A method and system for verifying the identity of a retired military personnel and matching policies

Abstract

This application discloses a method and system for linking veteran identity verification and policy matching, belonging to the field of data processing and government service technology. The method includes: obtaining basic veteran identity information; performing multi-factor identity verification based on blockchain and zero-knowledge proof technology to generate a unique digital identity identifier; accurately matching applicable preferential policies using a knowledge graph policy database based on the digital identity identifier; pushing the matching results to the user terminal, and automatically filling in the application form through a government service platform to achieve one-click policy application. This application also discloses a corresponding linkage system. By constructing a trusted identity verification mechanism and a precise policy matching engine, this application realizes a closed-loop business process from identity verification to policy application, effectively improving the security of identity verification, the accuracy of policy matching, and the efficiency of government processing, solving the problems of difficult implementation of veteran policies and cumbersome procedures in existing technologies.

Description

Technical Field

[0001] This application relates to the fields of data processing and government services technology, specifically a method and system for linking veteran identity verification with policy matching. Background Technology

[0002] In recent years, with the state's high emphasis on the construction of a service and support system for veterans, government departments at all levels have successively introduced a series of preferential policies covering employment and entrepreneurship, preferential treatment, education and training, legal aid, and other aspects. The effective implementation of these policies is a crucial link in demonstrating the state's care and protecting the legitimate rights and interests of veterans.

[0003] Currently, veterans affairs management departments and related government platforms generally use traditional information management systems when processing policy applications. Veterans need to first submit identity verification materials offline or online for verification, then consult various policy documents to determine their eligibility, and finally submit applications to different departments. In this process, some advanced regions have introduced government big data platforms, enabling electronic verification of some identity information.

[0004] However, existing technologies still have the following shortcomings: First, identity verification methods are limited, relying heavily on passwords or static document information, which lacks security and results in severe data silos between systems, making it difficult to form a unified and reliable digital identity. Second, policy matching depends on veterans' own understanding and selection of policies; due to the numerous policy items and complex applicable conditions, it is easy for them to miss out on benefits, receive incorrect benefits, or be unaware of the policies. Finally, the process from identity verification to policy application is fragmented, requiring veterans to repeatedly fill in information on multiple platforms, making the process cumbersome, inefficient, and affecting the timeliness and accuracy of policy implementation. Summary of the Invention

[0005] This application provides a method and system for linking veteran identity verification and policy matching. By constructing a blockchain-based trusted identity verification mechanism and a knowledge graph-based accurate policy matching engine, and linking the two with the government service platform, a closed loop of identity verification, policy matching, and one-click application can be realized. This can effectively solve the problems of insufficient identity verification security, inaccurate policy matching, and cumbersome procedures in the background technology.

[0006] To achieve the above objectives, this application provides the following technical solution: a method and system for linking veteran identity verification and policy matching. This method first utilizes blockchain and zero-knowledge proof technology to perform multi-factor identity verification on veterans and generate unique digital identity identifiers, ensuring the authenticity and privacy of their identities. Subsequently, through a knowledge graph policy database, applicable preferential policies are automatically and accurately matched based on the veteran's personal tags. Finally, it links with the government service platform to provide veterans with a one-click service for policy applications. This system, through modular design, integrates information collection, identity verification, policy matching, service delivery, and linked processing, realizing a shift from people searching for policies to policies finding people, significantly improving service efficiency and user experience.

[0007] Furthermore, the biometric information includes at least one of fingerprint features, facial features, and voiceprint features. The multi-factor authentication specifically employs zero-knowledge proof technology to compare the biometric information with on-chain evidence without disclosing the original biometric information, thereby verifying the authenticity of the identity. This technical solution ensures the accuracy of verification while maximizing the protection of veterans' biometric privacy and preventing the leakage of sensitive information during transmission and comparison.

[0008] Furthermore, after generating a unique digital identity in step S2, this identity is bound to the veteran's digital wallet address for targeted disbursement and traceability of subsequent preferential treatment funds. This technical solution provides a technological foundation for the automated and transparent disbursement of subsequent pensions, subsidies, and other funds, achieving auditability of fund flows.

[0009] Furthermore, the policy database is constructed using knowledge graph technology, with policy clauses, applicable conditions, handling departments, and time windows as nodes and logical relationships as edges, to achieve semantic-based precise policy matching. This technical solution can understand the implicit conditions in complex policy texts, achieving deep and multi-dimensional policy matching, significantly improving the recall and accuracy of the matching.

[0010] Furthermore, the policy matching report generated in step S4 includes a matching score, policy basis, a list of required materials, and an estimated processing time. It also supports filtering and sorting by policy type, applicable region, and validity period. This technical solution provides veterans with clear and quantifiable decision-making references, enhancing the transparency and user-friendliness of the service.

