Decentralized anonymous recruitment method, anonymous recruitment system and storage medium

Abstract

The invention provides a decentralized anonymous recruitment method, an anonymous recruitment system and a storage medium, the method is applied to an intelligent contract of the anonymous recruitment system, the anonymous recruitment system further comprises a job hunting client and a recruitment client, and the method comprises the following steps: obtaining a position intention issued by the recruitment client; obtaining an anonymous qualification certificate corresponding to the position intention issued by the job application client, and verifying the anonymous qualification certificate; if the anonymous qualification certificate passes the verification, generating an anonymous request corresponding to the anonymous qualification certificate, and sending the anonymous request to the recruitment client, so that the recruitment client generates a recruitment intention according to the anonymous request; after the recruitment intention is received, performing position matching based on the anonymous qualification certificate and the position intention; and if the position matching is successful, obtaining identity data of the job seeker based on an authorization strategy, and sending the identity data to the recruitment client. According to the method, the problem of leakage of personal information on the resumes can be solved, resume information counterfeiting is avoided, time consumption for resume calling is reduced, the matching efficiency of mass resumes is improved, and the control right of job seekers for personal sensitive information of the job seekers is ensured.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to the field of blockchain technology, specifically to a decentralized anonymous recruitment method, anonymous recruitment system, and storage medium. Background Technology

[0002] In today's human resources recruitment market, user privacy leaks and rampant misinformation have become chronic problems. Traditional recruitment platforms act as core information intermediaries, and job seekers' data authorization is often a one-time, all-or-nothing model, lacking fine-grained control over specific fields. Information included in job postings may lead to gender and regional discrimination. Job matching cannot prove compliance with recruitment criteria without compromising privacy, and mass applications and a lack of credibility are also weaknesses that recruiters struggle to identify. Summary of the Invention

[0003] A decentralized anonymous recruitment method is applied to the smart contract of an anonymous recruitment system, which further includes a job seeker client and a recruitment client. The method includes:

[0004] Firstly, this invention provides a human resources security authentication and matching method based on zero-knowledge proofs and attribute-based encryption. This method is applied to a decentralized anonymous recruitment system and includes the following steps: Multi-dimensional credential aggregation proof step: The job seeker client obtains the job threshold conditions posted by the recruiter, and generates anonymous qualification proofs based on locally stored verifiable credentials using a hierarchical zero-knowledge proof algorithm; the anonymous qualification proof includes a cryptographic commitment to credential attributes, a threshold aggregation signature, and a zero-knowledge range proof for numerical conditions; Weighted bidirectional matching step: The smart contract receives the anonymous qualification proof submitted by the job seeker and the recruitment intention submitted by the recruiter, calculates a matching score using a bidirectional intention verification algorithm, combining the job seeker's reputation weight and the recruiter's intention's time decay factor, and triggers a bidirectional matching state when the matching score exceeds a preset threshold; Strategic selective decryption step: After triggering the bidirectional matching state, the system generates a strategy key based on an attribute-based encryption mechanism, and the job seeker client generates an authorization proof according to a preset authorization strategy and submits it to the smart contract; after the smart contract verifies the authorization, it releases the decryption permission, allowing the recruiter to decrypt only specific identity attribute data that conforms to the authorization strategy.

[0005] The aforementioned technical solutions fundamentally eliminate the pathways to privacy leaks, enabling self-verification of qualifications in a zero-trust environment. This satisfies both the recruitment needs of employers and protects the privacy of job seekers. It changes the traditional one-way application or search model, triggering a connection only when both parties reach a certain level of mutual interest. This not only avoids interference from invalid information but also ensures the fairness and immutability of the matching process through algorithmic automation, achieving atomic control of data access permissions. This on-demand decryption mechanism ensures that data control remains in the hands of the user, preventing excessive disclosure and abuse. The system automatically reduces the matching weight of outdated positions, achieving a merit-based ecosystem without manual intervention. This ensures job seekers are prioritized for the most active and urgent recruitment needs, significantly improving the job search experience and success rate. High-reputation users receive preferential traffic allocation, while fraudsters are automatically demoted by the algorithm. Thus, without the need for centralized reviewers, technology effectively drives out bad actors, maintaining the platform's integrity ecosystem. It also enables efficient one-to-many encrypted sharing. Job seekers only need to encrypt their data once, and subsequently authorize different recruiters by distributing different policy keys, without having to re-encrypt the file for each recruiter. This significantly reduces the client's computational load and key management complexity when facing massive concurrent recruitment requests.

