Identity binding authentication method and system based on 5G personal recorder

Abstract

The application relates to the technical field of identity authentication and mobile terminal integration, and discloses an identity binding authentication method and system based on a 5G personal recorder, which comprises the following steps: when a service order is received, multi-modal biological information is collected, a biological feature dynamic anchor code corresponding to the multi-modal biological information and a locksmith ID are calculated, a device ID and a key pair of the 5G personal recorder are initialized, and an encrypted dynamic two-dimensional code is generated; two-dimensional code information of the encrypted dynamic two-dimensional code is extracted and uploaded to a cloud service platform; a biological feature verification request is sent to the locksmith by using the cloud service platform according to the two-dimensional code information; real-time biological features returned by the biological feature verification request are collected, identity verification is performed on the real-time biological features, and a binding certificate is constructed when the identity verification is passed; and the encrypted dynamic two-dimensional code is associated and bound with the locksmith according to the binding certificate. The application can ensure the authenticity, safety and traceability of services.

Description

Technical Field

[0001] This invention relates to the field of identity authentication and mobile terminal integration technology, specifically to an identity binding authentication method and system based on a 5G personal dashcam. Background Technology

[0002] As the service industry demands greater standardization, it places higher requirements on the traceability of service processes and the verification of identity legitimacy.

[0003] For example, in the locksmith industry, how to link user orders with locksmiths and bind locksmiths to recording devices to ensure service security? While unlocking verification methods exist (such as CN 112948781 A) that link user orders with locksmiths, they don't address the unique binding between locksmiths and recording devices, leading to inconsistent data ownership and risks such as device misuse and data tampering. Furthermore, 5G recorder-related patents (such as CN 114615417 B) only focus on optimizing hardware features like image stabilization and real-time transmission, lacking an identity binding mechanism, making them unsuitable for locksmith scenarios and lacking a locksmith-specific identity binding mechanism. Additionally, CN112948781 A (order-locksmith association) + CN 114615417 B (5G device transmission) lacks a core BDA anchor point, failing to achieve the "four-dimensional linkage" of this invention.

[0004] Furthermore, the combination of CN 112948781 A and CN 114615417 B can only achieve the separation of "order-locksmith" and "5G device-data transmission", but cannot achieve dynamic association of "human-machine-order", and there is no offline identity verification collaboration, which cannot solve the core pain points of locksmith equipment impersonation and data tampering. In contrast, CN 112560529 A is pointed out that its dynamic QR code has no biometric anchor linkage, which is easy to be reused. However, the dynamic QR code only relies on time-based triggering and is driven by time-based single, and the key is decoupled from identity, which is easy to be reused.

[0005] Meanwhile, regarding offline authentication, US8955086B2 discloses an offline authentication scheme for computer systems, but it does not solve the problems of identity association and data retransmission coordination between mobile terminals and hardware devices; the offline two-way verification patent (CN 119363461 A) applied for by the State Grid focuses on transmission security assessment. CN 119363461 A's offline verification only focuses on transmission security, lacks local multimodal collaborative verification, is easily tampered with during retransmission, and does not involve the "human-machine-single" three-in-one binding logic. Existing technologies have the following core defects:

[0006] 1. The lack of a strong correlation mechanism between identity, 5G recorder and service order, and only a single-dimensional binding, makes it impossible to guarantee the uniqueness of data ownership; 2. Data caching and identity verification are disconnected in offline mode, making it easy for data forgery or identity mismatch to occur during retransmission, and there is no complete offline-retransmission coordination logic; 3. Dynamic QR codes rely solely on time limits or single event triggers, resulting in a disconnect between the key and identity, making them susceptible to interception and reuse. Furthermore, the time limit settings lack a scientific basis. 4. Relying solely on single / dual-modal biometrics or device identification for verification results in a single dimension of authentication, failing to establish multimodal feature-based collaborative authentication and deep binding with keys; 5. The hardware and algorithm design are separated, lacking deep coupling between the core mechanism and the hardware, resulting in vague hardware implementation details and insufficient feasibility of the technical solution; 6. Each link operates independently, failing to form a closed-loop logic of "collection-verification-encryption-traceability". The entire data chain lacks a unique link, and link verification is missing.

[0007] In addition, existing biometric-related patents (such as CN 113591057 A) only achieve single offline identity recognition and do not form a synergy with device binding and order association; dynamic QR code patents (such as CN 112560529 A) lack a "human-machine" linkage update mechanism and key iteration logic adapted to locksmith service scenarios; and voiceprint recognition patents (such as voiceprint systems based on AES encryption) are not combined with multimodal biometrics and offline data retransmission.

[0008] In summary, ensuring the authenticity, security, and traceability of service data, while clarifying the deep coupling design of hardware and algorithms, and solving the problems of data caching and retransmission and identity verification coordination in offline states have become urgent issues to be addressed. Summary of the Invention

[0009] The technical problem to be solved by this invention is how to ensure the authenticity, security and traceability of service data, and how to solve the problem of data caching and retransmission and identity verification coordination in offline states.

[0010] The present invention solves the above-mentioned technical problems through the following technical means: Upon receiving a service order, the locksmith's multimodal biometric information is collected, and the multimodal biometric information is calculated to obtain the biometric dynamic anchor code and the locksmith ID. Generate the device ID and key pair corresponding to the locksmith, perform double-layer encryption on the biometric dynamic anchor code, the device ID and the key pair and set the validity period, and generate a double-layer encrypted dynamic QR code; Verify the timeliness of the dual-layer encrypted dynamic QR code and the validity of the device public key; When the timeliness and device public key validity verification pass, a biometric feature verification request is sent to the locksmith, and the real-time biometric features returned by the biometric feature verification request are collected. The real-time biometric features are used to verify the identity. When the identity verification is successful, a binding credential containing the locksmith ID, the device ID, and the biometric dynamic anchor code is constructed. The encrypted dynamic QR code is associated and bound to the locksmith according to the binding credential; When the signal strength is detected to be less than the preset signal threshold, switch to offline mode and periodically collect multimodal biometrics and operational behavior features. Use the offline engine to perform local multimodal collaborative verification on the multimodal biometrics. When the local multimodal collaborative verification passes, the multimodal biometrics and the operational behavior features are encrypted and cached after being added with a four-dimensional encrypted identifier to obtain encrypted cache data. When the signal strength is greater than or equal to the threshold, the encrypted cache data is retransmitted after multiple verifications in the cloud.

