Safe access judgment method and system for saas platform designated driver

Abstract

The invention discloses a safe access judgment method and system for saas platform designated drivers. The invention relates to the technical field of SaaS online car-hailing platforms. Matching identity information submitted by the current driver from an identity library; and if the identity information does not exist in the identity library, carrying out OCR identification on the photo of the identity information. The identity information comprises an identity card and a driving license; wherein the OCR result is compared with the submitted identity information, and if the OCR result is consistent with the submitted identity information, automatic If not, manual reexamination is carried out; the effective identity document information database is used for verifying the authenticity of the identity of the driver; through strict face verification, certificate verification and certificate data authenticity verification, the authenticity and legality of the identity of the driver can be ensured, identity false use and fraudulent behaviors are effectively prevented, and thus the safety of designated driving service is improved. According to the method, the age, driving age, illegal behavior records and the like of the driver are comprehensively checked, the driver is ensured to meet platform requirements and laws and regulations, and the compliance of designated driving service is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of SaaS online car-hailing platform, and in particular to a method and system for judging the safety access of designated drivers on a SaaS platform. Background Art

[0002] At present, the driver access mechanism in the designated driver service industry lacks a comprehensive and systematic regulatory system, resulting in the service providers showing a single and fragmented characteristics in driver recruitment and safety management, making it difficult to effectively identify and control potential high-risk driver groups. This situation contains multiple risks, which seriously threatens the safety and reliability of designated driver services. The authenticity and consistency verification of certificate information has become the primary challenge. Due to the limitations of the manual review process, the certificate information submitted by the driver does not match the actual information, and the certificate photos are forged or tampered with. These fraudulent behaviors can easily circumvent the existing review mechanism and bury safety risks for subsequent services. In particular, when the driver has a major violation record, if it cannot be effectively screened, it will directly threaten the personal safety of the customer.

[0003] The inconsistency between the person and the certificate is another major hidden danger. Some individuals who do not meet the requirements for designated drivers illegally enter the designated driver industry by stealing, borrowing or forging other people's certificates. This behavior not only harms the interests of customers and exposes them to unknown security risks, but also infringes on the legitimate rights and interests of those whose identities are impersonated, causing unnecessary legal disputes and social problems. What is more complicated is that some drivers with a record of illegal and irregular activities can easily switch to other platforms to continue to provide designated driver services after being banned by a certain platform. This phenomenon of cross-platform mobility makes it difficult for service providers to fully grasp the historical behavior records of drivers, effectively assess their risk levels, and thus cannot guarantee the security and stability of the service.

[0004] The chauffeur service industry urgently needs to establish a complete driver access and risk assessment system. By strengthening information verification technology, strictly reviewing qualifications, implementing multi-channel identity authentication, and establishing a cross-platform information sharing mechanism, it will fundamentally improve the safety management level of chauffeur services and ensure the healthy development of customers, drivers and the entire industry.

[0005] To this end, the present invention proposes a method and system for determining the safety access of designated drivers on a SaaS platform. Summary of the invention

[0006] In view of this, the present invention hopes to provide a method and system for determining the safety access of designated drivers on the SaaS platform, so as to solve or alleviate the technical problems existing in the prior art, namely, how to further verify the cross-platform flow phenomenon on the basis of enhancing the face verification, document verification and document data authenticity verification. And at least provide a beneficial option for this; the technical solution of the present invention is implemented as follows:

[0007] First, a method for determining the safety access of designated drivers on the SaaS platform:

[0008] 1. Overview:

[0009] The present invention aims to build a comprehensive and rigorous safe access mechanism for designated drivers to ensure the safety and reliability of designated driver services. By integrating the identity risk library and the driver's license risk library, the system can efficiently identify and intercept drivers with risks, while using OCR technology to improve the accuracy and efficiency of information review. The solution also sets a series of strict access rules, including multi-dimensional assessments such as age, driving experience, account security, violation records, multi-service provider registration, and historical service points to ensure that drivers meet the platform requirements. In addition, the solution also focuses on the training and real-name authentication of drivers, improves the professional quality of drivers through examinations and the issuance of work clothes, and ensures the authenticity of the driver's identity through real-name ID verification. Finally, through irregular sampling of driver information, the solution can continuously monitor the driver's compliance, promptly identify problems and take corresponding measures, thereby ensuring the high-quality operation of the designated driver service.

[0010] (II) Technical solution:

[0011] In the SaaS online car-hailing platform, after receiving the user's security access detection instruction, the following steps are started.