[0006] Secondly, this invention provides a human resources security authentication and matching system based on zero-knowledge proofs and attribute-based encryption. The system includes: an entity interaction layer for running job seeker and recruiter clients, managing locally verifiable credentials, and generating anonymous qualification certificates; a smart contract proxy layer deployed on a blockchain, including a verification module, a matching module, and a decryption control module; the verification module verifies the validity of the anonymous qualification certificate; the matching module executes the two-way intention verification algorithm, calculates a matching score, and determines whether a two-way matching state is triggered; the decryption control module verifies authorization certificates and distributes policy keys based on attribute-based encryption; and a data storage layer for storing encrypted identity attribute data ciphertext, which can only be decrypted by a specific party after obtaining the policy key.

[0007] Thirdly, the present invention provides a virtual device. This device operates within a computer device and includes: a proof generation module configured to acquire job threshold conditions and generate anonymous qualification certificates containing zero-knowledge scope proofs based on verifiable credentials; a weighted matching module configured to receive anonymous qualification certificates and recruitment intentions, calculate a matching score by combining reputation weights and time decay factors, and determine whether a matching state is triggered; and a policy decryption module configured to, upon successful matching, generate a policy key and decrypt specific identity data based on an attribute-based encryption mechanism and a user authorization policy.

[0008] Fourthly, the present invention provides an electronic device. The electronic device includes: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions stored in the memory to implement the steps of the method described in the first aspect. The electronic device may be a server, a cloud computing node, or a mobile terminal or personal computer used by a user.

[0009] Fifthly, the present invention provides a computer-readable storage medium. The computer-readable storage medium stores a computer program or instructions, which, when executed by a processor, implement the steps of the method described in the first aspect. The storage medium includes, but is not limited to, various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0010] In a sixth aspect, the present invention provides a computer program product. The computer program product includes a computer program or instructions that, when executed by a processor, implement the steps of the method described in the first aspect.

[0011] Seventhly, the present invention relates to a user interface. The present invention also provides a graphical user interface running on a mobile terminal or computer terminal for human-computer interaction: on the job seeker's side interface, it includes an area for displaying job thresholds, controls for selecting local credentials for authorization, and interactive elements for displaying the progress of anonymous qualification certificate generation and matching success prompts; on the recruiter's side interface, it includes an area for posting jobs and setting threshold weights, a list area for receiving anonymous matching requests, a display area for viewing decrypted identity data after authorization, and the ability to add post-interview evaluations of the job seeker's performance and reputation. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the overall architecture of an anonymous recruitment matching system provided in an embodiment of this application; Figure 2 This is a schematic diagram of a smart contract process that supports matching job seekers and employers, provided in an embodiment of this application. Figure 3 This is a schematic diagram of a two-way intention matching and strategy authorization process provided in an embodiment of this application; Figure 4 This is a flowchart illustrating a job search client provided in an embodiment of this application; Figure 5 This is a flowchart illustrating a recruitment client provided in an embodiment of this application. Detailed Implementation

[0013] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " indicates "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0014] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0015] Figure 1 This is a schematic diagram of the overall architecture of an anonymous recruitment matching system provided by an embodiment of the present invention. The architecture is built on a blockchain and decentralized storage. The system includes three main participants and one core technical component:

[0016] Participants:

[0017] Issuer 110: An authoritative third-party institution, such as a university, former employer, or professional certification body, is responsible for digitally signing data such as degrees, work experience, and technical certificates to generate verifiable credentials 125.