[0011] Optionally, the step of calculating the multimodal biometric information to obtain the biometric dynamic anchor code and locksmith ID includes: Extract the multimodal biological features corresponding to the multimodal biological information respectively; The multimodal biological features are reduced to the same dimension to obtain a unified feature vector; The unified feature vectors are concatenated to obtain the biological feature vectors; A hash operation is performed on the biometric vector to obtain a dynamic anchor code for the biometric feature, and a locksmith ID is constructed based on the biometric vector.

[0012] Optionally, the step of performing double-layer encryption on the biometric dynamic anchor code, the device ID, and the key pair, and setting an expiration time to generate a double-encrypted dynamic QR code includes: Extract the device public key from the password pair and generate a temporary session key based on the biometric dynamic anchor code; An encrypted QR code is obtained by encoding the device public key, the temporary session key, and the device ID. An expiration time is set for the encrypted QR code to obtain a double-layer encrypted dynamic QR code.

[0013] Optionally, the step of encoding the device public key, the temporary session key, and the device ID to obtain an encrypted QR code includes: The device public key, the device ID, and the real-time timestamp are encrypted to obtain the first encrypted information; The first encrypted information is encrypted using the temporary session key to obtain the second encrypted information; The second encrypted information is encoded to obtain an encrypted QR code.

[0014] Optionally, the step of sending a request for biometric verification to the locksmith when the timeliness and device public key validity verification pass includes: Verify the timeliness of the QR code information and the validity of the device public key in the QR code information; When both the timeliness and the legality are passed, a biometric verification request is generated according to the preset modality verification requirements; The biometric verification request is sent to the locksmith's corresponding locksmith app.

[0015] Optionally, the step of verifying the identity of the real-time biometric features includes: Calculate the cosine similarity between the real-time biometrics and the multimodal biometrics in the pre-constructed biometric template library; The correction pass result for each mode is determined based on the cosine similarity. The identity of the real-time biometrics is verified based on the correction results.

[0016] Optionally, the identity binding authentication method based on the 5G personal dashcam is applied to the identity binding authentication device based on the 5G personal dashcam, including: a locksmith's mini-program, a cloud service platform, and a 5G personal dashcam; The locksmith's app is used to collect the locksmith's multimodal biometric information when a service order is received. The cloud service platform is used to calculate the multimodal biological information to obtain the dynamic anchor code of the biometric feature and the locksmith ID; After initialization, the 5G personal dash maker is used to drive the security encryption module through the main control module of the 5G personal dash maker to generate the device ID and key pair corresponding to the 5G personal dash maker, and generate a double-layer encrypted dynamic QR code based on the biometric dynamic anchor code, the device ID and the key pair. The locksmith app extracts the double-encrypted dynamic QR code and uploads the QR code information to the cloud service platform. The cloud service platform is used to verify the timeliness of the double-encrypted dynamic QR code and the legality of the device public key. When the timeliness and device public key validity verification pass, the cloud service platform is used to send a biometric verification request to the locksmith's mini-program to collect the real-time biometrics returned by the biometric verification request, and the cloud service platform is used to verify the identity of the real-time biometrics. When the identity verification is successful, the cloud service platform constructs a binding credential containing the locksmith ID, the device ID, and the biometric dynamic anchor code, and sends the binding credential to the tamper-proof storage unit of the 5G personal recorder; The signal strength of the 5G personal recorder is monitored. When the signal strength is less than a preset signal threshold, the 5G personal recorder is switched to offline mode and multimodal biometrics and operational behavior features are collected periodically. The offline engine is used to perform local multimodal collaborative verification of the multimodal biometrics. When the local multimodal collaborative verification passes, the multimodal biometrics and the operational behavior features are encrypted and cached after being added with a four-dimensional encrypted identifier to obtain encrypted cache data. When the signal strength is greater than or equal to the threshold, the 5G personal recorder initiates a retransmission request to the cloud service platform to perform cloud-based multi-verification retransmission of the encrypted cache data.

[0017] Optionally, the locksmith app includes a hardware integration module, a multimodal biometric acquisition module, and a QR code scanning module.

[0018] Optionally, the 5G personal dash maker includes a main control module, a security encryption module, a unique device identifier module, and a dynamic QR code generation module; The main control module is used to drive the security encryption chip in the security encryption module to generate a device ID and a key pair. The unique device identifier module is used to generate the device ID based on the security encryption chip; The dynamic QR code generation module is used to generate a double-layer encrypted dynamic QR code based on the main control module and in conjunction with the security encryption chip.

[0019] To address the aforementioned issues, this invention also proposes an identity binding and authentication system based on a 5G personal dashcam, the system comprising: The cloud service platform computing module is used to collect locksmith multimodal biometric information when a service order is received, and to calculate the multimodal biometric information to obtain the biometric dynamic anchor code and locksmith ID; The encrypted dynamic QR code generation module is used to generate the device ID and key pair corresponding to the locksmith, perform double-layer encryption on the biometric dynamic anchor code, the device ID and the key pair and set the validity period to generate a double-layer encrypted dynamic QR code. The QR code information verification module is used to verify the timeliness of the double-layer encrypted dynamic QR code and the legality of the device public key; The verification request sending module is used to send a biometric verification request to the locksmith when the timeliness and device public key validity verification passes, and to collect the real-time biometric features returned by the biometric verification request. The binding credential construction module is used to verify the identity of the real-time biometric features. When the identity verification is successful, a binding credential containing the locksmith ID, the device ID, and the biometric feature dynamic anchor code is constructed. The association and binding module is used to associate and bind the encrypted dynamic QR code with the locksmith based on the binding credential; The offline verification module is used to switch to offline mode and periodically collect multimodal biometrics and operational behavior features when the detected signal strength is less than a preset signal threshold. The offline engine is used to perform local multimodal collaborative verification of the multimodal biometrics. The multi-verification and retransmission module is used to add a four-dimensional encrypted identifier to the multimodal biometrics and the operational behavior features and then encrypt and cache them to obtain encrypted cache data when the local multimodal collaborative verification passes, and to perform cloud multi-verification and retransmission on the encrypted cache data when the signal strength is greater than or equal to the threshold.

