Full-life-cycle management method and device for information data, equipment and medium

Abstract

The invention relates to a full-life-cycle management method and device for information data, equipment and a medium, and belongs to the field of information management. The method comprises the following steps: inputting information data and obtaining a sub-database; encrypting the sub-database through the database key; a user accesses the sub-database through the database key after real-name authentication, a terminal obtains watermark data in real time, and a binary image original watermark is generated through the watermark data; processing the binary image original watermark based on improved matrix transformation and obtaining a scrambling watermark, wherein the information data downloaded by a user carries the scrambling watermark; and presetting a low-access period, obtaining a user comprehensive similarity, matching low-access data according to the user comprehensive similarity, and pushing the low-access data to a user side. According to the method, hierarchical encryption protection is carried out on different data, tracking and tracing are carried out on data suspected to be leaked through scrambling watermarks, and meanwhile, data which are not accessed by people for a long time are matched for the users according to the similarity between the users, so that the data are prevented from being buried.

Description

Technical Field

[0001] The present invention belongs to the technical field of information management, and specifically relates to a method, device, equipment and medium for full life cycle management of information data. Background Art

[0002] Data management is the process of effectively collecting, storing, processing and applying data using computer hardware and software technology, with the aim of fully and effectively bringing into play the role of data. The key to achieving effective data management is data organization. With the development of computer technology, data management has gone through three stages of development: manual management, file system, and database system. The data structure established in the database system more fully describes the internal connections between data, facilitates data modification, updating and expansion, and at the same time ensures the independence, reliability, security and integrity of the data, reduces data redundancy, and thus improves the degree of data sharing and data management efficiency. However, at present, it is difficult to quickly track the leaker of leaked data, and some data has not been accessed for a long time. Big data will push less and less about this part of data, resulting in the possibility that some valuable data will be buried. Summary of the invention

[0003] In order to solve the above problems existing in the prior art, the present invention provides a method, device, equipment and medium for full life cycle management of information data.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] A full life cycle management method for information data, the implementation of which includes the following steps:

[0006] S1: Enter information data and obtain sub-databases, which include general sub-databases, important sub-databases, core sub-databases, and confidential sub-databases;

[0007] S2: Encrypting the sub-database using a database key, wherein the database key includes a general sub-database key, an important sub-database key, a core sub-database key, and a confidential sub-database key;

[0008] S3: After real-name authentication, the user accesses the sub-database through the database key, and the terminal obtains the watermark data in real time, and generates a binary image original watermark through the watermark data;

[0009] S4: Processing the original watermark of the binary image based on the improved matrix transformation and obtaining a scrambled watermark, and the information data downloaded by the user carries the scrambled watermark;

[0010] S5: Preset a low access period, obtain comprehensive user similarity, match low access data according to the comprehensive user similarity and push it to the user end, the low access data is the information data with less than 100 access times in the low access period.

[0011] Preferably, the general sub-database key is a random prime number key, the important sub-database key is a dual key of a fingerprint key and the random prime number key, the core sub-database key is a triple key of a face key, a fingerprint key and a random prime number key, and the confidential sub-database key is a quadruple key of an iris key, a face key, a fingerprint key and a random prime number key.

[0012] Preferably, the watermark data includes the user's Internet Protocol address, the last 3 digits of the user's ID card, and a digital timestamp.

[0013] Preferably, the step S4 specifically includes:

[0014] S401: Obtain a scrambling matrix, the expression of the scrambling matrix is:

[0015]

[0016] Wherein, A is a scrambling matrix, a is a first control parameter, b is a second control parameter, and a and b are random natural numbers;

[0017] S402: Perform a first scrambling on the original watermark of the binary image according to the scrambling matrix and obtain a first scrambled watermark. The mathematical description of the first scrambling is:

[0018]

[0019] Wherein, x' is the horizontal coordinate of the first scrambled watermark pixel, y' is the vertical coordinate of the first scrambled watermark pixel, A is the scrambling matrix, x is the horizontal coordinate of the original watermark pixel of the binary image, y is the vertical coordinate of the original watermark pixel of the binary image, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image;

[0020] S403: Perform a second scrambling on the first scrambled watermark and obtain a second scrambled watermark. The mathematical description of the second scrambling is:

[0021]

