Enterprise information management method and system based on big data

Abstract

The invention provides an enterprise information management method and system based on big data, and the method comprises the steps: obtaining enterprise information sent by a user terminal, and carrying out the data desensitization of the enterprise information, so as to obtain preprocessed data; generating a corresponding security parameter based on the confidentiality level of the user terminal, randomly selecting the key server within a preset data processing interval, and performing validity verification on a random selection result; if the random selection result passes the validity verification, generating a secret value corresponding to the user terminal according to the random selection result; generating a corresponding system key according to the terminal identifier of the user terminal and the security parameter, and performing data encryption on the preprocessed data by using the system key to obtain encrypted data; and performing secondary encryption on the system key by using the secret value to obtain an encryption key, and generating corresponding enterprise encryption information according to the encryption data and the encryption key.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to an enterprise information management method and system based on big data. Background Art

[0002] With the continuous development of new information industries such as the Internet of Things and big data, traditional enterprise information will gradually become intelligent. Therefore, the most important issue to consider in enterprise information management is information encryption.

[0003] With the rapid development of enterprise information management, enterprise information contains a large amount of private information, such as employee information, business secrets, etc. Therefore, ensuring that this information is not leaked can ensure that enterprise information management is more secure; the current way of enterprise information management is usually personnel management. However, with the operation of the enterprise, the amount of information is gradually increasing, resulting in a sharp increase in workload, and it is impossible to dynamically ensure the management of enterprise information, affecting work efficiency. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide an enterprise information management method and system based on big data, so as to at least solve the deficiencies in the above-mentioned technology.

[0005] The present invention proposes an enterprise information management method based on big data, comprising: Acquire the enterprise information sent by the user terminal, and perform data desensitization on the enterprise information to obtain pre-processed data; Generate corresponding security parameters based on the confidentiality level of the user terminal, randomly select a key server within a preset data processing interval, and verify the validity of the random selection result; If the random selection result passes the validity verification, generating a secret value corresponding to the user terminal according to the random selection result; Generate a corresponding system key according to the terminal identification of the user terminal and the security parameter, and encrypt the pre-processed data using the system key to obtain encrypted data; The system key is encrypted twice using the secret value to obtain an encryption key, and corresponding enterprise encryption information is generated according to the encrypted data and the encryption key.

[0006] Furthermore, the steps of obtaining the enterprise information sent by the user terminal and desensitizing the enterprise information to obtain pre-processed data include: Annotating the data interface of the user terminal to determine the interface type of the user terminal, and parsing the enterprise type in the enterprise information; Corresponding data desensitization rules are determined according to the interface type and the enterprise type, and the enterprise information is desensitized using the data desensitization rules to obtain preprocessed data.

[0007] Further, the steps of generating corresponding security parameters based on the confidentiality level of the user terminal, randomly selecting a key server within a preset data processing interval, and verifying the validity of the random selection result include: Acquire a corresponding confidentiality level according to a user identification of the user terminal, and call a corresponding security parameter from a preset parameter database based on the confidentiality level; A key server is randomly selected within a preset data processing interval to obtain a random key, a key weight of the user terminal for the random key is constructed, and the key weight and the random key are verified for validity using a Lagrange difference algorithm.

[0008] Further, the step of generating a corresponding system key according to the terminal identification of the user terminal and the security parameter includes: Choose a prime number As a bilinear group , The order, for A generator of , and using As the corresponding bilinear map ; Randomly select two bits that are the same as the prime number A mutually prime random number is used, and a hash function is defined to generate a corresponding system key according to the terminal identifier of the user terminal, the security parameter and the random number.

[0009] Further, the steps of re-encrypting the system key using the secret value to obtain an encryption key, and generating corresponding enterprise encryption information according to the encrypted data and the encryption key include: The system key is re-encrypted using an attribute encryption algorithm and the secret value to access a corresponding structural attribute to obtain an encryption key; A corresponding random vector is determined, and the encrypted data and the encryption key are associated according to the random vector to generate corresponding enterprise encryption information.

[0010] The present invention also proposes an enterprise information management system based on big data, comprising: A data desensitization module is used to obtain the enterprise information sent by the user terminal and perform data desensitization on the enterprise information to obtain pre-processed data; A data verification module, used to generate corresponding security parameters based on the confidentiality level of the user terminal, and randomly select a key server within a preset data processing interval, and verify the validity of the random selection result; A result generating module, configured to generate a secret value corresponding to the user terminal according to the random selection result if the random selection result passes the validity verification; a primary encryption module, used to generate a corresponding system key according to the terminal identification of the user terminal and the security parameter, and to encrypt the preprocessed data using the system key to obtain encrypted data; The secondary encryption module is used to perform secondary encryption on the system key using the secret value to obtain an encryption key, and generate corresponding enterprise encryption information according to the encrypted data and the encryption key.