[0018] Holder 120: i.e. job seeker. Job seeker uses DID wallet 121 to create and manage their own decentralized identity proof 122, which is encrypted and stored on IPFS 140. It holds immutable, verifiable, and verifiable resume credentials issued by different issuers. DID wallet 121 contains ZKP generator 123, which is used to generate anonymous qualification proofs 124 locally.

[0019] Verifier 130: This refers to the recruiter. The recruiter uses the recruiter client 131 to post job openings, filter anonymous proofs, and verify VCs after obtaining authorization. The recruiter records the interviews with job seekers and the fulfillment of the agreement, and stores these records on the blockchain.

[0020] Core technology components:

[0021] Smart Contract 150: Receives job requirements 151 from recruitment clients, stores the VC thresholds posted by recruiters, receives job applications from job seekers, and performs two-way matching 152. It handles anonymous matching and status management. After a successful match between a job seeker 120 and a recruiter 130, it sends a confirmation of the desired job application to the recruiter. It then requests authorization for identity data based on the job seeker's set strategy via the DIDComm 160 point-to-point encrypted communication protocol, and securely transmits the decrypted VC data.

[0022] based on Figure 1 The system architecture diagram shown below will be combined with... Figure 2-5 The methods provided in the embodiments of this application will be described.

[0023] Please see Figure 2 This application provides a schematic diagram of a smart contract process that supports matching job seekers and employers, as illustrated in an embodiment of the present application. Figure 2 As shown, the method in this application embodiment may include the following steps.

[0024] S101, Smart Contract Interface retrieves specific job intention data posted by recruitment clients:

[0025] Receive a job's hard requirements, or VC thresholds, defined by a recruiter through their client, for example: {"Education Requirement":"Must hold a Master's degree in VC from University A","Experience Requirement":"Must hold a VC with 5 years of development experience"}, and post it on Job Requirements Contract 151.

[0026] S102: Receive anonymous qualification certificates submitted by job seekers for the position and call the verification algorithm to verify their validity.

[0027] For anonymous qualification verification, a layered zero-knowledge proof generation algorithm is used, which utilizes the VC set VC={vc1, vc2,..., vc...} held locally by the job seeker. n} and the job threshold T={t1,t2,...,t m The client does not upload VCs directly, but instead uploads them for each VC. i Extract verifiable attribute A i Generate attribute commitment C i =Commit(A i ,r i ), where r i To act as a random blinding factor, ensure that commitments generated for the same attribute differ across different job applications, preventing user tracking through commitment values. Construct threshold aggregate signatures. S agg =AggregateSign({sign(sk j C j)|j∈qualified_indices})

[0028] Prove that the job seeker possesses valid credentials signed by an authoritative issuer, and that these credentials belong to a qualified set of indices. Generate a zero-knowledge scope proof (ZKP). knowledge This proves that the holder does indeed possess the ability to generate S. agg The corresponding private key proves that I am the legitimate holder of these credentials, for example, generating ZKP tokens based on numerical thresholds such as salary and years of service. range =GenerateRangeProof(A i ,t bounds (), prove that 5≤Years≤10, without revealing whether it is 6 years or 9 years.

[0029] Finally, it is integrated into anonymous qualification proof {C1...C n ,S agg ZKP range ZKP knowledge Submit to the blockchain smart contract.

[0030] S103. After the contract verification is successful, a corresponding anonymous request is automatically generated and pushed to the recruitment client, triggering the recruiter's intention confirmation mechanism.

[0031] The contract only needs to verify the aggregate signature S agg and zero-knowledge proof ZKP range The validity of the authentication can be verified to confirm the validity of the entire anonymous qualification certificate, generate the corresponding anonymous request and send it to the recruiter, and wait for the recruiter to submit their opinion on which anonymous requests they are interested in.

