RFID-based multi-mode identity authentication and access method for dense shelves

Abstract

The application relates to the technical field of intelligent file management, and discloses a dense-shelf multi-mode identity authentication and access method based on RFID, which comprises the following steps: through an intelligent path algorithm, preset file access paths are shown to users, access data of the users are acquired, analysis and calculation are carried out, dynamic access indexes of the users are obtained, and behavior states of the users in the file access are analyzed; the file access permission level of the users is evaluated through a dynamic permission index, multi-dimensional factors such as the number of accessed files, the types of the files and historical access data are comprehensively considered, dynamic and flexible control of the user permission is realized, the safety of high-density files is ensured, the access efficiency of low-density files is considered, meanwhile, the path deviation degree, time period distribution deviation and abnormal actions in the file access process of the users are monitored and analyzed in real time through the dynamic access index, and dynamic checking and abnormal early warning of the operation behavior of the users are realized.

Description

Technical Field

[0001] This invention relates to the field of intelligent archive management technology, and in particular to a multi-mode identity authentication and access method for mobile shelving based on RFID. Background Technology

[0002] With the advancement of archival informatization, archival management is gradually transitioning from manual recording to intelligent management, with user identification and archival access being particularly crucial. During archival utilization, operators must first verify their legal identity through identity verification, then locate the target archive according to their permissions and complete the access action. The entire process requires accurate identity authentication, traceable access records, and efficient and convenient operation. Currently, mobile shelving, as a high-density archival storage device, is widely used in various archives and enterprise / institutional archives. Its management typically combines electronic tags or barcode technology to locate and inventory the archives within the shelving. Some systems also introduce simple authentication methods such as passwords and card swipes to control access permissions.

[0003] However, the traditional mobile shelving storage and retrieval management model still has obvious shortcomings in actual operation: On the one hand, the identification methods are relatively simple, mostly relying on password input or IC card swiping authentication. Once the password is leaked or the card is lost, there is a high risk of impersonation, misjudgment, or even unauthorized access to files, and there is a lack of dynamic verification of user operation behavior; on the other hand, the storage and retrieval process lacks intelligent linkage. Identity verification, shelving opening and closing, and file positioning are often disconnected from each other. It is impossible to adaptively adjust the storage and retrieval path and monitoring intensity according to factors such as file security level and user real-time permissions, making it difficult to balance the security protection of high-security files with the storage and retrieval efficiency of low-security files.

[0004] To address the aforementioned technical deficiencies, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to address the problem that traditional mobile shelving storage and retrieval management methods rely on a single method of identity verification, which mostly depends on password input or IC card swiping authentication. Once the password is leaked or the card is lost, there is a high risk of impersonation, misjudgment, or even unauthorized access to files. Furthermore, there is a lack of dynamic verification of user operation behavior.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a multi-mode authentication and access method for mobile shelving based on RFID, comprising the following steps:

[0007] Step 1: Use an RFID reader to scan all the RFID tags on the file boxes inside the shelving unit to establish a mapping database between the file tag ID and the grid location code. At the same time, classify the security level of the stored files and attach the corresponding security level information.

[0008] Step 2: When a user initiates a file access request in front of the operating terminal, the operating terminal collects the user's multimodal identity data, performs standardized processing, analyzes and calculates it to obtain the user's identity matching index, and performs static verification of the user's identity.

[0009] Step 3: After the user's static verification is passed, the user's dynamic permission data is obtained based on the access request entered by the user on the operation terminal, and the data is analyzed and calculated to obtain the user's dynamic permission index, and the user's file access permission is dynamically evaluated.

[0010] Step 4: Based on historical access data of the archives and big data from environmental monitoring, predict the physical health of the archives, and analyze and calculate the upper limit of the current user's access time to the archives according to the physical health threshold.

[0011] Step 5: After the dynamic permission verification is passed, the system sends a control command to the mobile shelving electric control system to drive the mobile shelving in the corresponding column to open and close automatically. Through the intelligent path algorithm, the system displays the preset file access path to the user, obtains the user's access data, analyzes and calculates it to obtain the user's dynamic access index, and analyzes the user's file access behavior.

[0012] Furthermore, the stored archives are classified into three security levels: regular archives, confidential archives, and top secret archives. The security level of the regular archives is [missing information]. The confidentiality level of the classified files is The confidentiality level of top-secret files is [missing information]. ,and .