[0011] Furthermore, the data desensitization module includes: A data parsing unit, used to annotate the data interface of the user terminal to determine the interface type of the user terminal and parse out the enterprise type in the enterprise information; A data desensitization unit is used to determine corresponding data desensitization rules according to the interface type and the enterprise type, and use the data desensitization rules to desensitize the enterprise information to obtain pre-processed data.

[0012] Furthermore, the data verification module includes: A parameter calling unit, configured to obtain a corresponding confidentiality level according to a user identification of the user terminal, and call a corresponding security parameter from a preset parameter database based on the confidentiality level; The data verification unit is used to randomly select a key server within a preset data processing interval to obtain a random key, construct a key weight of the user terminal for the random key, and use a Lagrange difference algorithm to verify the validity of the key weight and the random key.

[0013] Furthermore, the primary encryption module is specifically used for: Choose a prime number As a bilinear group , The order, for A generator of , and using As the corresponding bilinear map ; Randomly select two bits that are the same as the prime number A mutually prime random number is used, and a hash function is defined to generate a corresponding system key according to the terminal identifier of the user terminal, the security parameter and the random number.

[0014] Furthermore, the secondary encryption module includes: A secondary encryption unit, used to perform secondary encryption on the system key using an attribute encryption algorithm and the secret value to access a corresponding structural attribute and obtain an encryption key; The data association unit is used to determine a corresponding random vector, and associate the encrypted data with the encryption key according to the random vector to generate corresponding enterprise encryption information.

[0015] The present invention also proposes a readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned enterprise information management method based on big data is implemented.

[0016] The present invention also proposes a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned enterprise information management method based on big data when executing the computer program.

[0017] The enterprise information management method and system based on big data in the present invention desensitizes enterprise information to avoid data abuse and leakage of sensitive information, generates security parameters using the confidentiality level of the user terminal, randomly selects the key server within a preset data processing interval, and uses validity verification to improve the stability and security of the key; generates a system key based on the terminal identification and security parameters of the user terminal, encrypts data using the system key, and re-encrypts the system key using the calculated secret value, so that information encryption has multiple encryption methods, thereby having a one-to-many advantage and being able to resist malicious collusion attacks by users. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of the enterprise information management method based on big data in the first embodiment of the present invention; Figure 2 for Figure 1 Detailed flow chart of step S101; Figure 3 for Figure 1 Detailed flow chart of step S102; Figure 4 for Figure 1 Detailed flow chart of step S105; Figure 5 is a structural block diagram of an enterprise information management system based on big data in a second embodiment of the present invention; Figure 6 FIG. 4 is a structural block diagram of a computer in a third embodiment of the present invention.

[0019] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0020] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0022] Embodiment 1 See also Figure 1 , which shows an enterprise information management method based on big data in the first embodiment of the present invention, and the method specifically includes steps S101 to S105: S101, obtaining enterprise information sent by a user terminal, and performing data desensitization on the enterprise information to obtain pre-processed data; For further information, see Figure 2 , the step S101 specifically includes steps S1011~S1012: S1011, annotating the data interface of the user terminal to determine the interface type of the user terminal, and parsing the enterprise type in the enterprise information; S1012, determining corresponding data desensitization rules according to the interface type and the enterprise type, and performing data desensitization on the enterprise information using the data desensitization rules to obtain preprocessed data.

[0023] In the specific implementation, the enterprise information sent by the user through the user terminal is obtained, wherein the user terminal includes but is not limited to mobile phones, computers, servers and other device terminals with communication functions, and the data interface of the user terminal is annotated, that is, the type of the data interface of the user terminal is determined, wherein the type of the data interface includes a list interface, a detail interface and a search interface, and the corresponding enterprise type is obtained according to the enterprise information sent by the user, including a limited liability company, a joint-stock limited liability company, an individual industrial and commercial household, a private partnership, etc.

[0024] Furthermore, according to the above-mentioned interface type and enterprise type, the data template that needs to be desensitized (i.e., data desensitization rule) is found in the corresponding database, and the data template is used to desensitize the above-mentioned enterprise information to avoid data abuse and leakage of sensitive information, as well as prevent adverse effects caused by improper data processing.

