also be other electronic devices that realize the same or similar functions. The following takes the above-mentioned big data-based material circulation management device (hereinafter referred to as "management device") as an example to illustrate this embodiment and the following embodiments.

[0061] It should be noted that in the material flow system of the supply chain, the process of goods or products from the producer to the end user covers multiple links such as procurement, production, transportation, storage, and sales. These different links can be regarded as different flow levels. Different flow levels require different operations on the flow data in the current system, such as viewing data, editing data, and setting the next flow level. Therefore, different flow levels can have flow instructions corresponding to different target tasks.

[0062] It should also be noted that this transfer instruction can be initiated by a user at the current level, for example, to query the planned purchase quantity of item A in the current system. It can also be received as an instruction from a previous transfer level, for example, to determine the actual purchase quantity of item A. This transfer instruction can clarify the specific target task operation that the current level needs to perform.

[0063] Step S20: Obtain the user identification of the current level, and generate material query information based on the user identification and the target task.

[0064] It should be noted that the current system can be set up with a login window to clarify the specific operating users of the target person at different flow levels, where each operating user has a unique user identification, such as user ID number, user real name, etc., and identity authentication information such as face or iris can also be entered for different operating users as specific information of the user identification.

[0065] It should be noted that the material query information may be attribute information in the current system, such as the application scenario of the current system, the network environment of each flow level in the current system, and the like.

[0066] In a specific implementation, the management device can determine the specific operating user who performs the target task at the flow level in the current system, as well as the network environment in which the operating user is located (for example, whether it is a public network) based on the user identifier and the target task, and jointly determine the material query information.

[0067] Step S30: determining whether the current level meets the permission conditions of the preset access control tree according to the material query information.

[0068] It should be noted that the current system may include different flow levels, and preset access control trees corresponding to the flow levels may be set according to the different flow levels. Therefore, before step S30, the following steps may also be included:

[0069] Step S01: Obtain the hierarchical division information of the current system.

[0070] Step S02: Generate a task execution plan according to the hierarchical division information, wherein the task execution plan includes several flow levels.

[0071] It should be noted that the current system can include all the circulation levels that material data can pass through. Users can select several circulation levels from all the circulation levels based on personalized needs as all the levels to complete the material circulation. For example, the current system can include all the circulation levels A to Z. Users can select A to G as the circulation levels in the task execution plan based on actual needs, and specifically set the circulation order of different circulation levels, for example, set the order to AFGFB.

[0072] Step S03: Based on each of the flow levels, a preset access control tree corresponding to each of the flow levels is generated.

[0073] It should be noted that the preset access control tree can be a pre-built tree-shaped access control structure, and each preset access control tree consists of a root node, non-leaf nodes and leaf nodes, where the root node can be the final accessible data, and the leaf nodes and non-leaf nodes constitute the threshold judgment conditions.

[0074] It should also be noted that the data corresponding to the non-leaf nodes can be extracted from the material query information to determine whether the material query information meets the threshold judgment conditions determined by the leaf node and the non-leaf node, that is, to determine whether the current level can pass through the preset access control tree to obtain the accessible data at the root node, that is, to obtain the authority to execute the target task.

[0075] In a specific implementation, the management device can set up a preset access control tree corresponding to each flow level based on the attribute characteristics of different flow levels, so as to realize access permission control for different levels.

[0076] Step S40: If yes, the current level is determined to be the execution level, and the material data corresponding to the target task is pushed to the execution level.

[0077] It should be noted that if the current level meets the permission conditions of the preset access control tree, the current level can be determined as the execution level that can execute the target task, and the execution level has the permission to obtain the corresponding material data.

[0078] In a specific implementation, when the material query information passes the permission conditions set by the preset access control tree of the current level, the management device determines that the current level is the execution level, and pushes the material data corresponding to the target task to the current level, so that the operator at the current level can perform the operation process required for the target task on the material data.

