A third-party-free publicly verifiable high-privacy group data contribution metric method and system

Abstract

The application provides a third-party-free publicly verifiable high-privacy group data contribution measurement method and system, which comprises the following steps: S1, generating public system parameters based on security parameters; S2, generating a public-private key pair based on the system parameters by each data owner in the group; S3, generating an integrity audit label with anonymity by the data owner; S4, completing the public verification of data integrity by interacting with the cloud server for auditing by the verifier; S5, quantifying the data contribution value of the data owner and generating a verifiable contribution proof; S6, verifying the validity of the contribution proof and the contribution value submitted by each data owner by the cloud server, completing the validity determination of the group transaction and realizing the benefit distribution according to the contribution value. The application can realize efficient and verifiable data contribution quantification in a user-controlled manner without a trusted third party, and prevent the data buyer from inferring sensitive information from unsold data.

Description

Technical Field

[0001] This invention belongs to the field of data element security technology, and in particular relates to a method and system for measuring the contribution of high-privacy group data that is publicly verifiable without a third party. Background Technology

[0002] With the rapid development of the large-scale model training data procurement and multi-party collaborative data trading industry, data delivery and ownership transfer via cloud platforms to reduce bandwidth costs and avoid copyright disputes has become a mainstream model. In this model, multiple data owners outsource the collaboratively generated data to cloud servers, and data buyers conduct data transactions through these cloud servers. To ensure fair transactions, the data contribution of each data owner must be quantified in the group transaction to allocate benefits.

[0003] Traditional Provable Data Possession (PDP) enables effective auditing of stored data and is an effective solution for proving the integrity of outsourced data. However, it is limited to single-owner scenarios and cannot be directly used for multi-party collaborative group transactions. As the first multi-ownership data auditing solution, Knox uses homomorphic group signatures to achieve identity concealment in multi-user scenarios, solving the problem that traditional PDP cannot adapt to multi-party collaboration. However, this solution does not support public auditing and incurs high communication overhead. Traditional multi-owner auditing solutions only support data integrity verification and do not introduce a data value weighting mechanism, making it impossible to differentiate and quantify the value of different data types, thus failing to adapt to data transaction scenarios with differentiated pricing. To address the contribution quantification problem in group transactions, existing technologies propose Provable Data Controller (PDC) schemes, with TA-PDC being a typical example of the first group transaction contribution quantification scheme. This scheme achieves contribution quantification in multi-owner group scenarios by introducing Linkable Ring Signatures and Inner Product Argument (IPA). However, existing contribution quantification schemes still have the following problems:

[0004] 1) High Trust Costs: Existing solutions (such as TA-PDC) achieve anonymous yet traceable contribution proofs through linkable ring signatures. However, this approach often relies on a trusted third party. This increases the trust costs and overhead of the system. More importantly, it is difficult to find a completely neutral and trustworthy third-party institution in real-world transaction scenarios. If the trusted third party is attacked or colludes, it will lead to the leakage of the data owner's privacy, making it unsuitable for real-world production environments. 2) Insufficient Privacy Protection: Existing contribution quantification solutions typically publicly bind data contribution values ​​to specific data types or tags, and data tags often have public linkability. This means that once a data buyer purchases a portion of the data, they can infer the type distribution of the remaining data by analyzing the tag link relationships of the purchased data, thereby leaking information about data that the data owner has not yet sold. 3) Low Computational and Communication Efficiency: Existing technical solutions (such as TA-PDC) typically use IPA, whose computational complexity is linearly related to the number of data types. As the number of collaborating users and data types increases, the time required to generate and verify contribution proofs will increase significantly, leading to excessively high communication costs and severely hindering its practical application in large-scale group data transactions. Summary of the Invention

[0005] This invention addresses the shortcomings of traditional data contribution proof schemes in existing group data trading scenarios, such as reliance on trusted third parties, privacy risks associated with tags, and excessive computational overhead for contribution quantification. It proposes a publicly verifiable, high-privacy group data contribution measurement method and system without a third party. By designing a novel ring signature-based weighted tag structure and improving the weight aggregation mechanism, it achieves efficient and verifiable data contribution quantification through user control, even without a trusted third party. Simultaneously, a random factor is introduced to remove the public linkage of weighted tags, preventing data buyers from inferring sensitive information from unsold data.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] A publicly verifiable, high-privacy group data contribution measurement method without third parties, the method comprising the following steps:

[0008] S1. Generate public system parameters based on security parameters;

[0009] S2. Each data owner in the group generates a public-private key pair based on system parameters: The group private key is distributed to the legitimate data owners in the group through a one-time registration process, and the corresponding group public key is set based on the system parameters and the group private key; Each data owner sets a personal private key based on the group private key, and calculates the personal public key corresponding to the personal private key based on the system parameters; The personal public keys of all data owners and the group public key constitute a public key set;

[0010] S3. Divide the original file to be uploaded into multiple data blocks, and divide each data block into sub-blocks with the same number as the data owner; the data owner constructs an audit tag for each data block based on system parameters, file identifier, data block value weight, personal private key, personal public key, group private key, and public key set; upload all data blocks and corresponding audit tags to the cloud server;

[0011] S4. The verifier randomly selects a portion of the data block indices and coefficients and sends an audit challenge request to the cloud server. After receiving the challenge request, the cloud server retrieves all the challenged data blocks and their corresponding tags, calculates the storage proof, and returns it to the verifier. The verifier receives the storage proof and verifies the data integrity. After successful verification, the verifier executes the subsequent steps.

[0012] S5. The data owner quantifies their own data contribution value and generates a verifiable contribution certificate, and sends the contribution value, contribution certificate and current transaction message to the cloud server;

[0013] S6. The cloud server verifies the validity of the contribution certificates and contribution values ​​submitted by each data owner, completes the determination of the validity of group transactions, and realizes the allocation of rights and interests based on the contribution values.

[0014] Preferably, the generation of public system parameters based on security parameters is as follows:

[0015] 1) Based on security parameters Determine prime numbers The length of the position;

[0016] 2) Choose three prime numbers of order. Multiplication cyclic group , and And define a bilinear mapping Three independent generators are randomly selected. , , ,in , Define two hash functions and ,in , ; For prime numbers Defined finite field;

[0017] 3) Determine and Value weight vector corresponding to each data type ;

[0018] 4) Set system parameters .

[0019] Preferably, each data owner within the group generates a public-private key pair based on system parameters, as follows:

[0020] 1) Distribute group private keys to legitimate data owners through a one-time registration process. And set the corresponding group public key as ;

[0021] 2) Data owners from limited domains Randomly select private key components Set their personal private key And calculate the corresponding personal public key. ,in Index for data owner;

[0022] 3) Set the public key set as .

[0023] Preferably, the data owner constructs an audit tag for each data block based on system parameters, file identifier, data block value weight, personal private key, personal public key, group private key, and public key set, as follows:

[0024] 1) Data owner piece The tag is ;in, All are data blocks The label component is specifically calculated as follows:

[0025] 2) , ;in, Represents data block Corresponding value weight, For file identifier, For data block indexing, For data owners The private key component;

[0026] 3) Randomly select two elements ,calculate Generate label components , ;in, , Representing data blocks Data belongs to the data owner and data owners sub-blocks, For data owners Personal public key,

[0027] , ,in For data owners Private key component

[0028] Preferably, the calculation of the storage proof is as follows:

[0029] The cloud server received the challenge request. Then, retrieve all challenged data blocks. and their corresponding tags ,

[0030] Computational storage proof ,in:

[0031] , , ,

[0032] , , ,

[0033] in, From data block index Randomly selected and containing A subset of elements, each coefficient from The sample is randomly selected evenly from the middle.

[0034] Preferably, the verification of data integrity is specifically as follows:

[0035] Validator receives stored proof Then, calculate Data integrity is verified by checking whether equation (1) holds true:

[0036] (1)

[0037] The verifier outputs a corresponding identifier based on the equation verification result: if the equation is true, output a data integrity identifier; if the equation is false, output a data integrity verification failure identifier.

[0038] Preferably, the verifier is the data owner or a third-party auditor.