[0025] S102, generating corresponding security parameters based on the confidentiality level of the user terminal, and randomly selecting a key server within a preset data processing interval, and verifying the validity of the random selection result; For further information, see Figure 3 , the step S102 specifically includes steps S1021~S1022: S1021, acquiring a corresponding confidentiality level according to the user identification of the user terminal, and calling a corresponding security parameter from a preset parameter database based on the confidentiality level; S1022, randomly selecting a key server within a preset data processing interval to obtain a random key, constructing a key weight of the user terminal for the random key, and using a Lagrange difference algorithm to verify the validity of the key weight and the random key.

[0026] In specific implementation, the corresponding confidentiality level of the user terminal is determined according to the user identification of the user terminal, and the security parameters corresponding to the confidentiality level are found in the preset parameter database. It can be understood that the security parameters corresponding to different user identifications are stored in the parameter database. A random key is obtained by randomly selecting the key server within the preset data processing interval. It can be understood that when the preset data processing interval is exceeded, it means that the data processing has not responded or there is an abnormality in the data, and the corresponding error message will be transmitted so that the user can make corrections according to the error message, and random selection is performed from the key server, which can improve the stability of the key; the key weight of the user terminal for the random key is constructed, that is, the key share of the user terminal for the random key, and the Lagrange difference algorithm is used to verify the equality of the key weight and the random key. If both sides of the equation are equal, it means that the random selection result passes the validity verification. It can be understood that the security and reliability of the key can be ensured in this way.

[0027] S103, if the random selection result passes the validity verification, generating a secret value corresponding to the user terminal according to the random selection result; In specific implementation, if the random selection result passes the validity verification, the key server will generate a secret value corresponding to the user terminal based on the random selection result, that is, the sensitivity of the key server to authenticate and authorize the user terminal, which includes the identity or authorization information of the user terminal.

[0028] S104, generating a corresponding system key according to the terminal identification of the user terminal and the security parameter, and encrypting the pre-processed data using the system key to obtain encrypted data; Furthermore, the step S104 specifically includes: Choose a prime number As a bilinear group , The order, for A generator of , and using As the corresponding bilinear map ; Randomly select two bits that are the same as the prime number A mutually prime random number is used, and a hash function is defined to generate a corresponding system key according to the terminal identifier of the user terminal, the security parameter and the random number.

[0029] In the specific implementation, choose a prime number As a bilinear group , The order, for A generator of , and using As the corresponding bilinear map , randomly select two prime numbers The random numbers are mutually prime, and the two random numbers belong to a random library. A hash function is defined to generate the corresponding system key according to the terminal identification, security parameters and random numbers of the user terminal. The terminal identification is the attribute information of the user terminal, which is randomly selected from the random library to which the two random numbers belong, thereby generating the system key.

[0030] Specifically, the preprocessed data is encrypted using a symmetric encryption algorithm and a system key to obtain encrypted data. In this embodiment, the symmetric encryption algorithm uses the AES algorithm. It can be understood that in other embodiments, the encryption algorithm can also use DES, 3DES, IDEA, etc.

[0031] S105, using the secret value to perform secondary encryption on the system key to obtain an encryption key, and generating corresponding enterprise encryption information according to the encrypted data and the encryption key.

[0032] For further information, see Figure 4 , the step S105 specifically includes steps S1051~S1052: S1051, performing secondary encryption on the system key using an attribute encryption algorithm and the secret value to access a corresponding structural attribute to obtain an encryption key; S1052, determining a corresponding random vector, and associating the encrypted data with the encryption key according to the random vector to generate corresponding enterprise encryption information.

[0033] In the specific implementation, the attribute encryption algorithm (in this example, the attribute encryption algorithm uses the CP-ABE algorithm. In some optional embodiments, the attribute encryption algorithm can also be the KP-ABE algorithm) and the secret value obtained above are used to perform secondary encryption on the system key. When the system key is generated, a system public key will be generated accordingly. The structure of the linear secret access policy corresponding to Ac-cp is set through the system public key access structure Ac-cp and the system key. ,in, for The matrix of order, is a row, indicating the number of user attributes; The columns represent the number of attributes of the access policy in CP-ABE. The rows in the matrix are associated with the attributes through a preset function, and a random vector is selected. The random vector is used to share the encryption element. The encrypted data and the encryption key are associated according to the random vector, so as to obtain the encrypted ciphertext of the enterprise information, that is, the corresponding enterprise encrypted information.