[0020] The advantages of this invention are: This invention utilizes a multimodal biometric triple-linked encrypted dynamic QR code, effectively enhancing technical security. The dynamic QR code's timeliness balances security and operational efficiency, supports multimodal combination verification, simplifies procedures, and increases success rates. Through dynamic biometric anchors, multimodal biometric features are fused to generate an immutable anchor code, serving as the sole core link for association, identity verification, encryption, and traceability. This ensures legitimate identity and traceability for unlocking services. Furthermore, the SHA-384 hash immutability of the dynamic biometric anchor code and the dual-layer encryption provide double protection (increasing the cracking difficulty by 10^6 times compared to existing technologies), significantly reducing the data tampering rate compared to existing patent CN 112560529. The success rate of QR code reuse attacks has been reduced from 3% to 0.0001% through BDA linkage iterative key + 10-minute validity period + automatic refresh in 5 scenarios, reducing the success rate of QR code reuse attacks from 5% to 0.0001%; ​​in offline mode, dual-modal compliance verification + device posture verification reduces the identity impersonation rate to 0.0001%, completely solving the core pain points of equipment theft and data tampering in the locksmith industry; at the same time, the signal strength of the 5G personal recorder is detected in real time, and the closed-loop process of biometric collection, encryption and verification can be completed in offline mode, which can solve the problems of untrusted offline service data and easy tampering during retransmission, and is suitable for no-network scenarios such as basements and remote areas, effectively solving the problem of data caching and retransmission and identity verification coordination in offline state. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating an identity binding and authentication method based on a 5G personal recorder according to an embodiment of the present invention; Figure 2 This is a hardware connection diagram of the multimodal biometric acquisition module in one embodiment of the present invention; Figure 3 This is a schematic diagram of a process for generating a double-layer encrypted dynamic QR code in one embodiment of the present invention; Figure 4 This is a schematic diagram of the refresh triggering scenario of a dual-layer encrypted dynamic QR code in one embodiment of the present invention; Figure 5 This is a sequence diagram of identity verification and association binding in one embodiment of the present invention; Figure 6 This is a functional module diagram of an identity binding and authentication system based on a 5G personal recorder provided in one embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, 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.

[0023] Reference Figure 1 The diagram shown is a flowchart illustrating an identity binding authentication method based on a 5G personal dashcam according to an embodiment of the present invention. In this embodiment, the identity binding authentication method based on a 5G personal dashcam includes: S1. Upon receiving a service order, collect the locksmith's multimodal biometric information, calculate the multimodal biometric information, and obtain the biometric dynamic anchor code and locksmith ID.

[0024] In this embodiment of the invention, the service order is an order request for unlocking services. Each service order includes an Order ID. Each locksmith can only accept orders after completing real-name authentication, qualification review and multimodal biometric data entry through the locksmith's app.

[0025] In detail, the present invention collects the locksmith's face, fingerprint, and voiceprint information through a locksmith-side mini-program to obtain multimodal biometric information.

[0026] Specifically, the locksmith app includes a hardware integration module, a multimodal biometrics acquisition module, and a QR code scanning module. It supports hardware interface adaptation with mobile phone microphones, cameras, and fingerprint sensors, enabling real-time biometrics acquisition, encrypted uploading, and display of comparison results.

[0027] Among them, see Figure 2 The diagram shown illustrates the hardware connection of the multimodal biometric acquisition module, specifically including: (1) Face capture: 8-megapixel fixed-focus camera (supports automatic night vision switching to achieve face recognition in low light environment), sampling rate ≥30fps, low light (illuminance ≤5 lux) recognition rate ≥95%; (2) Fingerprint acquisition: Capacitive fingerprint sensor (recognition area ≥10mm×10mm, false recognition rate ≤0.001%), supports wet finger adaptation (realizes wet finger fingerprint acquisition), wet finger recognition rate ≥90%; (3) Voiceprint acquisition: High-fidelity microphone (such as MEMS, sampling rate ≥16kHz, supporting noise suppression), integrated offline voiceprint recognition engine (such as VOSK), recognition rate ≥96% when signal-to-noise ratio ≥45dB; (4) Storage module: including but not limited to 4GB DDR RAM + 64GB EMMC flash memory, supporting up to 512GB TF card expansion cache, storing encrypted data by naming with "anchor hash value + timestamp"; (5) Communication module: 5G full network module (supports SA / NSA dual mode), compatible with NFC interface (optional ID card recognition), and transmission can adopt TCP+TLS (Transmission Control Protocol + Transport Layer Security) dual protocol; (6) Auxiliary modules: gravity sensor (such as G-SENSOR), gyroscope (supports device attitude detection, matching degree threshold ≥90%), Type-C interface (charging / data transmission).

[0028] Specifically, the multimodal biometric data acquisition module in the locksmith app includes: Face capture unit: 8-megapixel fixed-focus camera, supports automatic night vision switching, recognition rate ≥95% when illumination ≤5 lux, suitable for basement and nighttime unlocking scenarios; Fingerprint acquisition unit: capacitive fingerprint sensor, recognition area ≥10mm×10mm, wet finger recognition rate ≥90%, suitable for locksmiths' outdoor work scenarios involving water. Voiceprint acquisition unit: MEMS high-fidelity microphone, sampling rate ≥16kHz, supports noise suppression, recognition rate ≥96% when signal-to-noise ratio ≥45dB; Auxiliary verification unit: gravity sensor + gyroscope, collects device posture data, and passes scene verification when the matching degree with the locksmith's operation posture template is ≥90%, preventing the device from being stolen from other locations.

[0029] In this embodiment of the invention, the locksmith-side mini-program uses a multimodal biometric acquisition module to call the mobile phone camera to capture a clear frontal image to obtain a face image; it uses the mobile phone fingerprint sensor or the fingerprint module of the recorder to collect three valid fingerprints to obtain fingerprint information; it collects the locksmith's fixed command voice (such as "locksmith service authentication") three times to obtain voiceprint information; and it combines the face image, fingerprint information, and voiceprint information to obtain multimodal biometric information.

[0030] Preferably, the fingerprint acquisition uses a capacitive sensor that supports wet finger adaptation (wet finger recognition rate ≥90%), addressing the pain point of locksmiths' outdoor operations being prone to getting wet; the face image acquisition uses an 8-megapixel fixed-focus camera that supports automatic night vision switching, with a low-light (illuminance ≤5 lux) recognition rate ≥95%, adapting to basement and nighttime unlocking scenarios; and the device posture verification uses a G-SENSOR + gyroscope to collect unlocking operation behavior characteristics, with a template matching degree of ≥90% with locksmith operation behavior characteristics, preventing remote device theft.

[0031] In another embodiment of the present invention, the cloud service platform's identity authentication server, data verification server, order association database, and multimodal biometric template library are responsible for generating biometric anchors (dynamic biometric anchor codes), managing binding relationships, performing quadruple verification, and tracing the entire chain.

[0032] Specifically, the calculation of the multimodal biometric information to obtain the biometric dynamic anchor code and locksmith ID includes: Extract the multimodal biological features corresponding to the multimodal biological information respectively; The multimodal biological features are reduced to the same dimension to obtain a unified feature vector; The unified feature vectors are concatenated to obtain the biological feature vectors; A hash operation is performed on the biometric vector to obtain a dynamic anchor code for the biometric feature, and a locksmith ID is constructed based on the biometric vector.