[0032] S104, awaiting confirmation of recruitment intention data from the recruitment client.

[0033] S105, Invoke the matching logic to perform job matching calculation based on the anonymous qualification certificate and the job intention.

[0034] S106. If the calculation result determines that the job is a successful match, the smart contract retrieves the job seeker's identity data based on the authorization strategy and transmits the data to the recruitment client.

[0035] Please see Figure 3 This is a flowchart illustrating a decentralized anonymous recruitment method provided in an embodiment of this application. Figure 3 As shown, the method in this application embodiment may include the following steps S1051-S1053 and S1061-S1064.

[0036] S1051, the system retrieves the reputation weight, historical performance records, time decay factor corresponding to the job seeker's intention posting time, and specific intention weighted data from the database or on-chain storage.

[0037] Perform initialization and validation, load a matching queue Q, and calculate the job seeker reputation weight: w cred =CalculateReputation(p.prover_address), this reputation value is based on historical performance records such as interview attendance rate and data authorization authenticity. For the intention i submitted by the recruiter, calculate the time decay factor: decay=e -λ·(current_time-i.timestamp))

[0038] The longer a recruiter's interest has been around, the lower its weight, thus encouraging recruiters to remain active.

[0039] S1052, input the above parameters into the two-way intention verification algorithm to calculate the comprehensive matching score.

[0040] Calculate the final intention weight: i.weight=i.base_weight×decay×employer_reputation

[0041] S1053, compare the calculated matching score with the system's preset threshold. If the score reaches or exceeds the threshold, the match is considered successful, and the subsequent authorization process is triggered.

[0042] The weighted matching decision system traverses the queue and determines whether the matching condition is greater than a preset threshold. pw cred ×i.weight>threshold

[0043] The Matched state is triggered only when the weighted product exceeds the system-set threshold. This ensures that both parties proceed to the next step only when they have good credit and genuine interest, thus resolving issues of malicious order manipulation and interference from outdated intentions.

[0044] S1061, trigger the attribute-based encryption mechanism to generate paired policy keys based on the current authorization policy, specifically including a recruitment key for decryption and a job application key for encryption.

[0045] The authorization policy has a default value in the contract, and users can also customize an authorization policy when submitting an application, and generate a policy key based on the policy.

[0046] PK policy =GeneratePolicyKey(Policy)

[0047] S1062, the job search key along with the job matching information is sent to the job search client, instructing it to encrypt the sensitive data.

[0048] Send the job search key to the job search client, requesting verification and the current Matched status.

[0049] Fine-grained decryption: RecordAccessLog(A) records the data access behavior for this instance. verifier The match_id and requested_attributes are recorded on an immutable blockchain log, forming a complete regulatory traceability chain.

[0050] S1063, Receive the authorization certificate returned by the job application client, and parse and extract the ciphertext of the identity data encrypted with the job application key.

[0051] The validity of the proof returned by the job application client is verified, and a temporary decryption key temp_key is generated that is only valid for this session.

[0052] Using attribute-based encryption, recruiters can only decrypt attribute fields marked as true in the Policy.

[0053] S1064, The recruitment key and the encrypted identity data are packaged and sent to the recruitment client, giving it decryption privileges.

[0054] Please see Figure 4 This application provides a schematic diagram of a decentralized anonymous recruitment method, applicable to a job seeker client. For example... Figure 4 As shown, the method in this application embodiment may include the following steps.

[0055] S201, the client initiates a verification request to the school, employment, or certificate authority node associated with the job seeker, obtains at least one digital identity certificate, and securely stores it in the job seeker's local identity wallet.