[0012] 2.1 Step S1, data input:

[0013] Match the identity information submitted by the current driver from the identity database; if the identity information does not exist in the identity database, perform OCR recognition on the photo of the identity information. Identity information includes the ID card and driver's license; compare the OCR result with the submitted identity information, if they are consistent, the review will be automatically passed; if they are inconsistent, manual review will be conducted;

[0014] 2.1.1 Step S100, identity database matching:

[0015] Match the identity information submitted by the current driver from the identity database. The identity database is a database that stores legal and valid identity document information and is used to verify the authenticity of the driver's identity. If there is a record in the identity database that matches the submitted information, it means that the driver's identity information has been verified and the system can proceed to the next step.

[0016] 2.1.2 Step S101, OCR recognition (if the identity database does not match):

[0017] If the driver's ID card information does not exist in the identity database, the identity information photo submitted by the driver will be processed by OCR (optical character recognition). OCR technology automatically reads and analyzes the text information on documents such as ID cards and driver's licenses, including name, ID card number and driver's license number.

[0018] 2.1.3 Step S102, compare OCR results with submitted information:

[0019] The OCR result is compared with the identity information submitted by the driver to verify the consistency of the two. If the OCR result is consistent with the submitted information, it means that the driver's identity information is authentic and reliable, and the system can automatically review and pass it to the next step.

[0020] 2.1.4 Step S103, manual review (if inconsistent):

[0021] If the OCR result is inconsistent with the submitted information, it indicates that there is a possibility of identity error or fraud. The driver's application will be marked as a suspected problem case and transferred to the manual review stage.

[0022] 2.2 Step S2, access rule verification: automatically check the driver's basic information, account information, entry record, registration information and / or historical information; including:

[0023] Automatically check whether the driver's age and driving experience meet the platform requirements;

[0024] Automatically check the driver's account security status, such as whether the Alipay account is marked abnormal;

[0025] Automatically check whether the driver has any violations or past entry records;

[0026] Automatically detect whether a driver frequently registers with multiple service providers;

[0027] Automatically check the driver's historical service score to decide whether to limit the service area;

[0028] 2.2.1 Step S200, basic information verification:

[0029] Check the driver's basic information, including age and driving experience, to confirm whether they meet the entry standards set by the platform. For example, the platform requires that drivers must be at least a certain age (such as 23 years old) and have a certain number of years of driving experience (such as more than 3 years) before they can register as a designated driver.

[0030] 2.2.2 Step S201, Account Information Verification:

[0031] Check the driver's account security status, such as whether payment-related accounts (such as Alipay accounts) are marked as abnormal.

[0032] 2.2.3 Step S202, verification of entry record and registration information:

[0033] Check whether the driver has any violations or past registration records, and detect whether the driver frequently registers with multiple service providers.

[0034] This is to prevent drivers from circumventing regulation or committing fraud by registering on different platforms. If the system finds that a driver has engaged in such behavior, it may take restrictive measures or reject his / her application for registration.

[0035] 2.2.4 Step S203, historical service verification:

[0036] Check the driver's historical service score; if the driver's historical service score is lower than the threshold set by the platform, limit his service scope or lower his service priority to ensure that passengers can get high-quality chauffeur service.

[0037] 2.3 Step S3, driver training:

[0038] If the verified driver is a new driver, the examination venue will be arranged automatically; if the verified driver is not a new driver, enter S4.

[0039] Based on the driver's registration information, settlement record or historical data, determine whether the verified driver is a new settlement driver. If the judgment result is a new settlement driver, the examination venue and time will be automatically arranged. If the judgment result is not a new settlement driver (that is, the driver has registered on the platform and received training), it will directly enter S4 without repeated training.

[0040] 2.4 Step S4, real-name ID verification:

[0041] Authentication verification is performed based on the identity information and facial information provided by the driver; if the verification passes, the driver becomes an official driver; if the verification fails, the driver will not be able to accept orders.

[0042] 2.4.1 Step S400, information collection:

[0043] Drivers are required to provide valid identification information, including ID number and name, as well as face photos or real-time face video streams.

[0044] 2.4.2 Step S401, information comparison:

[0045] The identity information provided by the driver is compared with the database of the management department or third-party authority to verify the authenticity and validity of the identity information.

[0046] Use facial recognition technology to verify the facial photo or real-time facial video stream provided by the driver to ensure that the facial information is consistent with the identity information and that the operation is performed by the individual.

[0047] 2.4.3 Step S402, verification result processing:

[0048] If both identity information and face verification are passed, the driver will be marked as a formal driver and allowed to accept orders on the platform. If identity information or face verification fails, the system will mark the driver as verification failure and prohibit him from accepting orders on the platform. At the same time, the system can notify the driver of the reason for the verification failure and provide an opportunity or guidance for re-verification.