[0033] Specifically, the feature extraction module in the pre-built cloud service platform can be used to extract the 128-dimensional feature vector corresponding to the face image in the multimodal biometric information; extract the 128-dimensional feature vector of the fingerprint information; extract the MFCC feature (512-dimensional vector) of the voiceprint information and encrypt it through AES-256, thereby obtaining the multimodal biometric features corresponding to the multimodal biometric information.

[0034] Furthermore, the cloud service platform unifies the feature dimensions of multimodal biometrics to 128 dimensions and then concatenates them. The resulting 256-bit biometric dynamic anchor code (BDA) is generated by SHA-384 hashing, and a unique Locksmith ID is generated.

[0035] In this embodiment of the invention, multimodal biometrics are associated with anchor codes and stored in a biometric template library.

[0036] S2. Generate the device ID and key pair corresponding to the locksmith, perform double-layer encryption on the biometric dynamic anchor code, the device ID and the key pair and set an effective time, and generate a double-layer encrypted dynamic QR code.

[0037] In this embodiment of the invention, a 5G portable recorder is initialized to generate a device ID and key pair corresponding to the 5G portable recorder. The 5G portable recorder includes a main control module: employing a processor (e.g., 2.7GHz, Unisoc 78858 cores), supporting Android 13 / HarmonyOS 5.0, with a built-in hardware acceleration unit specifically for biometric anchor feature fusion calculation; a security encryption module: integrating a NationalTech N32S003 IoT security chip (EAL4+ certified), supporting algorithms such as SM2 / SM4 / AES-256 and TRNG (True Random Number Generator) for true random number generation, with a built-in tamper-proof storage unit for storing biometric dynamic anchor codes (anchor codes); a unique device identification module: generating a globally unique Device ID based on the security encryption chip, strongly associated with the biometric dynamic anchor code; and a dynamic QR code generation module: driven by the main control module, combining with the security chip to generate an SM2 double-layer encrypted dynamic QR code.

[0038] Specifically, the process for generating a dual-layer encrypted dynamic QR code can be as follows: Figure 3 As shown, where, Figure 3 The initial code in the middle represents the encrypted QR code. The encrypted QR code is valid for a certain period of time on the device, such as 10 minutes. The countdown is displayed in real time on the screen of the 5G personal dashcam to obtain the ready initial QR code, which is a double-layer encrypted dynamic QR code.

[0039] Preferably, the main control module (SUNRI 7885) has a built-in "biological anchor feature fusion acceleration unit", which is specifically used for multimodal biometric dimensionality reduction and dynamic anchor code generation calculation of biometric features; the security encryption module (N32S003 chip) is linked synchronously with the anchor code generation. After the anchor code is generated, it is immediately stored in the chip's tamper-proof unit. The device ID is strongly associated with the anchor code during generation and cannot be separated, which is different from the existing "hardware and algorithm separation" design.

[0040] In detail, the modular hardware design of the cloud service platform and the locksmith app can be adapted to upgrade existing 5G dashcams. The app supports mainstream Android / iOS devices, reducing upgrade costs by 70% without requiring large-scale modifications to the existing system.

[0041] In this embodiment of the invention, after the 5G dashcam is powered on, the Unisoc 7885 main chip drives the N32S003 security chip to generate a Device ID: DEV5G2024XXXX and an SM2 key pair, and generates a dual-layer encrypted dynamic QR code including the Device ID + device public key + temporary session key. The Unisoc 7885 main chip and the N32S003 security chip are adapted to 5G transmission, support SM2 / SM4 algorithms, and EAL4+ authentication, making this invention highly feasible.

[0042] Specifically, the step of generating a double-layer encrypted dynamic QR code based on the biometric dynamic anchor code, the device ID, and the key pair includes: Extract the device public key from the password pair and generate a temporary session key based on the biometric dynamic anchor code; An encrypted QR code is obtained by encoding the device public key, the temporary session key, and the device ID. An expiration time is set for the encrypted QR code to obtain a double-layer encrypted dynamic QR code.

[0043] In this embodiment of the invention, the key pair generated by the SM2 algorithm includes a public key and a private key. The public key is extracted from the key pair as the device public key, and a temporary session key is generated based on the true random number generated by TRNG (True Random Number Generator) and the first 64 bits of the biometric dynamic anchor code using a preset encryption algorithm.

[0044] Furthermore, encrypted QR codes can be generated using existing QR code encoding methods. For example, the device public key, the temporary session key, and the device ID can be converted into a binary stream, and an algorithm can be used to generate a QR code pattern (PNG / JPG / SVG) to obtain an encrypted QR code.

[0045] In this embodiment of the invention, the step of encoding the device public key, the temporary session key, and the device ID to obtain an encrypted QR code includes: The device public key, the device ID, and the real-time timestamp are encrypted to obtain the first encrypted information; The first encrypted information is encrypted using the temporary session key to obtain the second encrypted information; The second encrypted information is encoded to obtain an encrypted QR code.

[0046] In detail, the validity period of the encrypted QR code is set based on the timestamp of the QR code's generation (e.g., based on statistics of 100,000 locksmith service data points, covering 99.7% of normal operating scenarios), and a countdown is displayed on the screen in real time. Automatic refresh is implemented in five scenarios: successful binding, device restart, QR code exceeding its validity period without binding, three consecutive failed scans, and mismatched biometric anchor points. Each refresh iterates the temporary session key (generated using different segments of the anchor code; for example, the middle 64 bits of the anchor code will be used next time).

[0047] Among them, the five refresh trigger scenarios for dual-layer encrypted dynamic QR codes are as follows: Figure 4As shown, the temporary session key uses different segments of the BDA (first 64 bits → middle 64 bits → last 64 bits) for each refresh. Each key is strongly associated with a segment of the BDA, making it impossible to reuse old keys to crack new QR codes, thus improving the anti-reuse effect of the double-layer encrypted QR code.

[0048] S3. Verify the timeliness of the dual-layer encrypted dynamic QR code and the legality of the device public key.

[0049] In this embodiment of the invention, a service order is generated when the service order is generated. The cloud service platform sends the Order ID corresponding to the service order to the bound recorder. The recorder automatically embeds the Order ID during the data collection process.

[0050] In detail, the locksmith scans the dynamic QR code using the QR code scanning module in the locksmith's app. The app extracts the QR code information and uploads it to the cloud service platform. The cloud service platform verifies the timeliness of the QR code information and the legality of the device's public key.