[0022] Wherein, x″ is the horizontal coordinate of the second scrambled watermark pixel, y″ is the vertical coordinate of the second scrambled watermark pixel, A is the scrambling matrix, x' is the horizontal coordinate of the first scrambled watermark pixel, y' is the vertical coordinate of the first scrambled watermark pixel, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image;

[0023] S404: Perform a third scrambling on the second scrambled watermark and obtain the scrambled watermark. The mathematical description of the third scrambling is:

[0024]

[0025] Among them, x″′ is the horizontal coordinate of the scrambled watermark pixel, y″′ is the vertical coordinate of the scrambled watermark pixel, x″ is the horizontal coordinate of the second scrambled watermark pixel, y″ is the vertical coordinate of the second scrambled watermark pixel, A is the scrambling matrix, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image.

[0026] Preferably, the step S5 specifically includes:

[0027] S501: Acquire information data types, where the information data types include first-category information data, second-category information data, ..., i-th-category information data, ..., N-th-category information data;

[0028] S502: Acquire a user set, where the user set includes a first user, a second user, ..., a uth user, ..., a vth user, ..., an nth user;

[0029] S503: Obtaining user similarity based on user historical interaction values;

[0030] S504: obtaining user attribute similarity through user personal attribute similarity, wherein the user personal attribute similarity includes age similarity and gender similarity;

[0031] S505: Calculate the user comprehensive similarity according to the user similarity and the user attribute similarity, and the calculation formula is:

[0032] W u，v =β·S u，v +(1-β)·B u，v ,u=1,2,...n, v=1,2,...n,

[0033] Among them, W u,v is the comprehensive similarity between the u-th user and the v-th user, β is the weight factor, and its value is in the closed interval [0,1], S u,v is the user similarity between the u-th user and the v-th user, B u,v is the similarity of user attributes between the u-th user and the v-th user, and n is the total number of users;

[0034] S506: Preset a user comprehensive similarity threshold, match highly similar users, and push the low-access data visited by the highly similar users to the user terminal, wherein the highly similar users are users whose user comprehensive similarity is greater than or equal to the user comprehensive similarity threshold.

[0035] Preferably, the step S503 specifically includes:

[0036] S503-1: Obtain the user's historical interaction value, where the expression of the user's historical interaction value is:

[0037]

[0038] Among them, T u,i is the user historical interaction value of the u-th user for the i-th type of information data, N is the total number of information data types, and n is the total number of users;

[0039] S503-2: Calculate the user similarity, the calculation formula is:

[0040]

[0041] Among them, S u,v is the user similarity between the u-th user and the v-th user, n is the total number of users, T u,i is the historical interaction value of the u-th user for the i-th type of information data, T v,i is the historical interaction value of the vth user for the i-th type of information data, is the average historical interaction value of the u-th user, is the average historical interaction value of the vth user, and N is the total number of information data types.

[0042] Preferably, the step S504 specifically includes:

[0043] S504-1: Calculate the age similarity based on the user's age, using the following calculation formula:

[0044]

[0045] Among them, R u,v is the age similarity between the u-th user and the v-th user, min{·} is the minimum value, R u is the age of the u-th user, R v is the age of the vth user, and n is the total number of users;

[0046] S504-2: Calculate the user attribute similarity, the calculation formula is:

[0047] B u，v =α·R u，v +(1-α)·E u，v ,u=1,2,...n, v=1,2,...n,

[0048] Among them, B u,vis the similarity between the user attributes of the u-th user and the v-th user, α is the weight coefficient, and its value is in the closed interval [0,1], R u,v is the age similarity between the u-th user and the v-th user, E u,v is the gender similarity between the u-th user and the v-th user. The value is 1 when the u-th user and the v-th user have the same gender, and the value is 0 when the u-th user and the v-th user have different genders. n is the total number of users.

[0049] A full life cycle management device for information data, used to execute the above-mentioned full life cycle management method, characterized by comprising a data entry module, a database encryption module, a user access module, a watermark generation module, and a data push module;

[0050] The data entry module is used to enter information data and obtain sub-databases, and the sub-databases include general sub-databases, important sub-databases, core sub-databases, and confidential sub-databases;

[0051] The database encryption module is used to encrypt the sub-database by using a database key, wherein the database key includes a general sub-database key, an important sub-database key, a core sub-database key, and a confidential sub-database key;

[0052] The user access module is used for the user to access the sub-database through the database key after real-name authentication, and the terminal obtains watermark data in real time, and generates a binary image original watermark through the watermark data;

[0053] The watermark generation module is used to process the original watermark of the binary image based on the improved matrix transformation and obtain the scrambled watermark, and the information data downloaded by the user carries the scrambled watermark;

[0054] The data push module is used to preset a low access cycle, obtain user comprehensive similarity, match low access data according to the user comprehensive similarity and push it to the user end, wherein the low access data is the information data with less than 100 access times within the low access cycle.

