An information hierarchical encryption system based on internet of things

Abstract

The application discloses an information hierarchical encryption system based on Internet of Things, and relates to the technical field of information hierarchical encryption.The system discloses an encryption hierarchical module, an encryption substitution module and an encryption analysis module.The encryption hierarchical module can identify the information type of corresponding information when the information is initially stored, intelligently analyze the encryption hierarchical requirement of the information according to the information type, ensure the reasonable encryption of different types of information, and further facilitate the overall management of each encrypted information.The encryption substitution module can intelligently analyze the password modification requirement of encrypted information before the user decrypts the information, modify the password of the encrypted information into a safe and reasonable encryption string after determining that the password of the encrypted information needs to be modified, improve the decryption efficiency of the user for the encrypted information, and ensure the safety of the encrypted information.

Description

Technical Field

[0001] This invention relates to the field of information hierarchical encryption technology, and more specifically, to an information hierarchical encryption system based on the Internet of Things. Background Technology

[0002] Before storing information, users need to encrypt it to ensure secure storage. Users must enter a password to access stored information each time. Currently, users set their own passwords, leading to a large number of duplicate passwords and increasing the risk of insecurity. While a system-set password system would ensure unique passwords for each message, users would need to remember numerous passwords, potentially resulting in inefficient decryption. Summary of the Invention

[0003] In view of the shortcomings of existing technologies, the purpose of this invention is to provide an information hierarchical encryption system based on the Internet of Things.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] An information hierarchical encryption system based on the Internet of Things includes an encryption hierarchical module, an encryption substitution module, and an encryption analysis module;

[0006] Before the information is initially stored, the encryption and classification module identifies the information type of the information and performs encryption and classification processing on the information based on the type storage value of the information type.

[0007] Before a user accesses encrypted information in the storage terminal, the encryption replacement module obtains the decryption difficulty value of the encrypted information and determines whether the encrypted string of the encrypted information needs to be replaced based on the comparison result between the decryption difficulty value and its threshold. If the encrypted string of the encrypted information needs to be replaced, the encrypted string of the encrypted information is replaced.

[0008] The encryption analysis module is used to generate an information decryption log after the user decrypts the encrypted information, and to generate an information viewing log after the user views the encrypted information.

[0009] Furthermore, the information is encrypted and graded based on the type storage value of the information type. Specifically, before the information is stored for the first time, the information type is identified, the type storage value F i of the information type is obtained, the storage encryption level of the information type is obtained according to the type storage value, the information is randomly encrypted according to the storage encryption level to form encrypted information, the encrypted string is sent to the corresponding user, and the encrypted information is sent to the storage end of the server through the Internet of Things.

[0010] Each type of storage value F_i corresponds to a storage encryption level. The range of the type storage value F_i includes (0, F1], (F1, F2], ..., (F_i-1, F_i], and the storage encryption levels include storage encryption level 1, storage encryption level 2, ..., storage encryption level i-1, and storage encryption level i. The higher the storage encryption level, the more characters are represented in the encrypted string of that information type.

[0011] Furthermore, the type storage value of the information type is obtained in the following way: All encrypted information of this information type is retrieved at the storage end; each encrypted information is marked as belonging to the same category; each category of information is assigned an information number j, j = 1, 2, ..., n; the information lookup value Ej of each category of information is obtained; the information lookup value coefficient is set to Xc; and the formula is used... Retrieve the type storage value Fi for this information type, where n is the total number of information of the same type.

[0012] Furthermore, the information retrieval value for similar information is obtained as follows: All information retrieval logs for similar information prior to the current system time are retrieved; the retrieval duration of each log is retrieved; the sum of all retrieval durations is calculated and averaged to obtain the average retrieval duration, which is then marked as PJJ; the retrieval depth is retrieved; a preset retrieval depth is set; when the retrieval depth is greater than or equal to the preset depth, the log is marked as a deep retrieval log; the total number of deep retrieval logs is marked as SDC; all deep retrieval logs are sorted according to their log numbers; the difference between the log numbers of two adjacent deep retrieval logs after sorting is calculated and the absolute value is taken to obtain the deep retrieval interval; all deep retrieval intervals are summed and averaged to obtain the average deep retrieval interval, which is then marked as MKR. The formula is then used... The information retrieval value Ej for this type of information is obtained, where a1 is the average retrieval time coefficient, a2 is the total number of deep retrieval logs coefficient, and a3 is the average deep retrieval interval coefficient.