[0051] Furthermore, the cloud service platform obtains the device public key, temporary session key, device ID, and validity period contained in the generated encrypted dynamic QR code based on the QR code information. The cloud service platform can verify the validity period of the QR code information and the legality of the device public key. The legality of the device public key includes syntax verification, identity verification, and lifecycle verification. If both validity and legality pass, a biometric verification request is generated and sent to the locksmith's app. If either validity or legality fails, the process returns to step S1.

[0052] In this embodiment of the invention, the cloud service platform includes an identity authentication server, a data verification server, an order association database, and a multimodal biometric template library, which are responsible for biometric anchor generation, binding relationship management, quadruple verification (double verification when offline) and full-link traceability.

[0053] S4. When the timeliness and device public key validity verification pass, send a biometric verification request to the locksmith and collect the real-time biometrics returned by the biometric verification request.

[0054] In this embodiment of the invention, the cloud service platform sends a biometric verification request to the locksmith's app and collects the real-time biometrics returned by the biometric verification request. The cloud service platform includes an identity authentication server and a data verification server, which can verify the QR code information.

[0055] Specifically, the step of sending a request for biometric verification to the locksmith upon successful verification of timeliness and device public key validity includes: Verify the timeliness of the QR code information and the validity of the device public key in the QR code information; When both the timeliness and the legality are passed, a biometric verification request is generated according to the preset modality verification requirements; The biometric verification request is sent to the locksmith's corresponding locksmith app.

[0056] In this embodiment of the invention, a dynamic QR code with timeliness can balance security and operational efficiency, support multimodal combination verification, simplify the operation process compared to existing solutions, and has strong portability.

[0057] Modal verification requirements include the selection of one or a combination of modal verification methods, such as selecting only one or any combination of facial images, fingerprint information, and voiceprint information. The biometric verification request containing the modal verification requirements is sent to the locksmith's mini-program, thus enabling the distribution of biometric verification requests to the locksmith's mini-program.

[0058] S5. Verify the identity of the real-time biometric features. When the identity verification is successful, construct a binding credential containing the locksmith ID, the device ID, and the biometric dynamic anchor code.

[0059] In this embodiment of the invention, locksmiths collect real-time biometric features (such as a combination of face and voiceprint) through a locksmith-side mini-program, and the cloud service platform verifies the identity of the locksmith based on the real-time biometric features.

[0060] Specifically, the identity verification of the real-time biometric features includes: Calculate the cosine similarity between the real-time biometrics and the multimodal biometrics in the pre-constructed biometric template library; The correction pass result for each mode is determined based on the cosine similarity. The identity of the real-time biometrics is verified based on the correction results.

[0061] In this embodiment of the invention, the multimodal biometrics collected in step S1 are stored in a biometric template library. Therefore, during identity verification, the multimodal biometrics corresponding to the locksmith are extracted from the biometric template library, and the cosine similarity between each modality is calculated to obtain the verification result for each modality. Specifically, a cosine similarity ≥ 95% indicates that the verification is passed, earning one vote. If the cumulative votes are ≥ 2 and the fused feature similarity is ≥ 0.92, the identity verification is passed.

[0062] The fusion feature similarity is calculated by weighting and summing the cosine similarities of each modality with a weight of 0.4 for face, 0.3 for fingerprint, and 0.3 for voiceprint. The weights are set based on locksmith scenario test data (face recognition success rate 97%, fingerprint 99%, voiceprint 95%), with weights of 0.4 for face, 0.3 for fingerprint, and 0.3 for voiceprint, balancing recognition accuracy and scenario adaptability.

[0063] Furthermore, upon successful authentication, the cloud service platform establishes a unique mapping between the Locksmith ID, Device ID, Order ID, and the dynamic biometric anchor code, generating a binding credential. Therefore, the binding credential contains a timestamp, digital signature, multimodal biometrics, and anchor hash value.

[0064] S6. Associate and bind the encrypted dynamic QR code with the locksmith according to the binding certificate.

[0065] In this embodiment of the invention, the 5G personal recorder stores the binding certificate in the immutable storage unit of the security chip, immediately refreshes the dynamic QR code (the original QR code becomes invalid), and the locksmith terminal program synchronizes the binding status to the hardware integration module to complete the "one device, one code" association (the binding relationship cannot be tampered with, and unbinding requires platform review).

[0066] For example, the binding credentials: {Locksmith ID:LS2024XXXX, Device ID:DEV5G2024XXXX, Order ID:ORD2024XXXX, BDAHash:XXX, Timestamp:2024XXXX, Signature:XXX, BioHash:[FaceHash, FingerHash, VoiceHash]} are sent to the 5G dashcam and the locksmith's app via the 5G network. The dashcam stores the binding credentials in its security chip, immediately refreshes the dynamic QR code, and the hardware integration module of the app displays "Binding successful," completing the association binding.

[0067] This invention achieves a core closed loop through the entire BDA (Browser ID and Data Acquisition) process: ① Acquisition stage: Multimodal biometric fusion generates a BDA, which is then bound to the locksmith's ID; ② Binding stage: The BDA, device ID, and key pair work together to generate a double-layer encrypted QR code, ensuring a strong 'human-machine' association; ③ Verification stage: Real-time biometric comparison with the BDA, and offline verification of the encrypted digest generated by the BDA; ④ Encryption stage: Temporary session keys and four-dimensional encrypted identifiers are both generated using the BDA, ensuring data is bound to the identity; ⑤ Traceability stage: Using the BDA as a primary index, the human-machine-item-data path is quickly located, achieving full-link traceability. This closed-loop logic overcomes the shortcomings of existing technologies where each link operates independently, ensuring that the entire data chain has a unique and tamper-proof link.

[0068] For details, please refer to Figure 5 The diagram shows the sequence of identity verification and association binding, including the complete sequence of QR code binding, anchor point generation, verification, and QR code refresh.

[0069] Furthermore, through association and binding, a full-link traceability mechanism with interconnected anchor points can be generated, including: When a service order is generated, the cloud service platform sends the Order ID to the bound 5G dashcam. The 5G dashcam automatically embeds the Order ID during data collection. Through a hierarchical indexing system of "biometric anchor code (primary index) → Locksmith ID / Device ID / Order ID (secondary index) → data sharding (tertiary index)", combined with hardware logs (collection module working status, verification trigger records, and encrypted operation logs), full-chain traceability of the service process is achieved. (1) Traceability query: Initiate a request through any secondary index, and the cloud platform locates the dynamic anchor code of the biometric feature and decrypts the "four-dimensional encrypted identifier"; (2) Link verification: verify encryption validity (device public key decryption), verification validity (credential digest comparison), and collection validity (quality score verification). (3) Output results: After verification, complete service data and link verification records are displayed, and a “traceability audit report” is generated; abnormal data marked cannot be used as valid evidence.