[0049] 2.5 Step S5, random inspection of driver information:

[0050] The verification and reduction process of steps S1 to S4 is performed irregularly, the sampling results are recorded in the system, and the drivers are classified and processed. For compliant drivers, they are allowed to continue to provide services; for non-compliant drivers, warnings, restricted service scope or / and bans are taken.

[0051] (III) Mechanism for solving technical problems:

[0052] 3.1 Enhanced face verification and document checking Using face recognition technology, the face photo submitted by the driver is compared with the photo on the document to ensure the consistency between the two. This can effectively prevent identity fraud and improve the authenticity of the driver's identity. Through OCR technology (optical character recognition), the ID card, driver's license and other document information submitted by the driver is automatically read and compared with the identity database in the system to verify the validity of the document. At the same time, the authenticity of the document photo will be verified to prevent the use of forged or tampered documents.

[0053] 3.2 Verification of the authenticity of the documents and information The driver's entry records on the platform and other designated driving service providers are recorded to form a database of past entry records. This helps the platform identify whether the driver has cross-platform mobility. When a new driver submits an entry application, the system will automatically compare his information with the past entry record database to check whether the driver has a record of entry on other platforms. For drivers who frequently change platforms, the system will conduct a key review to assess whether they have any violations or service quality issues.

[0054] Second, a safety access judgment system for SaaS platform designated drivers:

[0055] like Figure 3 As shown, the system is used to implement the security access judgment method described above, which includes:

[0056] (1) User management module responsible for driver registration, login and information update.

[0057] (2) The certificate verification module uses OCR technology to read the certificate information submitted by the driver: compare it with the identity database of the data storage layer to verify the authenticity of the certificate; interact with the security and management layer to record the security log of the certificate verification process.

[0058] (3) The face verification module uses facial recognition technology to compare the face photo submitted by the driver with the ID photo: It works in conjunction with the ID verification module to ensure the authenticity and consistency of the driver's identity.

[0059] (4) The module responsible for querying the driver's past entry records on other designated driving platforms: interacts with the data storage layer to store and retrieve the driver's past entry records. Cooperates with other modules in the business logic layer to analyze the cross-platform mobility of drivers.

[0060] (5) Business logic processing module that receives requests from the user interaction layer and calls other modules to execute business logic: Conducts driver qualification review based on business rules, such as age, driving experience, violation records, etc. Processes cross-platform flow verification logic to evaluate the driver's service quality and compliance.

[0061] (6) The payment and settlement module is responsible for handling payment and settlement transactions between drivers and the platform (although it is not directly related to security access, it is part of the complete system): interacting with the data storage layer to record payment and settlement information. Connecting with the third-party payment platform interface to realize the flow of funds.

[0062] (7) Message push and notification module responsible for pushing system notifications, review results and order status information to drivers and administrators: interacts with the user interaction layer, business logic layer and data storage layer to ensure timely delivery of information.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] (1) Improved security: Through strict facial verification, document verification, and document data authenticity verification, the present invention can ensure the authenticity and legitimacy of the driver's identity, effectively prevent identity theft and fraud, and thus improve the security of the designated driver service. The present invention conducts a comprehensive review of the driver's age, driving experience, violation record, etc. to ensure that the driver meets the platform requirements and laws and regulations, and enhances the compliance of the designated driver service.

[0065] (2) Optimizing service quality: Through the evaluation of historical service scores and past entry records, the present invention can identify drivers with poor service quality or violations, and then take corresponding management measures to optimize the overall service quality. The present invention focuses on the phenomenon of cross-platform mobility. By comparing past entry records and analyzing driver behavior, potential cross-platform mobility risks can be discovered and handled in a timely manner to ensure the stable operation of the platform and the compliance of drivers. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0067] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0068] Figure 2 It is a schematic diagram of the steps of executing the method of the present invention;

[0069] Figure 3 It is a schematic diagram of the system composition of the present invention. DETAILED DESCRIPTION

[0070] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below;

[0071] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0072] Explanation of relevant terms:

[0073] (1) OCR recognition: Use optical character recognition technology to automatically read and analyze text information on documents such as identity cards and driver's licenses.

[0074] (2) Identity database: A database that stores legal and valid identity document information and is used to verify the authenticity of the driver's identity.

[0075] (3) Manual review: When the automatic review fails or there are doubts, a manual review is performed again.

[0076] (4) Historical service score: A score based on the driver’s past service performance, used to evaluate the driver’s service quality.

[0077] (5) Illegal behavior: any behavior of the driver that violates the platform regulations or laws and regulations during the service process.