[0011] Furthermore, the integrated processing module includes a form mapping unit, used to map the identity information corresponding to the digital identity to the application form fields of the target government service, and a status tracking unit, used to record the submission status, approval progress, and final result of the policy application, and to feed back to the service push module. This technical solution realizes the automatic flow and status synchronization of cross-system data, truly bridging the last mile of service delivery.

[0012] Compared with the prior art, the beneficial effects of this application are: 1. This application introduces blockchain technology and zero-knowledge proof to build a highly secure, highly reliable, and tamper-proof verification mechanism for veterans' identities, effectively solving the problems of easy data forgery and difficulty in cross-system mutual trust in traditional identity verification, while protecting personal privacy.

[0013] 2. This application utilizes knowledge graphs to construct a policy database and combines it with personal tags of veterans for semantic matching, realizing a shift from passive querying to proactive push notifications. This solves the problems of inaccurate policy matching and asymmetric policy information, ensuring that veterans fully enjoy the benefits they are entitled to.

[0014] 3. This application deeply integrates identity verification, policy matching, and government service procedures, realizing a closed-loop service of one-time verification, accurate matching, and one-click application, which greatly simplifies the process and improves the efficiency of the service and support system for veterans and the satisfaction of the public. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the overall structure of the system in this application.

[0016] In the diagram: 1. Information collection module; 2. Identity verification module; 3. Policy matching engine; 4. Service push module; 5. Joint processing module; 6. Supervision and audit module; 7. Encrypted storage unit; 8. Feature comparison unit; 9. Tagging processing unit; 10. Semantic matching unit; 11. Form mapping unit; 12. Status tracking unit. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] In the description of this application, any descriptions of orientation, such as up, down, front, back, left, right, etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are merely for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. When a feature is referred to as being set, fixed, or connected to another feature, it can be directly set, fixed, or connected to the other feature, or it can be indirectly set, fixed, or connected to the other feature.

[0019] Please see Figure 1 This application provides the following technical solution: a system for linking veteran identity verification and policy matching, comprising an information collection module 1, an identity verification module 2, a policy matching engine 3, a service push module 4, and a linked processing module 5. The identity verification module 2 specifically includes an encrypted storage unit 7 and a feature comparison unit 8. The policy matching engine 3 specifically includes a tagging processing unit 9 and a semantic matching unit 10. The linked processing module 5 specifically includes a form mapping unit 11 and a status tracking unit 12.

[0020] The information collection module 1 is used to acquire the basic identity information of veterans, including name, ID card number, veteran's certificate number, and biometric information. The identity verification module 2 is connected to the information collection module 1 and performs multi-factor identity verification based on blockchain technology and zero-knowledge proof mechanism to generate a digital identity identifier. Specifically, the encrypted storage unit 7 is deployed on the blockchain node to pre-store the hash value of the veteran's identity information; the feature comparison unit 8 extracts the biometric vector locally and compares it with the hash value on the chain. After successful verification, the digital identity identifier is generated.

[0021] The policy matching engine 3 is connected to the identity verification module 2 and has a built-in knowledge graph policy database. The tagging processing unit 9 converts the attribute information of veterans (such as years of service, merit awards, disability level, employment status, etc.) into structured tags; the semantic matching unit 10 calculates the semantic similarity between the structured tags and policy nodes in the knowledge graph, and outputs a list of policies with a matching degree exceeding a preset threshold.

[0022] The service push module 4 is connected to the policy matching engine 3 and is used to push the matching results (including matching score, policy basis, list of required materials and estimated processing time) and the policy application portal to the user terminal. The linkage processing module 5 is connected to the service push module 4 and the external government service platform. The form mapping unit 11 maps the identity information corresponding to the digital identity to the application form field of the target government service to realize one-click submission. The status tracking unit 12 records the submission status, approval progress and final result of the policy application and feeds it back to the service push module 4.

[0023] In addition, the system also includes a regulatory audit module 6, which is connected to the identity verification module 2, the policy matching engine 3, and the linkage processing module 5. It records all operation logs and generates audit reports for higher-level management departments to assess the policy implementation rate.

[0024] In use: Veterans first input their identity information and undergo facial recognition via a mobile device or self-service terminal. Information collection module 1 sends the collected data to identity verification module 2. Identity verification module 2 performs a zero-knowledge comparison between the facial feature vector collected on-site and the on-chain evidence. Upon successful verification, a temporary and unique digital identity is generated. This identity is then sent to policy matching engine 3. Based on the veteran's service record tags associated with this identity, policy matching engine 3 quickly retrieves and matches all local preferential policies applicable to the veteran in the knowledge graph. The matching results are presented to the user via message notifications and reports by service push module 4. After selecting a policy of interest, the veteran clicks "One-Click Application." The linked processing module 5 automatically fills in the identity information corresponding to the digital identity into the corresponding government service electronic form and submits it to the back-end approval system. Throughout the process, status tracking unit 12 updates the processing progress in real time to ensure a closed-loop service.