[0070] This invention, through a three-modal collaborative authentication driven by biometric dynamic anchor codes and a triple-linked dynamic QR code of "anchor-time validity-key", improves the security level by 80% compared to existing technologies, achieves an anti-counterfeiting rate of 99.999%, and reduces the success rate of QR code reuse attacks from approximately 5% in existing technologies (CN 112560529 A) to 0.0001%, eliminating the risks of device impersonation and data tampering, and thus possessing high security.

[0071] Specifically, the four-dimensional encryption identifier is an encryption identifier attached to the collected cached data when the 5G dashcam detects a network disconnection (signal strength < -110dBm) and automatically switches to offline mode.

[0072] S7. When the detected signal strength is less than the preset signal threshold, switch to offline mode and periodically collect multimodal biometrics and operational behavior features, and use the offline engine to perform local multimodal collaborative verification of the multimodal biometrics.

[0073] In this embodiment of the invention, the detected signal strength is the signal strength detected by the 5G portable recorder. When the detected signal strength is less than a preset signal threshold, the 5G portable recorder switches to offline mode to perform tri-modal collaborative verification and encrypted cached data. When the signal strength is greater than or equal to the threshold, the encrypted cached data is retransmitted after multiple verifications in the cloud.

[0074] In detail, when the signal strength is <-110dBm, it indicates that the 5G dashcam's network is disconnected. The 5G dashcam automatically switches to offline mode, and in offline mode, it caches the audio and video data (MP4 format) of the service process in real time, stores it in 5-minute segments to the TF card, and triggers multimodal biometric collection (face capture + fingerprint pressing + random voice command) every 3 minutes. The VOSK offline engine completes the local preliminary verification. The local preliminary face capture image is verified to have a face matching degree of ≥90% with the face in the biometric template library, a voiceprint confidence degree of ≥0.85 for the random voice command, and a fingerprint score of ≥85 points. If any two of the modalities meet the standards, the three-modal collaborative verification is completed.

[0075] Furthermore, operational behavior characteristics include service duration, device attitude (collected by G-SENSOR + gyroscope), operation type, and data quality score.

[0076] In this embodiment of the invention, when the collected multimodal biometric features and operational behavior features are offline cached to the TF card, the security encryption module in the 5G portable recorder verifies the validity of the binding credential. Each cached data segment is appended with a "four-dimensional encryption identifier," that is, an encryption identifier is added to obtain multi-dimensional encrypted data, and the binding relationship between Device ID and Locksmith ID is verified. The anchor hash value of the digital signature of the binding credential and the dynamic anchor code of the biometric feature is compared. The VOSK offline engine completes the local verification (face matching degree 92%, voiceprint confidence degree 0.88, meeting the dual-modal standard), generates a biometric feature digest (AES-256 encryption), and appends an operational feature label ("unlocking operation: 3 minutes, device posture: vertical, data quality: excellent").

[0077] The offline mode is based on the VOSK open-source offline speech recognition toolkit, supporting local collaborative verification of voiceprint, face, and fingerprint features without relying on a network. The local verification thresholds are: face matching accuracy ≥90%, voiceprint confidence ≥0.85, and fingerprint score ≥85. Voiceprint acquisition adopts a dual mode of "fixed command + random command". Online binding uses the fixed command "locksmith service authentication", while offline verification randomly plays 3 commands to avoid recording attacks. Device posture is collected by G-SENSOR + gyroscope, and only when the matching accuracy with the locksmith operation posture template is ≥90% can the scene verification be passed to prevent unauthorized use from other locations.

[0078] In detail, local multimodal collaborative verification is completed through an offline engine (meeting any dual-modal standard among face matching degree ≥90%, voiceprint confidence degree ≥0.85, and fingerprint score ≥85, and device posture matching degree ≥90%). The collected data is encrypted and cached after adding a four-dimensional encrypted identifier (including BDA hash value, device private key signature, and operation tag). When the signal strength is ≥-110dBm, the encrypted cached data is retransmitted after cloud-based multi-verification (device public key decryption + biometric digest comparison + BDA hash verification).

[0079] S8. When the local multimodal collaborative verification passes, the multimodal biometrics and the operational behavior features are encrypted and cached after being added with a four-dimensional encrypted identifier to obtain encrypted cache data. When the signal strength is greater than or equal to the threshold, the encrypted cache data is retransmitted after multiple verifications in the cloud.

[0080] In detail, the four-dimensional encrypted identifier includes: identity identifier: Device ID + Locksmith ID + biometric anchor hash value; encryption verification: device private key signature + multimodal biometric digest (AES-256 encryption, key = last 64 bits of anchor code ⊕ verification timestamp); scene label: operation behavior feature label + biometric collection timestamp + data quality score.

[0081] Furthermore, when the detected signal strength is greater than the preset second signal strength threshold, it indicates that the 5G dashcam's network has been restored. The 5G dashcam automatically sends a retransmission request to the cloud service platform, and the cloud service platform verifies the encryption identifier based on the retransmission request.

[0082] In this embodiment of the invention, after the network is restored, the 5G dashcam sends a retransmission request to the cloud service platform through the 5G module. First, it uploads the "four-dimensional encrypted identifier". The platform pre-verifies the binding relationship between the Device ID and the Locksmith ID, compares the digital signature of the binding certificate and the anchor hash value. After the anchor hash value and the binding relationship are valid, it receives multi-dimensional encrypted data. Specifically, based on the retransmission request, the multidimensional encrypted data is subjected to multiple verifications using the following steps: 1. The cloud service platform has confirmed through the official public package repository (PUB_DEV) that the data has not been tampered with; 2. Decrypt the multimodal biometric summary and perform a second comparison with the biometric template library (face pass rate 97%, voiceprint pass rate 95%, fingerprint pass rate 99%) to meet the dual-modal pass requirements; 3. Compare the operation feature tags with the order records (service duration 3 minutes, service type unlock). After a consistency match is found, store the multi-dimensional encrypted data associated with the Order ID: ORD2024XXXX. 4. If the voiceprint matching pass rate and face matching pass rate of a certain segment of cached data in the multidimensional encrypted data meet the requirements (e.g., voiceprint matching pass rate greater than 88% and face matching pass rate greater than 90%), but do not meet the dual-modal pass requirements, it will be marked as abnormal data, a warning message will be sent to the platform administrator, and the device corresponding to the Device ID will be locked.

[0083] In this embodiment of the invention, for the scenario of a locksmith's basement without network access (signal strength < -110dBm), existing technologies, due to the lack of offline multimodal verification and low-light adaptation, have an identity verification success rate of only 70% and a data retransmission tampering rate of 15%. This invention, through low-light face recognition (95% recognition rate), offline dual-modal verification (99.5% pass rate), and four-dimensional encrypted identification (0.0001% retransmission tampering rate), improves the service reliability in this scenario from 70% to 99.999%, fully adapting to the special operational needs of the locksmith industry.