[0078] (6) Previous registration records: the driver’s previous registration and service records on the platform or other designated driver service providers.

[0079] (7) Warning: A minor penalty for drivers who violate traffic rules to remind them to follow legal procedures.

[0080] (8) Restriction of service scope: A management measure taken against problematic drivers, restricting them to accepting orders only within a specific area.

[0081] (9) Ban: A punitive measure taken against drivers who seriously violate the rules, prohibiting them from providing services on the platform.

[0082] Embodiment 1: Figures 1-2 As shown, this embodiment discloses a method for determining the safety access of designated drivers on a SaaS platform; the SaaS online car-hailing platform periodically conducts random checks on driver information in terms of driver qualifications, service rules, and real-name ID cards. The purpose of the random checks is to ensure that the driver's credentials are valid and that he or she has not replaced an order during the service process, so as to ensure the safety and compliance of the service. During each random check, the following operation process is executed:

[0083] (I) Document review:

[0084] A. ID card information review:

[0085] (1) Risk database matching: After the system receives the ID card information submitted by the driver, it first matches it with the identity risk database. If the ID card information does not exist in the risk database, the system will enter the review process.

[0086] (2) System review: The system performs OCR on the ID card photo submitted by the driver and extracts the text information on the ID card. The OCR result is compared with the identity information submitted by the driver. If they are consistent, the system automatically passes the review. If they are inconsistent, the system enters the manual review stage and marks the risk level.

[0087] (3) Manual review: The manual reviewer reviews the ID card information based on the risk level reference provided by the system. If the review fails, the identity information is added to the identity risk database and the risk level is marked. If the review passes, it enters the next stage of review.

[0088] (4) Risk database existence processing: If the ID card information exists in the risk database, it will directly enter the manual review and provide a risk level reference. Based on the manual review results, the risk level will be updated or the number of times the review has been passed will be recorded.

[0089] B. Driver's license information review: The driver's license information review process is similar to the ID card information review process, including risk library matching, system review, manual review, and risk library existence processing.

[0090] C. Verification of access rules:

[0091] (1) Age rule detection: The system automatically checks whether the age on the driver’s ID card meets the platform requirements and whether the ID card is valid.

[0092] (2) Driving experience rule detection: The system calculates whether the driver’s driving experience meets the minimum entry age requirement specified by the platform based on the date the driver’s driver’s license was obtained, and checks whether the driver’s license is valid.

[0093] (3) Account security check: The system checks whether the driver’s Alipay account is in normal status and whether there is any outstanding debt or blacklist behavior.

[0094] (4) Risk rule detection: The system queries whether the driver has any violations or past entry records on the platform to assess his or her risk level.

[0095] (5) Registration platform detection: The system checks whether the driver has frequently registered with multiple service providers recently to prevent cross-platform mobility. If there is frequent registration, the system will restrict the entry or service scope.

[0096] (6) Driver service check: The system checks the driver’s historical service score. If the service score is low, the driver’s service scope will be restricted.

[0097] (II) Driver training:

[0098] For new drivers, the system will designate a test site for test training. After passing the test, the driver will be issued work clothes and necessary materials. If the test fails or the work clothes are not worn as required, the training will not be passed.

[0099] (III) Real name ID verification: When the driver passes the review and logs in to the driver terminal, he / she needs to verify his / her real name ID. The system uses facial verification technology to verify the consistency between the driver's identity information and facial information. After passing the verification, the driver becomes an official driver and can provide designated driver service.

[0100] Through OCR technology and facial authentication technology, the system can automatically identify and verify the driver's ID card and driver's license information, as well as facial information, to ensure the authenticity and legitimacy of the driver's identity. This helps prevent identity theft and fraud and improve service security. The system can effectively identify cross-platform mobility by querying whether the driver has frequently registered with multiple service providers recently and comparing the driver's entry records on different platforms. This helps the platform to promptly discover and deal with potential cross-platform mobility risks, ensuring the stable operation of the platform and the compliance of drivers.

[0101] Embodiment 2: Based on Embodiment 1, this embodiment further discloses the Python execution program of the solution described in Embodiment 1:

[0102]

[0103]

[0104]

[0105]

[0106] In the above program, the risk databases for ID cards and driver licenses are implemented using the dictionaries ID_RISK_DB and DRIVER_LICENSE_RISK_DB. The driver data is implemented using the list DRIVER_DATA.