[0079] This embodiment determines the target task according to the transfer instruction when there is a transfer instruction at the current level; obtains the user ID of the current level, and generates material query information based on the user ID and the target task; determines whether the current level meets the permission conditions of the preset access control tree based on the material query information; if so, determines that the current level is the execution level, and pushes the material data corresponding to the target task to the execution level. Because this embodiment generates material query information by combining the determined target task with the user ID, and can then determine whether it meets the permission conditions of the preset access control tree based on the material query information, and pushes the material data when the current level that meets the conditions is determined to be the execution level, it can achieve permission control of each transfer level and ensure the security of data during the material transfer process.

[0080] refer to Figure 3 , Figure 3 This is a flow chart of the second embodiment of the material flow management method based on big data of the present invention.

[0081] Based on the above embodiment, in this embodiment, in order to specifically construct preset access control trees of different flow levels, step S03 further includes:

[0082] Step S031: Acquire the basic attribute set of the current system.

[0083] It can be understood that the application scenario of the current system, the network environment information on which the current system depends, or the data format type, encryption transmission protocol of the data flowing in the current system and other relevant data of the current system can be obtained to extract various basic attributes and form a basic attribute set.

[0084] Step S032: Based on the flow levels, the basic attribute set is updated to obtain a hierarchical attribute set corresponding to each flow level;

[0085] It should also be noted that since different flow levels have different functions in the entire task execution plan, different flow levels can have various level attributes corresponding to the flow level. For example, the network environment of this flow level is required to be a private network, and the specific operation user of this flow level is required to log in less than 3 times within a preset time period.

[0086] In a specific implementation, each flow level can be further limited and updated based on the basic attributes of the current system. Obtaining the attributes of each level means obtaining the level attribute set corresponding to each flow level.

[0087] Step S033: constructing the preset access control tree according to the hierarchical attribute set.

[0088] It should be noted that, since the preset access control tree includes a root node, non-leaf nodes, and leaf nodes, in order to construct the preset access control tree, step S033 includes:

[0089] Step S0331: Determine the authority key of the flow level and define the root node according to the authority key.

[0090] It is understood that the permission key can be used to indicate the permission information for the specific operating user at the current level to obtain the material data corresponding to the target task. Since the root node is the last node in the preset access control tree, once the permission key at the root node is obtained, it can be used as the judgment standard for material query information to pass the preset access control tree.

[0091] Step S0332: defining the non-leaf nodes according to a preset threshold condition.

[0092] Step S0333: Obtain active attribute information in the hierarchical attribute set, and define the leaf node according to the active attribute information.

[0093] It is understandable that the active attribute information can be a number of hierarchical attributes extracted from the above-mentioned hierarchical attribute set, and each hierarchical attribute is defined as a leaf node, and a threshold restriction condition or a logical relationship restriction condition based on the hierarchical attribute can be preset as a preset threshold condition. The preset threshold condition of a non-leaf node can be represented by (n, t). For example, if the non-leaf node A is (3, 2), and the lower layer of the non-leaf node is a leaf node, then the threshold condition of the non-leaf node A can be: there are 3 leaf nodes under the non-leaf node A. When the material query information of the current layer meets the hierarchical attributes of at least 2 leaf nodes, the non-leaf node A is passed through to enter the non-leaf node (or root node) of the upper layer of the non-leaf node A.

[0094] Step S0334: Determine the preset access control tree according to the root node, the non-leaf nodes and the leaf nodes.

[0095] It is understandable that, since non-leaf nodes can be set layer by layer, the number of layers of non-leaf nodes can be personalized based on different security requirements.

[0096] In a specific implementation, when the root node is defined using an authority key and the preset threshold conditions for non-leaf nodes at different levels are set, several hierarchical attributes in the above hierarchical attribute set are used as the actual meaning of each leaf node to construct a preset access control tree for a certain flow level. The preset access control tree for each different flow level is constructed in the same manner to achieve differentiated permission settings at each flow level in the current system.

[0097] Furthermore, in order to specifically illustrate how to determine the authority of the current level in the preset access control tree based on the material query information, step S30 includes:

[0098] Step S301: Generate a plurality of hierarchical attribute tags according to the material query information.

[0099] Step S302: Compare each of the hierarchical attribute labels with the leaf nodes in the preset access control tree.