[0034] In summary, the enterprise information management method based on big data in the above-mentioned embodiments of the present invention desensitizes enterprise information to avoid data abuse and leakage of sensitive information, generates security parameters using the confidentiality level of the user terminal, and improves the stability and security of the key by randomly selecting the key server within a preset data processing interval and using validity verification. The system key is generated according to the terminal identification and security parameters of the user terminal, the data is encrypted by the system key, and the system key is re-encrypted using the calculated secret value, so that information encryption has multiple encryption methods, thereby having a one-to-many advantage and being able to resist malicious collusion attacks by users.

[0035] Embodiment 2 On the other hand, the present invention also proposes an enterprise information management system based on big data, see Figure 5 , which shows an enterprise information management system based on big data in a second embodiment of the present invention, the system includes: The data desensitization module 11 is used to obtain the enterprise information sent by the user terminal and perform data desensitization on the enterprise information to obtain pre-processed data; Furthermore, the data desensitization module 11 includes: A data parsing unit, used to annotate the data interface of the user terminal to determine the interface type of the user terminal and parse out the enterprise type in the enterprise information; A data desensitization unit is used to determine corresponding data desensitization rules according to the interface type and the enterprise type, and use the data desensitization rules to desensitize the enterprise information to obtain pre-processed data.

[0036] The data verification module 12 is used to generate corresponding security parameters based on the confidentiality level of the user terminal, and randomly select a key server within a preset data processing interval, and verify the validity of the random selection result; Furthermore, the data verification module 12 includes: A parameter calling unit, configured to obtain a corresponding confidentiality level according to a user identification of the user terminal, and call a corresponding security parameter from a preset parameter database based on the confidentiality level; The data verification unit is used to randomly select a key server within a preset data processing interval to obtain a random key, construct a key weight of the user terminal for the random key, and use a Lagrange difference algorithm to verify the validity of the key weight and the random key.

[0037] A result generating module 13, configured to generate a secret value corresponding to the user terminal according to the random selection result if the random selection result passes the validity verification; A primary encryption module 14, configured to generate a corresponding system key according to the terminal identification of the user terminal and the security parameter, and to encrypt the preprocessed data using the system key to obtain encrypted data; Furthermore, the primary encryption module 14 is specifically used for: Choose a prime number As a bilinear group , The order, for A generator of , and using As the corresponding bilinear map ; Randomly select two bits that are the same as the prime number A mutually prime random number is used, and a hash function is defined to generate a corresponding system key according to the terminal identifier of the user terminal, the security parameter and the random number.

[0038] The secondary encryption module 15 is used to perform secondary encryption on the system key using the secret value to obtain an encryption key, and generate corresponding enterprise encryption information according to the encrypted data and the encryption key.

[0039] Furthermore, the secondary encryption module 15 includes: A secondary encryption unit, used to perform secondary encryption on the system key using an attribute encryption algorithm and the secret value to access a corresponding structural attribute and obtain an encryption key; The data association unit is used to determine a corresponding random vector, and associate the encrypted data with the encryption key according to the random vector to generate corresponding enterprise encryption information.

[0040] The functions or operation steps implemented when the above modules and units are executed are generally the same as those in the above method embodiments, and will not be repeated here.

[0041] The enterprise information management system based on big data provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the system embodiment, reference can be made to the corresponding contents in the aforementioned method embodiment.

[0042] Embodiment 3 The present invention also provides a computer, see Figure 6 , shown is a computer in the third embodiment of the present invention, including a memory 10, a processor 20, and a computer program 30 stored in the memory 10 and executable on the processor 20, and when the processor 20 executes the computer program 30, the above-mentioned enterprise information management method based on big data is implemented.

[0043] The memory 10 includes at least one type of readable storage medium, which includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 10 may be an internal storage unit of a computer, such as a hard disk of the computer. In other embodiments, the memory 10 may also be an external storage device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card, etc. Further, the memory 10 may also include both an internal storage unit of the computer and an external storage device. The memory 10 may be used not only to store application software and various types of data installed in the computer, but also to temporarily store data that has been output or is to be output.

[0044] Among them, in some embodiments, the processor 20 can be an electronic control unit (Electronic Control Unit, abbreviated as ECU, also known as a vehicle computer), a central processing unit (Central Processing Unit, CPU), a controller, a microcontroller, a microprocessor or other data processing chip, used to run the program code stored in the memory 10 or process data, such as executing access restriction programs, etc.

[0045] It should be pointed out that Figure 6 The structure shown does not constitute a limitation on the computer. In other embodiments, the computer may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0046] An embodiment of the present invention further provides a readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the enterprise information management method based on big data as described above.