[0013] Furthermore, the standardization process includes grayscale and normalization preprocessing of facial image data, format verification of card swipe data, encryption of password data, and removal of invalid and abnormal data.

[0014] Furthermore, the calculation process for the user's identity matching index is as follows:

[0015] S11. Obtain and analyze the user's multimodal identity data, including user face matching degree, user identity card swipe matching degree, and user password matching degree data.

[0016] S12. Calculate the user's identity matching index according to the following formula. : in, The user's face recognition matching score is calculated using the cosine similarity of the feature vectors, with a value range of [0,1]. The system checks the matching score of the user's ID card; a score of 1 indicates a match between the ID card information and the user's ID card information, while a score of 0 indicates a mismatch. This represents the password matching score; 1 indicates a correct password and 0 indicates an incorrect password. The preset face weight coefficient, The preset identity card weight coefficient, The preset password weight coefficient, and The user's identity matching index is used to reflect the degree of identity matching of the user;

[0017] S13. Obtain the preset identity matching threshold. User identity matching index Comparative analysis, when If the user's identity matches poorly, then the user's static identity verification failed.

[0018] S14, when If the result is positive, it indicates that the user's identity matches well and the user's static identity verification is successful.

[0019] Furthermore, the calculation process for a user's dynamic permission index is as follows:

[0020] S21. After the user's static verification is passed, the user's dynamic permission data is obtained and analyzed. The dynamic permission data includes the number of files accessed, the number of file types, and historical file access data.

[0021] S22. Calculate the user's dynamic permission index according to the following formula. : in, Preset basic user permissions, This represents the total number of files currently awaiting access by the user. For the first Number of files to be accessed For the first The confidentiality coefficient of each file to be accessed The user enters the number of file types for access operations on the terminal. For historical users on the first Number of times a type of file is accessed. The total number of times a user has accessed and accessed a file in history; the user's dynamic permission index is used to reflect the user's permission level for accessing and accessing files.

[0022] S23. Obtain the preset dynamic permission threshold. With the user's dynamic permission index Comparative analysis, when If the user's access permission level is high, then the file access request entered by the user on the terminal is approved.

[0023] S24, when If the user's access permission level is too low, the file access request entered by the user on the terminal will not be approved.

[0024] Furthermore, the process of limiting the maximum duration of a user's access to files is as follows:

[0025] S31. Collect temperature and humidity data, light intensity, and vibration frequency environmental parameters of the archive storage environment in real time through RFID readers and writers, and combine them with the archive's historical usage frequency, number of openings and closings, and storage location information to construct an archive physical health prediction model.

[0026] S32. Use machine learning algorithms to train and analyze the above data to generate a dynamic health score for each file.

[0027] S33. Calculate the maximum allowed access operation duration for the current user according to the following formula. : in, The standard access duration allowed when the archives are in good health. The actual physical health of the files to be accessed. The preset lower threshold for health is, and .

[0028] Furthermore, the calculation process for the user's dynamic access index is as follows:

[0029] S41. After the dynamic permission verification is passed, the user's access data is obtained and analyzed and calculated in combination with the maximum access operation time allowed by the current user. The access data includes the file access path feature value, the file access time period distribution deviation, and the abnormal action evaluation value during the file access process. The abnormal action evaluation value is obtained by comprehensively evaluating the abnormal action data during the user's file access process and using a scale. The larger the value of the abnormal action evaluation value, the higher the degree of abnormality of the user's actions during the file access process.

[0030] S42. Calculate the user's dynamic access index according to the following formula. : in, The actual file access path characteristic value for the user. To display the preset file access path characteristics to the user, To measure the actual deviation of the data access time distribution for users. This is the maximum allowable deviation during the preset file access period. This is an evaluation value for abnormal actions during the actual user file access process. This is the maximum permissible abnormal action assessment value during the file access process. The preset path weight coefficients, The preset time period weighting coefficient, The maximum allowed access operation duration for the current user. The dynamic access index represents the actual time a user spends accessing files. It reflects the degree of standardization of a user's actions during the file access process.

[0031] Furthermore, the process of analyzing user behavior in accessing files is as follows:

[0032] S51. Obtain the preset dynamic access threshold. With the user's dynamic access index Comparative analysis;

[0033] S52, when If this occurs, it indicates that the user's actions during the file access process are within acceptable limits and will not trigger the abnormal alarm system.