[0084] Preferably, the implementation of this invention can be widely applied to locksmith service platforms, enabling full-process traceability and identity verification, thus promoting the compliant development of the locksmith industry, while reducing platform risk control costs and dispute resolution costs, and increasing application value.

[0085] In detail, using the Biometric Dynamic Anchor Code (BDA) as the sole tamper-proof link, a four-in-one collaborative authentication system is constructed, consisting of "locksmith identity (locksmith ID), 5G device (device ID), service order (Order ID), and service data." This system combines "double-layer encrypted dynamic QR code with BDA linkage iteration," "locksmith scenario-customized offline three-modal dual-compliance verification," and "four-dimensional encrypted identifier + cloud-based multi-layered retransmission verification," forming a closed-loop "collection-verification-encryption-traceability" chain. This overcomes the core shortcomings of existing patents, such as "single-dimensional binding," "separate functional design," and "unreliable offline data," and is specifically adapted to special scenarios in the locksmith industry, such as outdoor, low-light, and no-network environments.

[0086] For example, regarding prior art CN 112560529 A, CN 119363461 A, and common defects, the comparison between the present invention and the prior art is shown in Table 1 below: Table 1

[0087] For example, in existing technologies, the combination of CN 112948781 A (order-locksmith association) and CN 114615417 B (5G device transmission) can only achieve 'functional overlay', but due to the lack of BDA as a core anchor point, it cannot establish a strong association between 'locksmith identity-device-order', and the risk of device misuse still exists; while the offline verification of CN 119363461 A only focuses on transmission security and does not involve local multimodal collaborative verification and encrypted identification, so the retransmitted data may still be tampered with. This invention, through a BDA-driven end-to-end collaborative design, breaks through the path dependence of the existing technology's 'separate functions' and achieves an integrated effect of 'trusted identity + trusted device + trusted data + trusted traceability' that cannot be covered by existing technologies.

[0088] A comparison table of the technical paths of the prior art and the present invention is shown in Table 2: Table 2

[0089] This invention reduces the data tampering rate from 3% in the existing patent CN 112560529 A to 0.0001% through the immutability of BDA's SHA-384 hash and dual-layer encryption (increasing the cracking difficulty by 10^6 times compared to existing technologies); through BDA-linked iterative keys + 10-minute time limit + automatic refresh in 5 scenarios, the success rate of resisting QR code reuse attacks is reduced from 5% in existing technologies to 0.0001%; ​​in offline mode, dual-modal compliance verification + device posture verification reduces the identity impersonation rate to 0.0001%, completely solving the core pain points of equipment theft and data tampering in the locksmith industry.

[0090] like Figure 6 The diagram shown is a functional block diagram of an identity binding and authentication system based on a 5G personal recorder provided in an embodiment of the present invention.

[0091] The identity binding authentication system 100 based on a 5G personal dashcam described in this invention can be installed in a processing device. Depending on the functions implemented, the identity binding authentication system 100 based on a 5G personal dashcam may include a cloud service platform computing module 101, an encrypted dynamic QR code generation module 102, a QR code information verification module 103, a verification request sending module 104, a binding credential construction module 105, an association binding module 106, an offline verification module 107, and a multi-verification retransmission module 108. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, stored in the memory of the electronic device.

[0092] In this embodiment, the functions of each module / unit are as follows: The cloud service platform computing module 101 is used to collect locksmith multimodal biometric information when a service order is received, and to calculate the multimodal biometric information to obtain the biometric dynamic anchor code and locksmith ID; The encrypted dynamic QR code generation module 102 is used to generate the device ID and key pair corresponding to the locksmith, perform double-layer encryption on the biometric dynamic anchor code, the device ID and the key pair and set an effective time to generate a double-layer encrypted dynamic QR code. The QR code information verification module 103 is used to verify the timeliness of the double-layer encrypted dynamic QR code and the legality of the device public key; The verification request sending module 104 is used to send a biometric verification request to the locksmith when the timeliness and device public key legality verification passes, and to collect the real-time biometric features returned by the biometric verification request. The binding credential construction module 105 is used to verify the identity of the real-time biometric features. When the identity verification is successful, a binding credential containing the locksmith ID, the device ID, and the biometric feature dynamic anchor code is constructed. The association binding module 106 is used to associate and bind the encrypted dynamic QR code with the locksmith according to the binding credential; The offline verification module 107 is used to switch to offline mode and periodically collect multimodal biometrics and operational behavior features when the detected signal strength is less than a preset signal threshold, and to perform local multimodal collaborative verification of the multimodal biometrics using an offline engine. The multi-verification and retransmission module 108 is used to add a four-dimensional encrypted identifier to the multimodal biometric features and the operational behavior features after local multimodal collaborative verification passes, and then encrypt and cache the encrypted cache data to obtain encrypted cache data. When the signal strength is greater than or equal to the threshold, the encrypted cache data is retransmitted through cloud-based multi-verification and retransmission. The specific execution steps in each of the above modules are the same as the corresponding execution steps in the forgetting learning method for training the local client model.

[0093] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0094] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0095] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identity binding and authentication based on a 5G personal dashcam, characterized in that, include: Upon receiving a service order, the locksmith's multimodal biometric information is collected, and the multimodal biometric information is calculated to obtain the biometric dynamic anchor code and the locksmith ID. Generate the device ID and key pair corresponding to the locksmith, perform double-layer encryption on the biometric dynamic anchor code, the device ID and the key pair and set the validity period, and generate a double-layer encrypted dynamic QR code; Verify the timeliness of the dual-layer encrypted dynamic QR code and the validity of the device public key; When the timeliness and device public key validity verification pass, a biometric feature verification request is sent to the locksmith, and the real-time biometric features returned by the biometric feature verification request are collected. The real-time biometric features are used to verify the identity. When the identity verification is successful, a binding credential containing the locksmith ID, the device ID, and the biometric dynamic anchor code is constructed. The encrypted dynamic QR code is associated and bound to the locksmith according to the binding credential; When the signal strength is detected to be less than the preset signal threshold, switch to offline mode and periodically collect multimodal biometrics and operational behavior features. Use the offline engine to perform local multimodal collaborative verification on the multimodal biometrics. When the local multimodal collaborative verification passes, the multimodal biometrics and the operational behavior features are encrypted and cached after being added with a four-dimensional encrypted identifier to obtain encrypted cache data. When the signal strength is greater than or equal to the threshold, the encrypted cache data is retransmitted after multiple verifications in the cloud.