[0047] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0048] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0049] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0050] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0051] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for enterprise information management based on big data, characterized in that: include: Acquire the enterprise information sent by the user terminal, and perform data desensitization on the enterprise information to obtain pre-processed data; Generate corresponding security parameters based on the confidentiality level of the user terminal, randomly select a key server within a preset data processing interval, and verify the validity of the random selection result; If the random selection result passes the validity verification, generating a secret value corresponding to the user terminal according to the random selection result; Generate a corresponding system key according to the terminal identification of the user terminal and the security parameter, and encrypt the pre-processed data using the system key to obtain encrypted data; The system key is encrypted twice using the secret value to obtain an encryption key, and corresponding enterprise encryption information is generated according to the encrypted data and the encryption key.

2. The enterprise information management method based on big data according to claim 1 is characterized in that: The steps of obtaining the enterprise information sent by the user terminal and performing data desensitization on the enterprise information to obtain pre-processed data include: Annotating the data interface of the user terminal to determine the interface type of the user terminal, and parsing the enterprise type in the enterprise information; Corresponding data desensitization rules are determined according to the interface type and the enterprise type, and the enterprise information is desensitized using the data desensitization rules to obtain preprocessed data.

3. The enterprise information management method based on big data according to claim 1 is characterized in that: The steps of generating corresponding security parameters based on the confidentiality level of the user terminal, randomly selecting a key server within a preset data processing interval, and verifying the validity of the random selection result include: Acquire a corresponding confidentiality level according to a user identification of the user terminal, and call a corresponding security parameter from a preset parameter database based on the confidentiality level; A key server is randomly selected within a preset data processing interval to obtain a random key, a key weight of the user terminal for the random key is constructed, and the key weight and the random key are verified for validity using a Lagrange difference algorithm.

4. The enterprise information management method based on big data according to claim 1 is characterized in that: The step of generating a corresponding system key according to the terminal identification of the user terminal and the security parameter comprises: Choose a prime number As a bilinear group , The order, for A generator of , and using As the corresponding bilinear map ; Randomly select two bits that are the same as the prime number A mutually prime random number is defined, and a hash function is defined to generate a corresponding system key according to the terminal identifier of the user terminal, the security parameter and the random number.

5. The enterprise information management method based on big data according to claim 1, characterized in that: The steps of performing secondary encryption on the system key using the secret value to obtain an encryption key, and generating corresponding enterprise encryption information according to the encrypted data and the encryption key include: The system key is re-encrypted using an attribute encryption algorithm and the secret value to access a corresponding structural attribute to obtain an encryption key; A corresponding random vector is determined, and the encrypted data and the encryption key are associated according to the random vector to generate corresponding enterprise encryption information.

6. An enterprise information management system based on big data, characterized in that: include: A data desensitization module is used to obtain the enterprise information sent by the user terminal and perform data desensitization on the enterprise information to obtain pre-processed data; A data verification module, used to generate corresponding security parameters based on the confidentiality level of the user terminal, and randomly select a key server within a preset data processing interval, and verify the validity of the random selection result; A result generating module, configured to generate a secret value corresponding to the user terminal according to the random selection result if the random selection result passes the validity verification; a primary encryption module, used to generate a corresponding system key according to the terminal identification of the user terminal and the security parameter, and to encrypt the preprocessed data using the system key to obtain encrypted data; The secondary encryption module is used to perform secondary encryption on the system key using the secret value to obtain an encryption key, and generate corresponding enterprise encryption information according to the encrypted data and the encryption key.

7. The enterprise information management system based on big data according to claim 6, characterized in that: The data desensitization module includes: A data parsing unit, used to annotate the data interface of the user terminal to determine the interface type of the user terminal and parse out the enterprise type in the enterprise information; A data desensitization unit is used to determine corresponding data desensitization rules according to the interface type and the enterprise type, and use the data desensitization rules to desensitize the enterprise information to obtain pre-processed data.

8. The enterprise information management system based on big data according to claim 6, characterized in that: The data verification module comprises: A parameter calling unit, configured to obtain a corresponding confidentiality level according to a user identification of the user terminal, and call a corresponding security parameter from a preset parameter database based on the confidentiality level; The data verification unit is used to randomly select a key server within a preset data processing interval to obtain a random key, construct a key weight of the user terminal for the random key, and use a Lagrange difference algorithm to verify the validity of the key weight and the random key.

9. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the enterprise information management method based on big data as described in any one of claims 1 to 5 is implemented.

10. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the enterprise information management method based on big data as described in any one of claims 1 to 5 is implemented.

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