[0034] S53, when If this occurs, it indicates that the user's actions during the file access process are not in accordance with regulations, which will trigger the abnormal alarm system and send an alarm message to the staff.

[0035] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0036] This RFID-based multi-modal authentication and access method for mobile shelving effectively addresses the security vulnerabilities of traditional single authentication methods by introducing a multi-modal authentication system combining facial recognition, ID card swiping, and password input. Even if the password is leaked or the card is lost, multiple verifications are still required, significantly reducing the risk of impersonation and unauthorized access to files. Simultaneously, precise static identity verification based on a user identity matching index ensures that only authorized personnel can access the subsequent access process, further improving the accuracy and reliability of identity authentication. Furthermore, a dynamic permission index assesses the user's file access permission level, comprehensively considering multiple dimensions such as the number and type of files accessed, and historical access data, to dynamically manage user permissions. The flexible management system ensures the security of high-security archives while maintaining the efficiency of accessing low-security archives, avoiding overly rigid or lenient access permissions. Simultaneously, the system automatically plans and displays archive access paths through intelligent path algorithms, achieving intelligent linkage between identity verification, shelving opening and closing, and archive location. This reduces manual search and operation time, improving the convenience and overall efficiency of access operations. Furthermore, the system uses a dynamic access index to monitor and analyze path deviation, time period distribution deviation, and abnormal actions during user archive access in real time. This enables dynamic verification and anomaly warning of user behavior. Once abnormal behavior is detected, an alarm system is immediately triggered, effectively preventing improper operation or malicious behavior from threatening archive security. Attached Figure Description

[0037] Figure 1 A schematic diagram of the method flow of the present invention is shown. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Example:

[0040] like Figure 1 As shown, the RFID-based multi-mode authentication and access method for mobile shelving first involves a full inventory scan of the RFID tags on all file boxes within the shelving unit using an RFID reader. This establishes a mapping database between file tag IDs and grid location codes. Simultaneously, the stored files are classified into security levels and associated with corresponding security coefficients. It should be noted that the stored files are classified into three security levels: regular files, confidential files, and top secret files. The security coefficient for regular files is [missing information]. The confidentiality level of the classified files is The confidentiality level of top-secret files is [missing information]. ,and .

[0041] Then, when a user initiates a file access request at the terminal, the terminal collects the user's multimodal identity data, performs standardized processing, analyzes and calculates it to obtain the user's identity matching index, and performs static verification of the user's identity. It should be noted that the standardized processing includes grayscale and normalization preprocessing of facial image data, format verification of card swipe data, encryption of password data, and removal of invalid and abnormal data.

[0042] The user's identity matching index is calculated as follows:

[0043] S11. Obtain and analyze the user's multimodal identity data, including user face matching degree, user identity card swipe matching degree, and user password matching degree data.

[0044] S12. Calculate the user's identity matching index according to the following formula. : in, The user's face recognition matching score is calculated using the cosine similarity of the feature vectors, with a value range of [0,1]. The system checks the matching score of the user's ID card; a score of 1 indicates a match between the ID card information and the user's ID card information, while a score of 0 indicates a mismatch. This represents the password matching score; 1 indicates a correct password and 0 indicates an incorrect password. The preset face weight coefficient, The preset identity card weight coefficient, The preset password weight coefficient, and The user's identity matching index is used to reflect the degree of identity matching of the user. The higher the value of the identity matching index, the higher the degree of identity matching of the user. The lower the value of the identity matching index, the lower the degree of identity matching of the user.

[0045] S13. Obtain the preset identity matching threshold. User identity matching index Comparative analysis, when If the user's identity matches poorly, then the user's static identity verification failed.

[0046] S14, when If the user's identity matches well, the user's static identity verification is successful, and the user can enter a file access request on the terminal.

[0047] Then, after the user's static verification is passed, the user's dynamic permission data is obtained based on the access request entered by the user on the operation terminal, and analyzed and calculated to obtain the user's dynamic permission index, and the user's file access permission is dynamically evaluated.

[0048] The calculation process for a user's dynamic permission index is as follows:

[0049] S21. After the user's static verification is passed, the user's dynamic permission data is obtained and analyzed. The dynamic permission data includes the number of files accessed, the number of file types, and historical file access data.