[0100] It is understandable that, in order to facilitate comparison, the material query information can be extracted to obtain several hierarchical attribute tags, and the hierarchical attribute tags can include attribute information of the current level and attribute information of the specific operation user.

[0101] Step S303: Determine whether the current level meets the permission conditions based on the comparison result.

[0102] In a specific implementation, several hierarchical attribute tags extracted from the material query information are compared with the leaf nodes to determine whether each of the hierarchical attribute tags exists or meets the hierarchical attributes corresponding to the leaf nodes. If the number of hierarchical attribute tags that exist or meet the requirements is not less than the preset threshold conditions in the non-leaf nodes, the system passes through the non-leaf nodes of this layer and enters the non-leaf nodes of the next layer. When all non-leaf nodes are passed and the root node is obtained, the permission key at the root node is obtained, and it can be determined that the current layer meets the permission conditions of the preset access control tree.

[0103] This embodiment obtains the basic attribute set of the current system; updates the basic attribute set based on the circulation level to obtain the hierarchical attribute set corresponding to each circulation level; and constructs the preset access control tree based on the hierarchical attribute set. Specifically, the authority key of the circulation level is determined, and the root node is defined based on the authority key; the non-leaf nodes are defined based on the preset threshold conditions; the active attribute information in the hierarchical attribute set is obtained, and the leaf nodes are defined based on the active attribute information; and the preset access control tree is determined based on the root node, the non-leaf nodes, and the leaf nodes. Since this embodiment uses the authority key to define the root node and sets the preset threshold conditions for the non-leaf nodes at different levels, several hierarchical attributes in the hierarchical attribute set are used as the actual meaning of each leaf node, thereby constructing the preset access control tree for the circulation level. This allows the management device to perform permission access control at the current level through material query information, realizing differentiated permission settings at each circulation level in the current system, which is beneficial to further improving the security of the current system and preventing data leakage.

[0104] refer to Figure 4 , Figure 4 This is a flow chart of the third embodiment of the material flow management method based on big data of the present invention.

[0105] Based on the above embodiment, in order to further ensure the privacy of data flowing in the current system, step S40 includes:

[0106] Step S401: When the current level meets the permission condition, determine that the current level is an execution level.

[0107] In a specific implementation, when the current level meets the permission conditions of the preset access control tree, the permission key at the root node can be obtained, and the current level is determined to be the execution level that can execute the target task.

[0108] Step S402: Pushing the material data corresponding to the target task to the execution layer, so that the execution layer obtains the material data through the authority key.

[0109] It should also be noted that, in order to ensure the security of the material data, the material data may be encrypted before being pushed. Therefore, before step S402, the following steps may also be included:

[0110] Step S001: Acquire the current system's circulating data set.

[0111] Step S002: Determine the material data corresponding to the target task in the circulation data set.

[0112] In a specific implementation, the management device can obtain all the material data existing in the current system, namely the flow data set, and when the current level meets the permission conditions, extract the material data required for the target task to be executed at the current level.

[0113] Step S003: Encrypt the material data using a preset encryption method.

[0114] It is understandable that the preset encryption method can be a symmetric encryption method, which can use the same key for encryption and decryption. Therefore, accordingly, step S402 includes:

[0115] Step S402 ′: Push the encrypted material data to the execution layer, so that the execution layer decrypts the material data using the authority key to complete the target task.

[0116] In a specific implementation, the authority key may include the key information in the above-mentioned preset encryption method. Therefore, when the encrypted material data is pushed to the execution level, the execution level may decrypt the material data through the authority key, and then perform subsequent processing operations to complete the target task.

[0117] In this embodiment, when the current level meets the permission conditions, the current level is determined to be the execution level. Furthermore, the material data is pre-encrypted using a preset encryption method. When the encrypted material data is pushed to the execution level, the execution level can decrypt the material data using the permission key and perform subsequent processing operations to complete the target task. This helps further ensure the security of material data during transmission and reduces the risk of data leakage in the current system.