[0107] The ocr_recognize function performs the OCR recognition process, receives the image and returns the recognized ID card information. The face_verification function performs the face verification process, receives the ID card information and face image, and returns the verification result. The review_documents function reviews the driver's ID card and driver's license information. First, check whether the ID card information is in the risk database. If it is, it will enter the manual review; otherwise, it will enter the system review. The system review compares the OCR recognition result with the information submitted by the driver. If there is a discrepancy, it will enter the manual review.

[0108] The verify_driver function verifies the consistency between the driver's identity information and facial information through facial authentication technology. The spot_check_drivers function randomly selects a specified number of drivers from the driver list for spot checks. For each driver sampled, the document review, driver training (if no training) and real name verification (if no verification) are performed in sequence.

[0109] Set the number of drivers to be spot checked and call the spot_check_drivers function to perform the spot check. Output the spot check results, showing the training status and verification status of each spot checked driver.

[0110] All the above embodiments only express the implementation methods of the relevant practical applications of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached claims. It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0111] For those skilled in the art, it can be further appreciated that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0112] At the same time, those skilled in the art can understand that all or part of the processes in all the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

Claims

1. A method for determining the safety access of a designated driver on a SaaS platform, characterized in that: In the SaaS online car-hailing platform, after receiving the user's security access detection instruction, the following steps are executed: S1, matching the identity information submitted by the current driver from the identity database; if the ID card information does not exist in the identity database, performing OCR recognition on the photo of the identity information; S2, automatically checking the driver's basic information, account information, check-in record, registration information and / or historical information; S3: If the driver being verified is a new driver, the test site will be arranged automatically; if the driver being verified is not a new driver, the process will proceed to S4; S4, performs authentication verification based on the identity information and facial information provided by the driver; if the verification passes, the driver becomes a formal driver; if the verification fails, the driver cannot accept orders.

2. The security access determination method according to claim 1, characterized in that: In said S1, the identity information includes an ID card and a driver's license; The OCR result is compared with the submitted identity information. If they are consistent, they will be automatically reviewed and approved; if they are inconsistent, they will enter manual review.

3. The security access determination method according to claim 1, characterized in that: In S2, the basic information includes: Automatically check whether the driver's age and driving experience meet the platform requirements; Automatically check the driver's account security status, such as whether the Alipay account is marked abnormal; Automatically check whether the driver has any violations or past entry records; Automatically detect whether a driver frequently registers with multiple service providers; Automatically check the driver's historical service points to decide whether to limit the service area.

4. The security access determination method according to claim 3, characterized in that: The execution process of S2 includes: S200, checking the basic information of the driver, including age and driving experience, to confirm whether he meets the admission criteria set by the platform; S201, checking the driver's account security status; S202, querying whether the driver has any violations or past registration records, and detecting whether the driver frequently registers with multiple service providers; S203, checking the driver's historical service score; if the driver's historical service score is lower than the threshold set by the platform, restricting his service scope or lowering his service priority.

5. The security access determination method according to claim 1, characterized in that: In S3, based on the driver's registration information, settlement record or historical data, it is determined whether the verified driver is a new driver; if the judgment result is a new driver, the examination venue and time are automatically arranged; if the judgment result is not a new driver, directly enter S4.

6. The security access determination method according to claim 1, characterized in that: The execution process of S4 includes: S400 requires the driver to provide valid identity information, including ID number and name, as well as face photo or real-time face video stream; S401, comparing the identity information provided by the driver with the database to verify the authenticity and validity of the identity information.

7. The security access determination method according to claim 6, characterized in that: In S4, if both the identity information and face verification are passed, the driver will be marked as an official driver and allowed to accept orders on the platform; if the identity information or face verification fails, the driver will be marked as verification failure and prohibited from accepting orders on the platform.

8. The security access determination method according to claim 1, characterized in that: It also includes S5, random inspection of driver information: irregularly executing the reduction process such as steps S1 to S4, recording the inspection results in the system, and classifying the drivers; allowing compliant drivers to continue to provide services; and issuing warnings, restricting service scope, or / and banning non-compliant drivers.

9. A system for implementing the security access determination method according to any one of claims 1 to 8, characterized in that: The system comprises: Responsible for the driver registration, login and information update user management module; A certificate verification module that uses OCR technology to read the certificate information submitted by the driver; A face verification module that uses face recognition technology to compare the face photo submitted by the driver with the ID photo; a module responsible for querying the driver's past entry records on other designated driving platforms; The business logic processing module receives requests from the user interaction layer and calls other modules to execute business logic; The payment and settlement module is responsible for handling payment and settlement transactions between drivers and the platform.

10. The system according to claim 9, characterized in that: It also includes a message push and notification module responsible for pushing system notifications, review results and order status information to drivers and administrators.

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