[0055] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for managing the entire life cycle of information data when executing the program.

[0056] A storage medium containing computer executable instructions, which, when executed by a computer processor, are used to execute the above-mentioned method for managing the entire life cycle of information data.

[0057] The beneficial effects of the present invention are:

[0058] (1) By generating a scrambled watermark based on the user's Internet Protocol address, the last three digits of the user's ID card, and the digital timestamp, it is easy to track the source, and when data is leaked, the leaking user can be quickly identified based on the scrambled watermark;

[0059] (2) By matching low-access data based on comprehensive user similarity and pushing it to the user end, the situation where some data has been unavailable for a long time and the push intensity has decreased can be reduced, thus preventing some valuable data from being buried;

[0060] (3) By adopting different encryption methods for data of different importance, the protection of important data can be improved and the workload caused by over-protection of ordinary data can be reduced;

[0061] (4) By processing the original watermark of the binary image based on the improved matrix transformation and obtaining the scrambled watermark, the uniqueness of the scrambled watermark is ensured, and the acquisition method is random, convenient and efficient;

[0062] (5) By matching another user who has high similarity with the user in terms of gender, age, and historical interaction data, the user is pushed low-visit data that the other user has visited. This makes the matching mechanism more scientific and increases the possibility that the user will be pushed data of interest. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0064] Figure 1 The present invention is a flowchart of the steps of a method for managing the entire life cycle of information data. DETAILED DESCRIPTION

[0065] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0066] The working principle and use process of the present invention:

[0067] See also Figure 1 , a full life cycle management method for information data, including:

[0068] S1: Enter information data and obtain sub-databases, which include general sub-databases, important sub-databases, core sub-databases, and confidential sub-databases;

[0069] S2: Encrypt the sub-database by using a database key, wherein the database key includes a general sub-database key, an important sub-database key, a core sub-database key, and a confidential sub-database key. The general sub-database key is a random prime number key, the important sub-database key is a double key of a fingerprint key and the random prime number key, the core sub-database key is a triple key of a face key, a fingerprint key, and a random prime number key, and the confidential sub-database key is a quadruple key of an iris key, a face key, a fingerprint key, and a random prime number key;

[0070] S3: After real-name authentication, the user accesses the sub-database through the database key, and the terminal obtains watermark data in real time, and generates a binary image original watermark through the watermark data. The watermark data includes the user's Internet Protocol address, the last 3 digits of the user's ID card, and a digital timestamp;

[0071] S4: Processing the original watermark of the binary image based on the improved matrix transformation and obtaining a scrambled watermark, and the information data downloaded by the user carries the scrambled watermark;

[0072] S5: Preset a low access period, obtain comprehensive user similarity, match low access data according to the comprehensive user similarity and push it to the user end, the low access data is the information data with less than 100 access times in the low access period.

[0073] In this embodiment, the binary image original watermark is processed based on the improved matrix transformation to obtain the scrambled watermark, which ensures the uniqueness of the scrambled watermark, and the acquisition method is random, convenient and efficient. The user downloads the information data with the scrambled watermark, which is convenient for tracing the source, and when the data is leaked, the leaking user can be quickly locked according to the scrambled watermark. The specific implementation can be carried out through the following steps:

[0074] S401: Obtain a scrambling matrix, the expression of the scrambling matrix is:

[0075]

[0076] Wherein, A is a scrambling matrix, a is a first control parameter, b is a second control parameter, and a and b are random natural numbers;

[0077] S402: Perform a first scrambling on the original watermark of the binary image according to the scrambling matrix and obtain a first scrambled watermark. The mathematical description of the first scrambling is:

[0078]