2. The identity binding and authentication method based on a 5G personal dashcam as described in claim 1, characterized in that, The process of calculating the multimodal biometric information using a pre-defined cloud service platform to obtain the biometric dynamic anchor code and locksmith ID includes: Extract the multimodal biological features corresponding to the multimodal biological information respectively; The multimodal biological features are reduced to the same dimension to obtain a unified feature vector; The unified feature vectors are concatenated to obtain the biological feature vectors; A hash operation is performed on the biometric vector to obtain a dynamic anchor code for the biometric feature, and a locksmith ID is constructed based on the biometric vector.

3. The identity binding and authentication method based on a 5G personal dashcam as described in claim 1, characterized in that, The process of performing double-layer encryption on the biometric dynamic anchor code, the device ID, and the key pair, and setting an expiration time to generate a double-encrypted dynamic QR code includes: Extract the device public key from the password pair and generate a temporary session key based on the biometric dynamic anchor code; An encrypted QR code is obtained by encoding the device public key, the temporary session key, and the device ID. An expiration time is set for the encrypted QR code to obtain a double-layer encrypted dynamic QR code.

4. The identity binding and authentication method based on a 5G personal dashcam as described in claim 3, characterized in that, The process of encoding the device public key, the temporary session key, and the device ID to obtain an encrypted QR code includes: The device public key, the device ID, and the real-time timestamp are encrypted to obtain the first encrypted information; The first encrypted information is encrypted using the temporary session key to obtain the second encrypted information; The second encrypted information is encoded to obtain an encrypted QR code.

5. The identity binding and authentication method based on a 5G personal dashcam as described in claim 1, characterized in that, The step of sending a biometric feature verification request to the locksmith when the timeliness and device public key validity verification pass includes: Verify the timeliness of the QR code information and the validity of the device public key in the QR code information; When both the timeliness and the legality are passed, a biometric verification request is generated according to the preset modality verification requirements; The biometric verification request is sent to the locksmith's corresponding locksmith app.

6. The identity binding and authentication method based on a 5G personal dashcam as described in claim 1, wherein the step of verifying the identity of the real-time biometric features includes: Calculate the cosine similarity between the real-time biometrics and the multimodal biometrics in the pre-constructed biometric template library; The correction pass result for each mode is determined based on the cosine similarity. The identity of the real-time biometrics is verified based on the correction results.

7. The identity binding authentication method based on a 5G dashcam as described in claim 1, applied to an identity binding authentication device based on a 5G dashcam, the device comprising: Locksmith app, cloud service platform and 5G personal dashcam; The locksmith's app is used to collect the locksmith's multimodal biometric information when a service order is received. The cloud service platform is used to calculate the multimodal biological information to obtain the dynamic anchor code of the biometric feature and the locksmith ID; After initialization, the 5G personal dash maker is used to drive the security encryption module through the main control module of the 5G personal dash maker to generate the device ID and key pair corresponding to the 5G personal dash maker, and generate a double-layer encrypted dynamic QR code based on the biometric dynamic anchor code, the device ID and the key pair. The locksmith app extracts the double-encrypted dynamic QR code and uploads the QR code information to the cloud service platform. The cloud service platform is used to verify the timeliness of the QR code information and the legality of the device public key. When the timeliness and device public key validity verification pass, the cloud service platform is used to send a biometric verification request to the locksmith's mini-program to collect the real-time biometrics returned by the biometric verification request, and the cloud service platform is used to verify the identity of the real-time biometrics. When the identity verification is successful, the cloud service platform constructs a binding credential containing the locksmith ID, the device ID, and the biometric dynamic anchor code, and sends the binding credential to the tamper-proof storage unit of the 5G personal recorder; The signal strength of the 5G personal recorder is monitored. When the signal strength is detected to be less than a preset signal threshold, the 5G personal recorder is switched to offline mode and multimodal biometrics and operational behavior features are collected periodically. The offline engine is used to perform local multimodal collaborative verification of the multimodal biometrics. When the local multimodal collaborative verification passes, the multimodal biometrics and the operational behavior features are encrypted and cached after being added with a four-dimensional encrypted identifier to obtain encrypted cache data. When the signal strength is greater than or equal to the threshold, the 5G personal recorder initiates a retransmission request to the cloud service platform to perform cloud-based multi-verification retransmission of the encrypted cache data.

8. The identity binding and authentication device based on a 5G personal recorder as described in claim 7, characterized in that, The locksmith app includes a hardware integration module, a multimodal biometrics acquisition module, and a QR code scanning module.

9. The identity binding and authentication device based on a 5G personal recorder as described in claim 7, characterized in that, The 5G personal dashcam includes a main control module, a security encryption module, a device identification module, and a dynamic QR code generation module. The main control module is used to drive the security encryption chip in the security encryption module to generate a device ID and a key pair. The device identification module is used to generate the device ID based on the security encryption chip; The dynamic QR code generation module is used to generate a double-layer encrypted dynamic QR code based on the main control module and in conjunction with the security encryption chip.

10. An identity binding and authentication system based on a 5G personal dashcam, characterized in that, include: The cloud service platform computing module is used to collect locksmith multimodal biometric information when a service order is received, and to calculate the multimodal biometric information to obtain the biometric dynamic anchor code and locksmith ID; The encrypted dynamic QR code generation module is used to generate the device ID and key pair corresponding to the locksmith, perform double-layer encryption on the biometric dynamic anchor code, the device ID and the key pair and set the validity period to generate a double-layer encrypted dynamic QR code. The QR code information verification module is used to extract the double-layer encrypted dynamic QR code and verify the timeliness of the QR code information and the legality of the device public key; The verification request sending module is used to send a biometric verification request to the locksmith when the timeliness and device public key validity verification passes, and to collect the real-time biometric features returned by the biometric verification request. The binding credential construction module is used to verify the identity of the real-time biometric features. When the identity verification is successful, a binding credential containing the locksmith ID, the device ID, and the biometric feature dynamic anchor code is constructed. The association and binding module is used to associate and bind the encrypted dynamic QR code with the locksmith based on the binding credential; The offline verification module is used to switch to offline mode and periodically collect multimodal biometrics and operational behavior features when the detected signal strength is less than a preset signal threshold. The offline engine is used to perform local multimodal collaborative verification of the multimodal biometrics. The multi-verification and retransmission module is used to add a four-dimensional encrypted identifier to the multimodal biometrics and the operational behavior features and then encrypt and cache them to obtain encrypted cache data when the local multimodal collaborative verification passes, and to perform cloud multi-verification and retransmission on the encrypted cache data when the signal strength is greater than or equal to the threshold.

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