[0056] A job seeker's resume contains two important sections. The first section includes sensitive personal information such as name, photo, contact information, and address, which recruiters can use to contact the applicant privately. The second section details the applicant's technical skills and experience, allowing them to match the applicant with the recruiter's needs and demonstrate the strength of the recruiter's interest. The second section is verified by certifications issued by relevant authoritative institutions. Additionally, the resume includes the applicant's historical job-matching performance, contributing to a credit score.

[0057] S202 responds to the job seeker's selected job preferences and retrieves corresponding attribute data from the identity wallet. A random blinding factor is introduced, and combined with the identity data and job preferences, an anonymous qualification certificate containing attribute commitments and threshold aggregation signatures is generated.

[0058] Attribute commitments ensure that commitments generated for the same attribute differ across different job applications, preventing user tracking through commitment values ​​and reducing verification overhead through aggregated signatures. Job seekers submit proof to a smart contract indicating their interest in the position, but remain completely anonymous within the contract.

[0059] S203, send the anonymous qualification certificate to the smart contract for matching, and wait for feedback.

[0060] S204, Receive a job matching success notification message from the system, which includes the job search key and matching details.

[0061] S205, based on the matching details, extract the matching identity data corresponding to the strategy from the local wallet, encrypt the matching identity data using the received job application key, and generate an authorization certificate.

[0062] S206, the generated authorization certificate is sent to the smart contract to complete the controlled delivery of identity data.

[0063] S103, if the anonymous qualification certificate is verified, an anonymous request corresponding to the anonymous qualification certificate is generated and the anonymous request is sent to the recruitment client so that the recruitment client generates a recruitment intention based on the anonymous request;

[0064] Please see Figure 5 This application provides a schematic diagram of a decentralized anonymous recruitment method, applied to a recruitment client. For example... Figure 5 As shown, the method in this application embodiment may include the following steps.

[0065] S301: The client listens for and receives anonymous requests pushed by smart contracts.

[0066] The client sends a job posting to the smart contract and waits for the smart contract to send an anonymous request.

[0067] Before posting a job opening, the recruiting platform needs to verify the qualifications and then add hard requirements such as age, education, and skills based on the job requirements.

[0068] S302 awaits a list of anonymous job seekers who meet its requirements, sent to it by a smart contract.

[0069] S303 generates a confirmed recruitment intention based on the anonymous request and sends it back to the smart contract to trigger matching calculations.

[0070] When a smart contract sends an anonymous job application list, recruiters can currently only see anonymous candidate IDs, but the system automatically verifies that these IDs 100% meet the thresholds defined in the job requirements. Recruiters can then filter based on the job requirements, such as those who meet the most requirements or those with the strongest technical skills, adding their level of satisfaction with the request before sending it to the smart contract for final matching.

[0071] S304, waiting for matching to complete, receiving encrypted identity data sent by the smart contract and the recruitment key that matches the data.

[0072] Receive data sent by the smart contract, verify the job seeker's data integrity and identity using the recruitment key that matches the data.

[0073] S305: Obtain the decrypted plaintext identity data and initiate subsequent recruitment processes based on this data.

[0074] Interview invitations are submitted based on the information of the job seekers obtained. The interview evaluation can be added to assess the job seeker's trustworthiness in accepting the invitation and the validity of the data.

[0075] It should be understood that the apparatus provided in this application embodiment is used to execute the above-described decentralized anonymous recruitment method, and therefore can achieve the same effect as the above-described implementation method.

[0076] The processing module may be a processor or a controller that can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc., and the storage module may be a memory.

[0077] In addition, the device provided in this application embodiment may specifically be a chip, component or module. The chip may include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute a decentralized anonymous recruitment method provided in the above embodiment.

[0078] This application also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the aforementioned method steps to implement the decentralized anonymous recruitment method provided in the above embodiments.

[0079] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned steps to implement a decentralized anonymous recruitment method provided in the above embodiment.