[0118] In addition, an embodiment of the present invention also proposes a storage medium, on which a material flow management program based on big data is stored. When the material flow management program based on big data is executed by a processor, the steps of the material flow management method based on big data as described above are implemented.

[0119] In addition, reference Figure 5 , Figure 5 This is a structural block diagram of the first embodiment of the material circulation management device based on big data of the present invention. The present invention also proposes a material circulation management device based on big data, the device comprising:

[0120] The task determination module 501 is configured to determine a target task according to a transfer instruction when a transfer instruction exists at the current level;

[0121] An identification determination module 502 is configured to obtain a user identification of the current level and generate material query information based on the user identification and the target task;

[0122] The authority determination module 503 is used to determine whether the current level meets the authority conditions of the preset access control tree according to the material query information;

[0123] The data acquisition module 504 is configured to determine that if so, the current level is the execution level, and push the material data corresponding to the target task to the execution level.

[0124] Furthermore, the authority judgment module 503 is also used to obtain the hierarchical division information of the current system; generate a task execution plan based on the hierarchical division information, wherein the task execution plan includes several flow levels; and based on each of the flow levels, generate a preset access control tree corresponding to each of the flow levels.

[0125] This embodiment determines the target task according to the transfer instruction when there is a transfer instruction at the current level; obtains the user ID of the current level, and generates material query information based on the user ID and the target task; determines whether the current level meets the permission conditions of the preset access control tree based on the material query information; if so, determines that the current level is the execution level, and pushes the material data corresponding to the target task to the execution level. Because this embodiment generates material query information by combining the determined target task with the user ID, and can then determine whether it meets the permission conditions of the preset access control tree based on the material query information, and pushes the material data when the current level that meets the conditions is determined to be the execution level, it can achieve permission control of each transfer level and ensure the security of data during the material transfer process.

[0126] Based on the above-mentioned first embodiment of the material circulation management device based on big data of the present invention, a second embodiment of the material circulation management device based on big data of the present invention is proposed.

[0127] In this embodiment, further, the permission judgment module 503 is also used to obtain the basic attribute set of the current system; based on the flow hierarchy, the basic attribute set is updated to obtain the hierarchical attribute set corresponding to each of the flow hierarchies; and the preset access control tree is constructed according to the hierarchical attribute set.

[0128] Furthermore, the preset access control tree includes a root node, non-leaf nodes and leaf nodes; the authority judgment module 503 is also used to determine the authority key of the flow level, and define the root node according to the authority key; define the non-leaf node according to the preset threshold condition; obtain the positive attribute information in the hierarchical attribute set, and define the leaf node according to the positive attribute information; determine the preset access control tree according to the root node, the non-leaf node and the leaf node.

[0129] Furthermore, the permission judgment module 503 is also used to generate several hierarchical attribute labels based on the material query information; compare each of the hierarchical attribute labels with the leaf nodes in the preset access control tree; and judge whether the current level meets the permission conditions based on the comparison results.

[0130] Furthermore, the data acquisition module 504 is also used to determine that the current level is the execution level when the current level meets the permission conditions; and push the material data corresponding to the target task to the execution level so that the execution level obtains the material data through the permission key.

[0131] Furthermore, the data acquisition module 504 is also used to obtain the circulation data set of the current system; determine the material data corresponding to the target task in the circulation data set; encrypt the material data using a preset encryption method; and push the encrypted material data to the execution level, so that the execution level decrypts the material data through the authority key to complete the target task.

[0132] Other embodiments or specific implementation methods of the material circulation management device based on big data of the present invention can refer to the above-mentioned method embodiments and will not be repeated here.