[0050] S22. Calculate the user's dynamic permission index according to the following formula. : in, Preset basic user permissions (values ​​are integers from 10 to 100). This represents the total number of files currently awaiting access by the user. For the first Number of files to be accessed For the first The confidentiality coefficient of each file to be accessed Enter the number of file types to be accessed by the current user on the terminal (file types include, but are not limited to, personnel files, financial files, project data files, and machinery files). For historical users on the first Number of times a type of file is accessed. The total number of times a user accesses a file in history. The user's dynamic permission index is used to reflect the user's permission level for accessing files. The higher the value of the dynamic permission index, the higher the user's permission level for accessing files. The lower the value of the dynamic permission index, the lower the user's permission level for accessing files.

[0051] S23. Obtain the preset dynamic permission threshold. With the user's dynamic permission index Comparative analysis, when If the user's access permission level is high, then the file access request entered by the user on the terminal is approved.

[0052] S24, when If the user's access permission level is too low, the file access request entered by the user on the terminal will be rejected. If the user initiates a file access request again within 12 hours, the staff will re-evaluate the preset user basic permissions and re-judge the file access request entered by the user on the terminal. If the judgment is successful, the file can be accessed; otherwise, the user will be prohibited from accessing the file.

[0053] Subsequently, based on historical access data of the archives and big data from environmental monitoring, the physical health of the archives is predicted, and based on the physical health threshold, the upper limit of the current user's access time to the archives is analyzed and calculated.

[0054] The process of limiting the maximum duration of a user's access to files is as follows:

[0055] S31. Collect temperature and humidity data, light intensity, and vibration frequency environmental parameters of the archive storage environment in real time through RFID readers and writers, and combine them with the archive's historical usage frequency, number of openings and closings, and storage location information to construct an archive physical health prediction model.

[0056] S32. Use machine learning algorithms (such as random forest or LSTM neural network) to train and analyze the above data to generate a dynamic health score for each file. The score range is [0,1], where 0 represents a serious risk of damage and 1 represents an intact file.

[0057] S33. Calculate the maximum allowed access operation duration for the current user according to the following formula. : in, The standard access duration allowed when the archives are in good health. The actual physical health of the files to be accessed. The preset lower threshold for health is, and It should be noted that when At that time, the files will be retrieved and repaired by staff.

[0058] Finally, after the dynamic permission verification is passed, the system sends a control command to the mobile shelving electric control system to drive the mobile shelving in the corresponding column to open and close automatically. Through the intelligent path algorithm, the system displays the preset file access path to the user, obtains the user's access data, performs analysis and calculation, and obtains the user's dynamic access index to analyze the user's file access behavior.

[0059] The calculation process for a user's dynamic access index is as follows:

[0060] S41. After the dynamic permission verification is passed, the user's access data is obtained and analyzed and calculated in combination with the maximum access operation time allowed by the current user. The access data includes the file access path characteristic value, the file access time distribution deviation, and the abnormal action evaluation value during the file access process. The abnormal action evaluation value is obtained by comprehensively evaluating the abnormal action data of the user during the file access process (such as the user forcibly pulling the handle or manually pushing the shelf before the mobile shelving is completely stopped, the user frequently clicking the open and close buttons in a short period of time without taking out or putting back any files, and the RFID tag repeatedly showing the "identify-disappear-identify" state in a very short period of time, which may indicate that the user is trying to tear off or block the tag). The abnormal action evaluation value during the file access process is obtained by using a scale. The larger the value of the abnormal action evaluation value, the higher the degree of abnormality of the user's actions during the file access process.

[0061] S42. Calculate the user's dynamic access index according to the following formula. : in, The actual file access path characteristic value for the user. To display the preset file access path characteristics to the user, The deviation of the actual file access time distribution for users is calculated (the deviation is expressed as the ratio of the absolute value of the deviation from the normal access time to the total time period, with a value range of 0-1). This is the maximum allowable deviation during the preset file access period. This is an evaluation value for abnormal actions during the actual user file access process. This is the maximum permissible abnormal action assessment value during the file access process. The preset path weight coefficients, The preset time period weighting coefficient, The maximum allowed access operation duration for the current user. The dynamic access index represents the actual time a user spends accessing and retrieving files. It reflects the degree of standardization of the user's actions during the file access process. The higher the value of the dynamic access index, the less standard the user's actions during the file access process. The lower the value of the dynamic access index, the more standard the user's actions during the file access process.