[0079] Wherein, x' is the horizontal coordinate of the first scrambled watermark pixel, y' is the vertical coordinate of the first scrambled watermark pixel, A is the scrambling matrix, x is the horizontal coordinate of the original watermark pixel of the binary image, y is the vertical coordinate of the original watermark pixel of the binary image, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image;

[0080] S403: Perform a second scrambling on the first scrambled watermark and obtain a second scrambled watermark. The mathematical description of the second scrambling is:

[0081]

[0082] Wherein, x″ is the horizontal coordinate of the second scrambled watermark pixel, y″ is the vertical coordinate of the second scrambled watermark pixel, A is the scrambling matrix, x' is the horizontal coordinate of the first scrambled watermark pixel, y' is the vertical coordinate of the first scrambled watermark pixel, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image;

[0083] S404: Perform a third scrambling on the second scrambled watermark and obtain the scrambled watermark. The mathematical description of the third scrambling is:

[0084]

[0085] Among them, x″′ is the horizontal coordinate of the scrambled watermark pixel, y″′ is the vertical coordinate of the scrambled watermark pixel, y″ is the horizontal coordinate of the second scrambled watermark pixel, y″ is the vertical coordinate of the second scrambled watermark pixel, A is the scrambling matrix, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image.

[0086] In this embodiment, a low access period is preset, and the comprehensive similarity of users is obtained. The low access data is matched according to the comprehensive similarity of users and pushed to the user end, so as to reduce the situation where the push strength of some data decreases due to long-term unattended access, and avoid the burial of some valuable data. The low access data is the information data with less than 100 access times in the low access period, which can be implemented by the following steps:

[0087] S501: Acquire information data types, where the information data types include first-category information data, second-category information data, ..., i-th-category information data, ..., N-th-category information data;

[0088] S502: Acquire a user set, where the user set includes a first user, a second user, ..., a uth user, ..., a vth user, ..., an nth user;

[0089] S503: Obtaining user similarity based on user historical interaction values;

[0090] S504: obtaining user attribute similarity through user personal attribute similarity, wherein the user personal attribute similarity includes age similarity and gender similarity;

[0091] S505: Calculate the user comprehensive similarity according to the user similarity and the user attribute similarity, and the calculation formula is:

[0092] W u，v =β·S u，v +(1-β)·B u，v ,u=1,2,...n, v=1,2,...n,

[0093] Among them, W u,v is the comprehensive similarity between the u-th user and the v-th user, β is the weight factor, and its value is in the closed interval [0,1], S u,v is the user similarity between the u-th user and the v-th user, B u,v is the similarity of user attributes between the u-th user and the v-th user, and n is the total number of users;

[0094] S506: Preset a user comprehensive similarity threshold, match highly similar users, and push the low-access data visited by the highly similar users to the user end. The matching mechanism is more scientific, which increases the possibility of users being pushed data of interest. The highly similar users are users whose user comprehensive similarity is greater than or equal to the user comprehensive similarity threshold.

[0095] In this embodiment, user similarity is obtained according to user historical interaction values, which can be implemented by the following steps:

[0096] S503-1: Obtain the user's historical interaction value, where the expression of the user's historical interaction value is:

[0097]

[0098] Among them, T u,i is the user historical interaction value of the u-th user for the i-th type of information data, N is the total number of information data types, and n is the total number of users;

[0099] S503-2: Calculate the user similarity, the calculation formula is:

[0100]

[0101] Among them, S u,v is the user similarity between the u-th user and the v-th user, n is the total number of users, T u,i is the historical interaction value of the u-th user for the i-th type of information data, T v,i is the historical interaction value of the vth user for the i-th type of information data, is the average historical interaction value of the u-th user, is the average historical interaction value of the vth user, and N is the total number of information data types.

[0102] In this embodiment, the user attribute similarity is obtained through the user personal attribute similarity, and the user personal attribute similarity includes age similarity and gender similarity, which can be specifically implemented by the following steps:

[0103] S504-1: Calculate the age similarity based on the user's age, using the following calculation formula:

[0104]

[0105] Among them, R u,v is the age similarity between the u-th user and the v-th user, min{·} is the minimum value, R u is the age of the u-th user, R v is the age of the vth user, and n is the total number of users;

[0106] S504-2: Calculate the user attribute similarity, the calculation formula is:

[0107] B u，v =α·R u，v +(1-α)·E u，v ,u=1,2,n,v=1,2,...n,

[0108] Among them, B u,v is the similarity between the user attributes of the u-th user and the v-th user, α is the weight coefficient, and its value is in the closed interval [0,1], R u,v is the age similarity between the u-th user and the v-th user, E u,v is the gender similarity between the u-th user and the v-th user. The value is 1 when the u-th user and the v-th user have the same gender, and the value is 0 when the u-th user and the v-th user have different genders. n is the total number of users.