[0133] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element referenced by the phrase "comprising a ... limited" does not preclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0134] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0135] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0136] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A material flow management method based on big data, characterized in that: The method comprises: When a transfer instruction exists at the current level, determining the target task according to the transfer instruction; Obtaining a user identifier of the current level, and generating material query information based on the user identifier and the target task; Determining whether the current level meets the permission conditions of a preset access control tree based on the material query information, the preset access control tree includes a root node, non-leaf nodes, and leaf nodes, and the permission conditions include a hierarchical attribute condition based on the leaf nodes and a preset threshold condition based on the non-leaf nodes; If so, the current level is determined to be the execution level, and the material data corresponding to the target task is encrypted and pushed to the execution level; Before determining whether the current level meets the permission conditions of the preset access control tree according to the material query information, the following steps are included: Get the hierarchical division information of the current system; generating a task execution plan according to the hierarchical division information, wherein the task execution plan includes a plurality of flow levels; Based on each of the flow levels, a preset access control tree corresponding to each of the flow levels is generated according to the basic attributes of the current system and the hierarchical attributes of each of the flow levels.

2. The material flow management method based on big data according to claim 1, characterized in that: The generating of a preset access control tree corresponding to each of the transfer levels based on each of the transfer levels includes: Obtaining a basic property set of the current system; Based on the flow levels, the basic attribute set is updated to obtain a level attribute set corresponding to each flow level; The preset access control tree is constructed according to the hierarchical attribute set.

3. The material flow management method based on big data according to claim 2, characterized in that: The step of constructing the preset access control tree according to the hierarchical attribute set includes: Determining an authority key of the transfer level, and defining the root node according to the authority key; Defining the non-leaf node according to a preset threshold condition; Acquire active attribute information in the hierarchical attribute set, and define the leaf node according to the active attribute information; The preset access control tree is determined according to the root node, the non-leaf nodes, and the leaf nodes.

4. The material flow management method based on big data according to claim 3, characterized in that: The determining, based on the material query information, whether the current level meets the permission conditions of the preset access control tree includes: Generate a plurality of hierarchical attribute tags according to the material query information; Comparing each of the hierarchical attribute labels with the leaf nodes in the preset access control tree; It is determined whether the current level meets the permission conditions based on the comparison result.

5. The material flow management method based on big data according to claim 4, characterized in that: If so, determining that the current level is the execution level, and pushing the material data corresponding to the target task to the execution level, including: When the current level meets the permission condition, determining that the current level is an execution level; The material data corresponding to the target task is pushed to the execution layer, so that the execution layer obtains the material data through the authority key.

6. The material flow management method based on big data according to claim 5, characterized in that: Before pushing the material data corresponding to the target task to the execution layer so that the execution layer obtains the material data through the authority key, the method includes: Obtaining a flow data set of the current system; Determining material data corresponding to the target task in the circulation data set; Encrypting the material data using a preset encryption method; Accordingly, the pushing of the material data corresponding to the target task to the execution layer so that the execution layer obtains the material data through the authority key includes: The encrypted material data is pushed to the execution layer, so that the execution layer decrypts the material data using the authority key to complete the target task.

7. A material flow management device based on big data, characterized in that: The device comprises: A task determination module, configured to determine a target task according to a transfer instruction when a transfer instruction exists at the current level; an identification determination module, configured to obtain a user identification of the current level and generate material query information based on the user identification and the target task; an authority determination module, configured to determine, based on the material query information, whether the current level meets the authority conditions of a preset access control tree, wherein the preset access control tree includes a root node, non-leaf nodes, and leaf nodes, and the authority conditions include a hierarchical attribute condition based on the leaf node and a preset threshold condition based on the non-leaf node; A data acquisition module is configured to, if yes, determine that the current level is the execution level, and encrypt and push the material data corresponding to the target task to the execution level; The identification determination module is also used to obtain the hierarchical division information of the current system; generate a task execution plan based on the hierarchical division information, wherein the task execution plan includes several flow levels; based on each of the flow levels, generate a preset access control tree corresponding to each of the flow levels according to the basic attributes of the current system and the hierarchical attributes of each of the flow levels.

8. A material flow management device based on big data, characterized in that: The device includes: a memory, a processor, and a big data-based material flow management program stored in the memory and executable on the processor, wherein the big data-based material flow management program is configured to implement the steps of the big data-based material flow management method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium stores a material circulation management program based on big data, and when the material circulation management program based on big data is executed by the processor, the steps of the material circulation management method based on big data as described in any one of claims 1 to 6 are implemented.

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