[0013] Furthermore, the decryption difficulty value of the encrypted information is obtained as follows: Obtain all information decryption logs since the last replacement of the encrypted string. Sort all information decryption logs according to the chronological order of information decryption time. Calculate the difference between the number of decryption errors of two adjacent pairs after sorting and take the absolute value to obtain the error fluctuation difference. Set an error fluctuation threshold difference. When the error fluctuation difference is greater than or equal to the threshold difference, increment the error fluctuation count by one. Sum all error fluctuation counts to obtain the total number of error fluctuations, and mark it as KRS. Sum the decryption error counts of all information decryption logs and take the average to obtain the average decryption error count, and mark it as WCP. Sum the information decryption time of all information decryption logs and take the average to obtain the average information decryption time, and mark it as LEY. Use the formula... The decryption difficulty value NDZ of the encrypted information is obtained, where b1 is the coefficient of the total number of error fluctuations, b2 is the coefficient of the average number of decryption errors, and b3 is the coefficient of the average information decryption time.

[0014] Furthermore, based on the comparison between the decryption difficulty value and its threshold, it is determined whether the encrypted string of the encrypted information needs to be replaced. Specifically, a decryption difficulty threshold is set, and when the decryption difficulty is less than the decryption difficulty threshold, the encrypted string of the encrypted information remains unchanged.

[0015] When the decryption difficulty is greater than or equal to the decryption difficulty threshold, the encrypted information is marked as modified information. The information type of the modified information is obtained, the knowledge graph of each information type is obtained, and all encrypted information stored by the user on the storage side is obtained. Through knowledge graph association analysis, encrypted information of information types that are not related to the information type of the modified information is marked as irrelevant encrypted information. The information lookup value and decryption difficulty value of the modified information are obtained and marked as [x1, x2]. The information lookup value and decryption difficulty value of the irrelevant encrypted information are obtained and marked as [y1, y2]. The recommended modification value of the modified information and the irrelevant encrypted information is obtained using the cosine similarity formula. A recommended modification threshold is set. When the recommended modification value is less than the recommended modification threshold, the irrelevant encrypted information is marked as encrypted reference information. The encrypted reference information with the smallest recommended modification value is marked as encrypted replacement information. The encrypted string of the modified information is replaced with the encrypted string of the encrypted replacement information, and the encrypted string of the modified information is sent to the corresponding user.

[0016] Furthermore, the user inputs an encrypted string for the encrypted information, and after input, a decryption log of the encrypted information is generated;

[0017] Users can view encrypted information, and once the viewing is complete, an information viewing log for that encrypted information will be generated.

[0018] Furthermore, the information decryption log includes the information decryption time, information decryption duration, and number of decryption errors.

[0019] Furthermore, the information retrieval log includes user ID, log number, retrieval duration, and retrieval depth.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] 1. An encryption classification module is set up, which can identify the information type of the corresponding information when the information is first stored, and intelligently analyze the encryption classification requirements of the information according to the information type to ensure reasonable encryption of different types of information, thereby facilitating the overall management of various encrypted information.

[0022] 2. An encryption replacement module is set up, which can intelligently analyze the password modification needs of encrypted information before the user decrypts it. After determining that the password of the encrypted information needs to be modified, the password of the encrypted information is modified to a secure and reasonable encrypted string, thereby improving the user's decryption efficiency while ensuring the security of encrypted information. Attached Figure Description

[0023] Figure 1 A flowchart for determining whether the encrypted string of encrypted information needs to be replaced. Detailed Implementation

[0024] Reference Figure 1 An information hierarchical encryption system based on the Internet of Things includes an encryption hierarchical module, an encryption substitution module, and an encryption analysis module.

[0025] Encryption Level Module: Before the information is initially stored, the information type is identified, the type storage value Fi is obtained, the storage encryption level for the information type is determined based on the type storage value, and the information is randomly encrypted according to the storage encryption level (e.g., when the storage encryption level is 2, the corresponding encryption string is 8 characters, and the information is encrypted with 8 random characters, such as dgET5809 or 8092DR20, where the encrypted characters in the encryption string are all randomly generated), forming encrypted information. The encrypted string is then sent to the corresponding user (i.e., the user who uploaded and stored the information, with each encrypted information corresponding to one user), and the encrypted information is also sent to the server's storage end via the Internet of Things.