[0109] A full life cycle management device for information data, comprising a data entry module, a database encryption module, a user access module, a watermark generation module, and a data push module;

[0110] The data entry module is used to enter information data and obtain sub-databases, and the sub-databases include general sub-databases, important sub-databases, core sub-databases, and confidential sub-databases;

[0111] The database encryption module is used to encrypt the sub-database by using a database key, wherein the database key includes a general sub-database key, an important sub-database key, a core sub-database key, and a confidential sub-database key;

[0112] The user access module is used for the user to access the sub-database through the database key after real-name authentication, and the terminal obtains watermark data in real time, and generates a binary image original watermark through the watermark data;

[0113] The watermark generation module is used to process the original watermark of the binary image based on the improved matrix transformation and obtain the scrambled watermark, and the information data downloaded by the user carries the scrambled watermark;

[0114] The data push module is used to preset a low access cycle, obtain user comprehensive similarity, match low access data according to the user comprehensive similarity and push it to the user end, wherein the low access data is the information data with less than 100 access times within the low access cycle.

[0115] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0116] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0117] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0118] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for managing the entire life cycle of information data, characterized in that: The implementation of the full life cycle management method includes the following steps: S1: Enter information data and obtain sub-databases, which include general sub-databases, important sub-databases, core sub-databases, and confidential sub-databases; S2: Encrypting the sub-database using a database key, wherein the database key includes a general sub-database key, an important sub-database key, a core sub-database key, and a confidential sub-database key; S3: After real-name authentication, the user accesses the sub-database through the database key, and the terminal obtains the watermark data in real time, and generates a binary image original watermark through the watermark data; S4: Processing the original watermark of the binary image based on the improved matrix transformation and obtaining a scrambled watermark, and the information data downloaded by the user carries the scrambled watermark; S5: Preset a low access period, obtain comprehensive user similarity, match low access data according to the comprehensive user similarity and push it to the user end, the low access data is the information data with less than 100 access times in the low access period.

2. The full life cycle management method according to claim 1, characterized in that: The general sub-database key is a random prime number key, the important sub-database key is a dual key of a fingerprint key and the random prime number key, the core sub-database key is a triple key of a face key, a fingerprint key and a random prime number key, and the confidential sub-database key is a quadruple key of an iris key, a face key, a fingerprint key and a random prime number key.

3. The full life cycle management method according to claim 1, characterized in that: The watermark data includes the user's Internet Protocol address, the last 3 digits of the user's ID card, and a digital timestamp.

4. The full life cycle management method according to claim 1, characterized in that: The step S4 specifically includes: S401: Obtain a scrambling matrix, the expression of the scrambling matrix is: Wherein, A is a scrambling matrix, a is a first control parameter, b is a second control parameter, and a and b are random natural numbers; S402: Perform a first scrambling on the original watermark of the binary image according to the scrambling matrix and obtain a first scrambled watermark. The mathematical description of the first scrambling is: Wherein, x' is the horizontal coordinate of the first scrambled watermark pixel, y' is the vertical coordinate of the first scrambled watermark pixel, A is the scrambling matrix, x is the horizontal coordinate of the original watermark pixel of the binary image, y is the vertical coordinate of the original watermark pixel of the binary image, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image; S403: Perform a second scrambling on the first scrambled watermark and obtain a second scrambled watermark. The mathematical description of the second scrambling is: in, x is the horizontal coordinate of the second scrambled watermark pixel, y is the vertical coordinate of the second scrambled watermark pixel, A is the scrambling matrix, x' is the horizontal coordinate of the first scrambled watermark pixel, y' is the vertical coordinate of the first scrambled watermark pixel, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image; S404: Perform a third scrambling on the second scrambled watermark and obtain the scrambled watermark. The mathematical description of the third scrambling is: Among them, x... is the horizontal coordinate of the scrambled watermark pixel, y is the vertical coordinate of the scrambled watermark pixel, x is the horizontal coordinate of the second scrambled watermark pixel, y is the vertical coordinate of the second scrambled watermark pixel, A is the scrambling matrix, mod is the remainder function, l is the original watermark length of the binary image, and d is the original watermark width of the binary image.