[0080] In this embodiment, the device, computer-readable storage medium, computer program product, or chip are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0081] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0082] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0083] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A decentralized, anonymous recruitment method, characterized in that, A smart contract applied to an anonymous recruitment system, the anonymous recruitment system also including a job seeker client and a recruitment client, the method comprising: Obtain the job intentions posted by the recruitment client; Obtain and verify the anonymous qualification certificate corresponding to the job intention posted by the job search client; If the anonymous qualification certificate is verified, an anonymous request corresponding to the anonymous qualification certificate is generated and sent to the recruitment client so that the recruitment client can generate a recruitment intention based on the anonymous request; Upon receiving the recruitment intention, job matching is performed based on the anonymous qualification certificate and the job intention; If a job is successfully matched, the job seeker's identity data is obtained based on the authorization policy, and the identity data is sent to the recruitment client.

2. The method according to claim 1, wherein obtaining the job seeker's identity data based on an authorization strategy and sending the identity data to the recruitment client comprises: The authorization policy is generated based on the attribute-based encryption mechanism, and the policy key includes a recruitment key and a job application key. The job search key and job matching information are sent to the job search client to enable the job search client to generate an authorization certificate, which includes the job seeker's encrypted identity data, which is encrypted using the job search key. Receive the authorization certificate sent by the job application client, and obtain the encrypted identity data in the authorization certificate; The recruitment key and the encrypted identity data are sent to the recruitment client so that the recruitment client can obtain the job seeker's identity data based on the recruitment key.

3. The method according to claim 1, characterized in that, The job matching based on the anonymous qualification certificate and the job intention includes: Obtain the reputation weight corresponding to the job seeker, the time decay factor corresponding to the job intention, and the intention weighted data, and calculate the matching score based on the two-way intention verification algorithm; If the matching score reaches a preset threshold, the job match is considered successful.

4. A decentralized, anonymous recruitment method, characterized in that, A job seeker client for an anonymous recruitment system, the anonymous recruitment system further including a smart contract and a recruitment client, the method comprising: Apply for proof of identity from the job seeker's school, employer, and certification body, wherein the proof of identity includes at least one; The identity verification is stored in the job seeker's corresponding identity wallet; Receive job application intentions from job seekers and obtain any identity attribute from all the aforementioned identity documents; Anonymous qualification certificates are generated based on all the aforementioned identity data, job intentions, and random blinding factors. These anonymous qualification certificates are used by the smart contract for job matching. If a successful job match is received, the job seeker's identity data is sent to the smart contract, which then sends the identity data to the recruitment client.

5. The method according to claim 4, characterized in that, The prompt information includes a job search key and job matching information. Sending the job seeker's identity data to the smart contract includes: Obtain the matching identity data corresponding to the job matching information; The matching identity data is encrypted using the job search key to obtain authorization proof; Send the authorization certificate to the smart contract.

6. The method according to claim 4, characterized in that, The anonymous qualification proof includes attribute commitment, threshold aggregate signature, and...

7. A decentralized, anonymous recruitment method, characterized in that, A recruitment client for an anonymous recruitment system, the anonymous recruitment system also including a smart contract and a job seeker client, the method comprising: Receive anonymous requests; The system obtains the recruitment intention generated by the recruiter in response to the anonymous request, and sends the recruitment intention to the smart contract, so that the smart contract sends the job seeker identity data corresponding to the recruitment intention. Receive identity data sent by the smart contract.

8. The method according to claim 7, characterized in that, The identity data is encrypted using the job search key corresponding to the job search client, and the receipt of the identity data sent by the smart contract includes: Receive the identity data sent by the smart contract and the recruitment key that matches the job search key; The identity data is decrypted based on the recruitment key to obtain decrypted identity data, which is used by the recruiter to enter the recruitment process.

9. An anonymous recruitment system, characterized in that, The anonymous recruitment system includes: Memory, used to store executable program code; A processor is configured to call and run the executable program code from the memory, causing the anonymous recruitment system to perform the method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program code that, when executed, implements the method as described in any one of claims 1 to 8.

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