[0026] Each type of storage value Fi corresponds to a storage encryption level. The range of the type storage value Fi includes (0, F1], (F1, F2], ..., (Fi-1, Fi], and the storage encryption levels include storage encryption level 1, storage encryption level 2, ..., storage encryption level i-1, and storage encryption level i. When Fi ∈ (0, F1), the storage encryption level of the information type is set to storage encryption level 1. The higher the storage encryption level, the more characters the encrypted string of the information type has. For example, the encrypted string corresponding to storage encryption level 1 is 6 characters, the encrypted string corresponding to storage encryption level 2 is 8 characters, and the encrypted string corresponding to storage encryption level 3 is 10 characters.

[0027] The encryption classification module can identify the information type when the information is first stored, and intelligently analyze the encryption classification requirements based on the information type to ensure reasonable encryption for different types of information.

[0028] Encryption replacement module: Before users access encrypted information in the storage, the module obtains the decryption difficulty value of the encrypted information and sets a decryption difficulty threshold. The decryption difficulty threshold is a system-set threshold that can be modified according to actual needs. When the decryption difficulty is less than the decryption difficulty threshold, the encrypted string of the encrypted information remains unchanged.

[0029] When the decryption difficulty is greater than or equal to the decryption difficulty threshold, the encrypted information is marked as modified information. The information type of the modified information is obtained, and the knowledge graph for each information type is acquired. All encrypted information stored by the user on the storage side is obtained. Through knowledge graph association analysis, encrypted information of information types not related to the modified information is marked as irrelevant encrypted information. The information lookup value and decryption difficulty value of the modified information are obtained and marked as [x1, x2], where x1 is the information lookup value of the modified information and x2 is the decryption difficulty value of the modified information. The information lookup value and decryption difficulty value of irrelevant encrypted information are obtained and marked as [y1, y2], where y1 is the information lookup value of irrelevant encrypted information and y2 is the decryption difficulty value of irrelevant encrypted information. The cosine similarity formula (the formula is recommended) is then used. The system retrieves recommended password change values ​​for the password change information and irrelevant encrypted information, sets a recommended password change threshold (the system-defined threshold can be modified according to actual needs), and performs no processing when the recommended password change value is greater than or equal to the recommended password change threshold. When the recommended password change value is less than the recommended password change threshold, the irrelevant encrypted information is marked as encrypted reference information, the encrypted reference information with the smallest recommended password change value is marked as encrypted replacement information, the encrypted string of the password change information is replaced with the encrypted string of the encrypted replacement information, and the encrypted string of the password change information is sent to the corresponding user.

[0030] Relationships between different information types are represented in the form of knowledge graphs. For example, relationships in a knowledge graph represent associations between different information types, such as dependency relationships and influence relationships.

[0031] The decryption difficulty value of encrypted information is obtained as follows: Obtain all decryption logs of the encrypted information since the last modification of the encrypted string. Sort all decryption logs according to the chronological order of decryption time. Calculate the difference between the number of decryption errors of two adjacent pairs after sorting and take the absolute value to obtain the error fluctuation difference. Set an error fluctuation threshold difference, which is a system-defined threshold that can be modified according to actual needs. When the error fluctuation difference is greater than or equal to the error fluctuation threshold difference, increment the error fluctuation count by one. Sum all error fluctuation counts to obtain the total error fluctuation count, marked as KRS. Sum the decryption error counts of all information decryption logs and take the average to obtain the average decryption error count, marked as WCP. Sum the information decryption time of all information decryption logs and take the average to obtain the average information decryption time, marked as LEY. Use the formula... The decryption difficulty value NDZ of the encrypted information is obtained, where b1 is the total number of error fluctuations coefficient, b2 is the average number of decryption errors coefficient, and b3 is the average information decryption time coefficient. The value of b1 is 0.98, the value of b2 is 0.48, and the value of b3 is 0.51.

[0032] The encryption replacement module can intelligently analyze the password modification needs of encrypted information before the user decrypts it. After determining that the password of the encrypted information needs to be modified, it will modify the password of the encrypted information to a secure and reasonable encrypted string, continuously optimizing the user's decryption experience and ensuring the security of encrypted information while improving the user's decryption efficiency.

[0033] Encryption Analysis Module: After the user inputs an encrypted string of encrypted information, a decryption log of the encrypted information is generated. The decryption log includes the information decryption time (the time corresponding to the user inputting the first encrypted character), the information decryption duration, and the number of decryption errors (each incorrect character input in the encrypted string is counted as 1 decryption error).