5. The full life cycle management method according to claim 1, characterized in that: The step S5 specifically includes: S501: Acquire information data types, where the information data types include first-category information data, second-category information data, ..., i-th-category information data, ..., N-th-category information data; S502: Acquire a user set, where the user set includes a first user, a second user, ..., a uth user, ..., a vth user, ..., an nth user; S503: Obtaining user similarity based on user historical interaction values; S504: obtaining user attribute similarity through user personal attribute similarity, wherein the user personal attribute similarity includes age similarity and gender similarity; S505: Calculate the user comprehensive similarity according to the user similarity and the user attribute similarity, and the calculation formula is: W u，v =β·S u，v +(1-β)·B u，v ,u=1,2,...n,V=1,2,...n, Among them, W u,v is the comprehensive similarity between the u-th user and the v-th user, β is the weight factor, and its value is in the closed interval [0, 1], S u，v is the user similarity between the u-th user and the v-th user, B u，v is the similarity of user attributes between the u-th user and the v-th user, and n is the total number of users; S506: Preset a user comprehensive similarity threshold, match highly similar users, and push the low-access data visited by the highly similar users to the user terminal, wherein the highly similar users are users whose user comprehensive similarity is greater than or equal to the user comprehensive similarity threshold.

6. The full life cycle management method according to claim 5, characterized in that: The step S503 specifically includes: S503-1: Obtain the user's historical interaction value, where the expression of the user's historical interaction value is: Among them, T u，i is the user historical interaction value of the u-th user for the i-th type of information data, N is the total number of information data types, and n is the total number of users; S503-2: Calculate the user similarity, the calculation formula is: Among them, S u，v is the user similarity between the u-th user and the v-th user, n is the total number of users, T u，i is the historical interaction value of the u-th user for the i-th type of information data, T v，i is the historical interaction value of the vth user for the i-th type of information data, is the average historical interaction value of the u-th user, is the average historical interaction value of the vth user, and N is the total number of information data types.

7. The full life cycle management method according to claim 5, characterized in that: The step S504 specifically includes: S504-1: Calculate the age similarity based on the user's age, using the following calculation formula: Among them, R u，v is the age similarity between the u-th user and the v-th user, min{·} is the minimum value, R u is the age of the u-th user, R v is the age of the vth user, and n is the total number of users; S504-2: Calculate the user attribute similarity, the calculation formula is: B u，v =α·R u，v +(1-a)·E u，v ,u=1,2,...n,V=1,2,...n, Among them, B u，v is the similarity between the user attributes of the u-th user and the v-th user, α is the weight coefficient, and its value is in the closed interval [0, 1], R u，v is the age similarity between the u-th user and the v-th user, E u，v is the gender similarity between the u-th user and the v-th user. The value is 1 when the u-th user and the v-th user have the same gender, and the value is 0 when the u-th user and the v-th user have different genders. n is the total number of users.

8. A device for managing the entire life cycle of information data, characterized in that: It includes data entry module, database encryption module, user access module, watermark generation module and data push module; The data entry module is used to enter information data and obtain sub-databases, and the sub-databases include general sub-databases, important sub-databases, core sub-databases, and confidential sub-databases; The database encryption module is used to encrypt the sub-database by using a database key, wherein the database key includes a general sub-database key, an important sub-database key, a core sub-database key, and a confidential sub-database key; The user access module is used for the user to access the sub-database through the database key after real-name authentication, and the terminal obtains watermark data in real time, and generates a binary image original watermark through the watermark data; The watermark generation module is used to process the original watermark of the binary image based on the improved matrix transformation and obtain the scrambled watermark, and the information data downloaded by the user carries the scrambled watermark; The data push module is used to preset a low access cycle, obtain user comprehensive similarity, match low access data according to the user comprehensive similarity and push it to the user end, wherein the low access data is the information data with less than 100 access times within the low access cycle.

9. An electronic device 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 program, the method for managing the entire life cycle of information data as described in any one of claims 1 to 7 is implemented.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the full life cycle management method of information data as described in any one of claims 1-7 when executed by a computer processor.

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