[0025] It is worth noting that the core chip of the identity verification module 2 disclosed in this embodiment is a high-performance security chip, specifically the Z32H330TC, which supports national cryptographic algorithms, to ensure the security of encryption operations. The camera in the information collection module 1 can be a 1080P high-definition module supporting liveness detection, with a recommended frame rate of at least 30fps. The policy matching engine 3 runs on a server equipped with an NVIDIA Tesla T4 graphics processor to accelerate semantic computation of the knowledge graph. When the linkage processing module 5 connects to local government service platforms, it uses a RESTful API interface, with data exchange format in standard JSON, and adheres to the OAuth 2.0 authentication protocol authorized by each platform. The control switch group (or microcontroller) controls the collaborative work of each module using methods commonly found in existing technologies, namely, triggering and responding through predefined communication protocols and timing logic.

[0026] Although embodiments of this application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for linking veteran identity verification with policy matching, characterized in that, include: Step S1: Obtain the basic identity information of the veteran, including name, ID card number, veteran's certificate number and biometric information; Step S2: Based on blockchain technology, compare the basic identity information with the encrypted evidence information in the database of the veterans affairs management department to complete multi-factor identity verification and generate a unique digital identity identifier; Step S3: After the identity verification is passed, extract at least one preferential policy from the policy database that matches the veteran's years of service, meritorious service, disability level, and employment status according to the digital identity identifier; Step S4: Push the matched preferential policy and the corresponding application portal and processing procedure to the veteran through a visual interface and generate a policy matching report; Step S5: Receive the veteran's policy application instruction, link with the government service platform, automatically fill in the identity information in the application form, and complete the one-click application for the policy.

2. The method for linking veteran identity verification and policy matching according to claim 1, characterized in that: The biometric information includes at least one of fingerprint features, facial features, and voiceprint features. The multi-factor identity verification specifically involves using zero-knowledge proof technology to compare the features with on-chain evidence without disclosing the original biometric information in order to verify the authenticity of the identity.

3. The method for linking veteran identity verification and policy matching according to claim 1, characterized in that: After generating a unique digital identity in step S2, the identity will be bound to the veteran's digital wallet address for targeted distribution and tracking of subsequent preferential treatment funds.

4. The method for linking veteran identity verification and policy matching according to claim 1, characterized in that: The policy database is constructed using knowledge graph technology, with policy clauses, applicable conditions, handling departments and time windows as nodes and logical relationships as edges, to achieve semantic-based accurate policy matching.

5. The method for linking veteran identity verification and policy matching according to claim 1, characterized in that: The policy matching report generated in step S4 includes a matching score, policy basis, a list of required materials, and an estimated processing time. It also supports filtering and sorting by policy type, applicable region, and validity period.

6. A system for linking veteran identity verification and policy matching, used to execute the method described in any one of claims 1 to 5, characterized in that: include: The information collection module is used to obtain basic identity information of veterans; An identity verification module, connected to the information collection module, performs multi-factor identity verification and generates a digital identity identifier based on blockchain technology and zero-knowledge proof mechanism; a policy matching engine, connected to the identity verification module, has a built-in knowledge graph policy database for policy matching based on the digital identity identifier. The service push module is connected to the policy matching engine and is used to push the matching results and policy application entry to the user terminal. The linkage processing module is connected to the service push module and the external government service platform to receive application instructions and automatically complete the form data filling and submission.

7. The veteran identity verification and policy matching linkage system according to claim 6, characterized in that: The identity verification module includes: an encrypted storage unit deployed on a blockchain node for storing the hash value of the veteran's identity information; and a feature comparison unit for extracting biometric vectors locally and comparing them with the hash value on the chain, generating the digital identity identifier after successful verification.

8. The veteran identity verification and policy matching linkage system according to claim 6, characterized in that: The policy matching engine includes: a tagging processing unit for converting the attribute information of veterans into structured tags; and a semantic matching unit for calculating the semantic similarity between the structured tags and policy nodes in the knowledge graph, and outputting a list of policies with a matching degree exceeding a preset threshold.

9. The veteran identity verification and policy matching linkage system according to claim 6, characterized in that: The linked processing module includes: a form mapping unit, used to map the identity information corresponding to the digital identity to the application form fields of the target government service; and a status tracking unit, used to record the submission status, approval progress and final result of the policy application, and to feed it back to the service push module.

10. A system for linking veteran identity verification and policy matching according to claim 6, characterized in that: It also includes a regulatory audit module, which is connected to the identity verification module, policy matching engine and linkage processing module, to record all operation logs and generate audit reports for higher-level management departments to assess the policy implementation rate.

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