[0034] The user then reviews the encrypted information. After the review is completed, an information review log for the encrypted information is generated. The information review log includes the user ID (the user ID that reviewed the encrypted information), the log number (the log number is y, where y = 1, 2, ..., N, and N is a positive integer. The log number is generated according to the order of the information review logs. Each information review log corresponds to an independent and unique log number. For example, if a total of 3 information review logs are generated for the encrypted information, then the information review logs for the encrypted information are log number 1, log number 2, and log number 3), the review duration (i.e., the total time the user spends reviewing the encrypted information), and the review depth (i.e., the total number of times the user clicks on the information annotations in the encrypted information. Information annotations can be text explanations, image explanations, etc., corresponding to the encrypted information. Clicking on the corresponding encrypted information will display the corresponding information annotation. For example, if the sentence in the encrypted information is "Are kings and nobles born with a special destiny?", clicking on "kings and nobles" will display the corresponding annotation).

[0035] The type storage value of the information type is obtained as follows: All encrypted information of this information type is retrieved from the storage terminal. Each encrypted information is marked as belonging to the same category. Each category of information is assigned an information number j, j = 1, 2, ..., n. The information lookup value Ej of each category of information is obtained. The information lookup value coefficient is set to Xc, c = 1, 2, 3, ..., c; X1 < X2 < X3 < ... < Xc. Each information lookup value coefficient corresponds to a range of information lookup values, including (0, E1], (E1, E2], ..., (Ej-1, Ej]. When Ej ∈ (0, E1], the corresponding information lookup value coefficient is X1. The formula is then used... Retrieve the type storage value Fi for this information type, where n is the total number of information of the same type.

[0036] The information retrieval value for similar information is obtained as follows: All information retrieval logs for similar information prior to the current system time are retrieved; the retrieval duration of each log is retrieved; the sum of all retrieval durations is calculated and averaged to obtain the average retrieval duration, which is then marked as PJJ; the retrieval depth is retrieved; a preset retrieval depth is set (a system-preset value that can be modified according to actual needs); when the retrieval depth is greater than or equal to the preset depth, the log is marked as a deep retrieval log; when the retrieval depth is less than the preset depth, no action is taken; the total number of deep retrieval logs is marked as SDC; all deep retrieval logs are sorted according to their log numbers; the difference between the log numbers of two adjacent deep retrieval logs after sorting is calculated and the absolute value is taken to obtain the deep retrieval interval; all deep retrieval intervals are summed and averaged to obtain the average deep retrieval interval, which is then marked as MKR; and finally, the formula is used to calculate the deep retrieval interval. The information retrieval value Ej for this type of information is obtained, where a1 is the average retrieval time coefficient, a2 is the total number of deep retrieval logs coefficient, and a3 is the average deep retrieval interval coefficient. The value of a1 is 0.84, the value of a2 is 0.89, and the value of a3 is 0.62.

[0037] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0038] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0039] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0040] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0041] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0042] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0043] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0044] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A hierarchical encryption system for information based on the Internet of Things, characterized in that, Includes encryption classification module, encryption substitution module, and encryption analysis module; Before the information is initially stored, the encryption and classification module identifies the information type of the information and performs encryption and classification processing on the information based on the type storage value of the information type. Before a user accesses encrypted information in the storage terminal, the encryption replacement module obtains the decryption difficulty value of the encrypted information and determines whether the encrypted string of the encrypted information needs to be replaced based on the comparison result between the decryption difficulty value and its threshold. If the encrypted string of the encrypted information needs to be replaced, the encrypted string of the encrypted information is replaced. The encryption analysis module is used to generate an information decryption log after the user decrypts the encrypted information, and to generate an information viewing log after the user views the encrypted information.

2. The information hierarchical encryption system based on the Internet of Things according to claim 1, characterized in that, The information is encrypted and graded based on the type storage value of the information type. Specifically, before the information is stored for the first time, the information type is identified, the type storage value Fi of the information type is obtained, the storage encryption level of the information type is obtained according to the type storage value, the information is randomly encrypted according to the storage encryption level to form encrypted information, the encrypted string is sent to the corresponding user, and the encrypted information is sent to the storage end of the server through the Internet of Things. Each type of storage value Fi corresponds to a storage encryption level. The range of the type storage value Fi includes (0, F1], (F1, F2], ..., (Fi-1, Fi], and the storage encryption levels include storage encryption level 1, storage encryption level 2, ..., storage encryption level i-1, storage encryption level i. The higher the storage encryption level, the more characters are represented in the encrypted string of that information type.