[0062] The process of analyzing user data access behavior is as follows:

[0063] S51. Obtain the preset dynamic access threshold. With the user's dynamic access index Comparative analysis;

[0064] S52, when If this occurs, it indicates that the user's actions during the file access process are within acceptable limits and will not trigger the abnormal alarm system.

[0065] S53, when If the user's actions during the file access process are not in accordance with regulations, it will trigger the abnormal alarm system and send an alarm message to the staff. The staff will promptly identify the user and evaluate the user's actions during the file access process. If the evaluation is satisfactory, the user can continue to complete the file access operation; if the evaluation is unsatisfactory, the user will be prohibited from continuing to complete the file access operation.

[0066] In addition, when users perform file access operations, the RFID module reads the RFID tag information of the target file in real time during the operation, records the file transfer information, including access time, user, file number, access type, and uploads the transfer information to the management platform simultaneously to update the file management ledger and ensure that the ledger data is consistent with the actual access situation in real time.

[0067] This invention effectively addresses the security vulnerabilities of traditional single-authentication methods by introducing a multimodal identity authentication system combining facial recognition, ID card swiping, and password input. Even if the password is leaked or the card is lost, multiple verifications are still required, significantly reducing the risk of impersonation and unauthorized access to files. Simultaneously, precise static identity verification based on a user identity matching index ensures that only authorized personnel can access subsequent data, further improving the accuracy and reliability of identity authentication. Furthermore, a dynamic permission index assesses the user's file access permission level, comprehensively considering factors such as the number and type of files accessed, as well as historical access data, enabling dynamic and flexible control of user permissions, thus ensuring both security and safety. The system balances the security of high-security archives with the access efficiency of low-security archives, avoiding overly rigid or lenient access permissions. Simultaneously, an intelligent path algorithm automatically plans and displays the archive access path, enabling intelligent linkage between identity verification, shelving opening / closing, and archive location. This reduces manual search and operation time, improving the convenience and overall efficiency of access operations. Furthermore, a dynamic access index monitors and analyzes in real time the path deviation, time period distribution deviation, and abnormal actions during user archive access, achieving dynamic verification and anomaly warning for user behavior. Once abnormal behavior is detected, an alarm system is immediately triggered, effectively preventing improper operation or malicious behavior from threatening archive security.

[0068] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0069] 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.

[0070] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A multi-mode authentication and access method for mobile shelving based on RFID, characterized in that, Includes the following steps: Step 1: Use an RFID reader to scan all the RFID tags on the file boxes inside the shelving unit to establish a mapping database between the file tag ID and the grid location code. At the same time, classify the security level of the stored files and attach the corresponding security level information. Step 2: When a user initiates a file access request in front of the operating terminal, the operating terminal collects the user's multimodal identity data, performs standardized processing, analyzes and calculates it to obtain the user's identity matching index, and performs static verification of the user's identity. Step 3: After the user's static verification is passed, the user's dynamic permission data is obtained based on the access request entered by the user on the operation terminal, and the data is analyzed and calculated to obtain the user's dynamic permission index, and the user's file access permission is dynamically evaluated. Step 4: Based on historical access data of the archives and big data from environmental monitoring, predict the physical health of the archives, and analyze and calculate the upper limit of the current user's access time to the archives according to the physical health threshold. Step 5: After the dynamic permission verification is passed, the system sends a control command to the mobile shelving electric control system to drive the mobile shelving in the corresponding column to open and close automatically. Through the intelligent path algorithm, the system displays the preset file access path to the user, obtains the user's access data, analyzes and calculates it to obtain the user's dynamic access index, and analyzes the user's file access behavior.

2. The RFID-based multi-mode authentication and access method for mobile shelving units according to claim 1, characterized in that, The stored archives are classified into three levels: regular archives, confidential archives, and top secret archives. The confidentiality level of the regular archives is [missing information]. The confidentiality level of the classified files is The confidentiality level of top-secret files is [missing information]. ,and .

3. The RFID-based multi-mode authentication and access method for mobile shelving units according to claim 1, characterized in that, The standardization process includes grayscale and normalization preprocessing of facial image data, format verification of card swipe data, encryption of password data, and removal of invalid and abnormal data.