3. The information hierarchical encryption system based on the Internet of Things according to claim 2, characterized in that, The type storage value of the information type is obtained as follows: All encrypted information of this information type is retrieved from the storage terminal; each encrypted information is marked as belonging to the same category; each category is assigned an information number j, j = 1, 2, ..., n; the information lookup value Ej for each category is obtained; the information lookup value coefficient is set to Xc; and the formula is used... Retrieve the type storage value Fi for this information type, where n is the total number of information of the same type.

4. The information hierarchical encryption system based on the Internet of Things according to claim 3, characterized in that, The information retrieval value for similar information is obtained as follows: All information retrieval logs for similar information prior to the current system time are retrieved; the retrieval duration of each log is retrieved; the sum of all retrieval durations is calculated and averaged to obtain the average retrieval duration, which is then marked as PJJ; the retrieval depth is retrieved; a preset retrieval depth is set; when the retrieval depth is greater than or equal to the preset depth, the log is marked as a deep retrieval log; the total number of deep retrieval logs is marked as SDC; all deep retrieval logs are sorted according to their log numbers; the difference between the log numbers of two adjacent deep retrieval logs after sorting is calculated and the absolute value is taken to obtain the deep retrieval interval; all deep retrieval intervals are summed and averaged to obtain the average deep retrieval interval, which is then marked as MKR. The formula is then used... The information retrieval value Ej for this type of information is obtained, where a1 is the average retrieval time coefficient, a2 is the total number of deep retrieval logs coefficient, and a3 is the average deep retrieval interval coefficient.

5. The information hierarchical encryption system based on the Internet of Things according to claim 4, characterized in that, The decryption difficulty value of encrypted information is obtained as follows: Obtain all decryption logs of the encrypted information since the last replacement of the encrypted string. Sort all decryption logs in chronological order of decryption time. Calculate the difference between the number of decryption errors of two adjacent pairs after sorting and take the absolute value to obtain the error fluctuation difference. Set an error fluctuation threshold difference. When the error fluctuation difference is greater than or equal to the threshold difference, increment the error fluctuation count by one. Sum all error fluctuation counts to obtain the total error fluctuation count, labeled as KRS. Sum the decryption error counts of all decryption logs and take the average to obtain the average decryption error count, labeled as WCP. Sum the information decryption time of all decryption logs and take the average to obtain the average information decryption time, labeled as LEY. Use the formula... The decryption difficulty value NDZ of the encrypted information is obtained, where b1 is the coefficient of the total number of error fluctuations, b2 is the coefficient of the average number of decryption errors, and b3 is the coefficient of the average information decryption time.

6. The information hierarchical encryption system based on the Internet of Things according to claim 5, characterized in that, Based on the comparison between the decryption difficulty value and its threshold, it is determined whether the encrypted string of the encrypted information needs to be replaced. Specifically, a decryption difficulty threshold is set, and when the decryption difficulty is less than the decryption difficulty threshold, the encrypted string of the encrypted information remains unchanged. When the decryption difficulty is greater than or equal to the decryption difficulty threshold, the encrypted information is marked as modified information. The information type of the modified information is obtained, the knowledge graph of each information type is obtained, and all encrypted information stored by the user on the storage side is obtained. Through knowledge graph association analysis, encrypted information of information types that are not related to the information type of the modified information is marked as irrelevant encrypted information. The information lookup value and decryption difficulty value of the modified information are obtained and marked as [x1, x2]. The information lookup value and decryption difficulty value of the irrelevant encrypted information are obtained and marked as [y1, y2]. The recommended modification value of the modified information and the irrelevant encrypted information is obtained using the cosine similarity formula. A recommended modification threshold is set. When the recommended modification value is less than the recommended modification threshold, the irrelevant encrypted information is marked as encrypted reference information. The encrypted reference information with the smallest recommended modification value is marked as encrypted replacement information. The encrypted string of the modified information is replaced with the encrypted string of the encrypted replacement information, and the encrypted string of the modified information is sent to the corresponding user.

7. The information hierarchical encryption system based on the Internet of Things according to claim 6, characterized in that, The user inputs an encrypted string for the encrypted information, and after the input is completed, a decryption log of the encrypted information is generated. Users can view encrypted information, and once the viewing is complete, an information viewing log for that encrypted information will be generated.

8. The information hierarchical encryption system based on the Internet of Things according to claim 7, characterized in that, The information decryption log includes the information decryption time, information decryption duration, and number of decryption errors.

9. A hierarchical information encryption system based on the Internet of Things according to claim 8, characterized in that, The information retrieval log includes user ID, log number, retrieval duration, and retrieval depth.

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