4. The RFID-based multi-mode authentication and access method for mobile shelving units according to claim 1, characterized in that, The user's identity matching index is calculated as follows: S11. Obtain and analyze the user's multimodal identity data, including user face matching degree, user ID card swipe matching degree, and user password matching degree data. S12. Calculate the user's identity matching index according to the following formula. : in, The user's face recognition matching score is calculated using the cosine similarity of the feature vectors, with a value range of [0,1]. The system checks the matching score of the user's ID card; a score of 1 indicates a match between the ID card information and the user's ID card information, while a score of 0 indicates a mismatch. This represents the password matching score; 1 indicates a correct password and 0 indicates an incorrect password. The preset face weight coefficient, The preset identity card weight coefficient, The preset password weight coefficient, and The user's identity matching index is used to reflect the degree of identity matching of the user; S13. Obtain the preset identity matching threshold. User identity matching index Comparative analysis, when If the user's identity matches poorly, then the user's static identity verification failed. S14, when If the result is positive, it indicates that the user's identity matches well and the user's static identity verification is successful.

5. The RFID-based multi-mode authentication and access method for mobile shelving units according to claim 1, characterized in that, The calculation process for a user's dynamic permission index is as follows: S21. After the user's static verification is passed, the user's dynamic permission data is obtained and analyzed. The dynamic permission data includes the number of files accessed, the number of file types, and historical file access data. S22. Calculate the user's dynamic permission index according to the following formula. : in, Preset basic user permissions, This represents the total number of files currently awaiting access by the user. For the first Number of files to be accessed For the first The confidentiality coefficient of each file to be accessed The user enters the number of file types for access operations on the terminal. For historical users on the first Number of times a type of file is accessed. The total number of times a user has accessed and accessed a file in history; the user's dynamic permission index is used to reflect the user's permission level for accessing and accessing files. S23. Obtain the preset dynamic permission threshold. With the user's dynamic permission index Comparative analysis, when If the user's access permission level is high, then the file access request entered by the user on the terminal is approved. S24, when If the user's access permission level is too low, the file access request entered by the user on the terminal will not be approved.

6. The RFID-based multi-mode authentication and access method for mobile shelving units according to claim 1, characterized in that, The process of limiting the maximum duration of a user's access to files is as follows: S31. Collect temperature and humidity data, light intensity, and vibration frequency environmental parameters of the archive storage environment in real time through RFID readers and writers, and combine them with the archive's historical usage frequency, number of openings and closings, and storage location information to construct an archive physical health prediction model. S32. Use machine learning algorithms to train and analyze the above data to generate a dynamic health score for each file. S33. Calculate the maximum allowed access operation duration for the current user according to the following formula. : in, The standard access duration allowed when the archives are in good health. The actual physical health of the files to be accessed. The preset lower threshold for health is, and .

7. The RFID-based multi-mode authentication and access method for mobile shelving units according to claim 1, characterized in that, The calculation process for a user's dynamic access index is as follows: S41. After the dynamic permission verification is passed, the user's access data is obtained and analyzed and calculated in combination with the maximum access operation time allowed by the current user. The access data includes the file access path feature value, the file access time period distribution deviation, and the abnormal action evaluation value during the file access process. The abnormal action evaluation value is obtained by comprehensively evaluating the abnormal action data during the user's file access process and using a scale. The larger the value of the abnormal action evaluation value, the higher the degree of abnormality of the user's actions during the file access process. S42. Calculate the user's dynamic access index according to the following formula. : in, The actual file access path characteristic value for the user. To display the preset file access path characteristics to the user, To measure the actual deviation of the data access time distribution for users. This is the maximum allowable deviation during the preset file access period. This is an evaluation value for abnormal actions during the actual user file access process. This is the maximum permissible abnormal action assessment value during the file access process. The preset path weight coefficients, The preset time period weighting coefficient, The maximum allowed access operation duration for the current user. The dynamic access index represents the actual time a user spends accessing files. It reflects the degree of standardization of a user's actions during the file access process.

8. The RFID-based multi-mode authentication and access method for mobile shelving units according to claim 1, characterized in that, The process of analyzing user data access behavior is as follows: S51. Obtain the preset dynamic access threshold. With the user's dynamic access index Comparative analysis; S52, when If this occurs, it indicates that the user's actions during the file access process are within acceptable limits and will not trigger the abnormal alarm system. S53, when If this occurs, it indicates that the user's actions during the file access process are not in accordance with regulations, which will trigger the abnormal alarm system and send an alarm message to the staff.

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