[0039] Preferably, the data owner quantifies their own data contribution value and generates a verifiable contribution certificate, then sends the contribution value, contribution certificate, and current transaction message to the cloud server, specifically including the following steps:

[0040] S5.1, Data Owner Receive aggregated tags from the cloud server Using hash functions calculate and and aggregate them into ,in Indicates the data owner The set of indexes for the data blocks it owns;

[0041] S5.2 Select random numbers ,calculate ; and use transaction messages Calculate contribution proof ):

[0042]

[0043]

[0044]

[0045] ;

[0046] in Used to uniquely identify the current transaction;

[0047] S5.3, Based on Value Weight Vector Calculate data owner Contribution value ;

[0048] S5.4, Contribution value, contribution proof, and transaction message. It is sent to the cloud server for subsequent contribution verification and transaction confirmation.

[0049] Preferably, the cloud server verifies the validity of the contribution proofs and contribution values ​​submitted by each data owner, completes the determination of the validity of group transactions, and allocates rights based on the contribution values, specifically including the following steps:

[0050] S6.1 Cloud servers utilize hash functions calculate , And for each data owner j, calculate its corresponding aggregation label. and ,in , , This represents the set of indices representing the data blocks owned by data owner j;

[0051] S6.2, Use contribution proof and the amount of data contributed. calculate And check whether equation (2) holds true:

[0052] (2)

[0053] If any data owner's verification fails, the cloud server returns 0, deeming the transaction invalid; if all users' contribution proofs pass verification, the total contribution value of all data owners is compared with the purchase amount of the data buyer. Whether they are consistent, that is, whether equation (3) holds true:

[0054] (3)

[0055] in, This represents the contribution value of each data owner;

[0056] If the equation is true, the cloud server outputs 1, confirming the group transaction is valid and distributing it according to the contribution values ​​of each data owner. Distribute the profits; otherwise, output 0, indicating the transaction is invalid.

[0057] A publicly verifiable, high-privacy group data contribution measurement system without a third party, wherein the system is implemented using any of the above methods, including data owners, cloud servers, data buyers, and third-party auditors.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. Eliminating the need for trusted third parties: Existing technical solutions (such as TA-PDC) typically require the introduction of trusted third parties to achieve contribution quantification, which not only increases system complexity but also poses privacy risks. This invention utilizes ring signatures with user-controllable linkability and designs a new weighted label structure, enabling data owners to generate contribution proofs independently without relying on trusted third parties.

[0060] 2. Enhanced Privacy Protection: Existing technologies (such as TA-PDC) allow tags to be publicly linked, meaning that once a data buyer purchases a portion of the data, they can infer the type of unsold data through linked tags, thus compromising the data owner's privacy. This invention introduces a random factor to break the public linkability between tags, ensuring that even after a data buyer obtains the data in a group transaction, they cannot infer the data owner's data type from the purchased data, thereby achieving a higher level of privacy protection.

[0061] 3. Improve computational and communication efficiency: Existing technical solutions (such as TA-PDC) typically employ IPA, which contributes to quantization complexity and data type... Positive correlation proves that the generation and verification time increases too rapidly with the amount of data, which is detrimental to large-scale applications. This invention abandons IPA and optimizes the weight aggregation mechanism so that the quantization cost is only related to the number of user-defined data blocks. , and global data types It is unrelated to communication costs and effectively reduces computing speed. Attached Figure Description

[0062] Figure 1 This is a schematic diagram of the system model of the present invention;

[0063] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0064] The following is in conjunction with the appendix Figure 1-2 The technical solution of the present invention will be described in detail below.

[0065] This invention aims to address the problem in existing data trading markets where collaboratively generated data from groups struggles to achieve efficient and fair contribution measurement and verification while ensuring the privacy of all parties. Specifically, existing technologies often rely on trusted third parties for contribution calculation, which can easily leak data information that the data owner has not sold. This invention proposes a highly privacy-oriented group data contribution measurement method and system that is publicly verifiable without a third party. By introducing a user-controllable and linkable ring signature mechanism and an optimized weight aggregation algorithm, it enables data owners to autonomously quantify their contributions and allows cloud servers to publicly verify the fairness of transactions.

[0066] For the convenience of describing this invention application, some related technologies will be introduced below.

[0067] Bilinear pairing:

[0068] Bilinear pairing is a method defined on two numbers of large prime order. Multiplication cyclic group and Mapping relationship between ,in Also of the rank The multiplication cyclic group. Let... and They are and For any generator, bilinear pairings must satisfy the following three key properties: 1) Computability: for any... , It can perform efficient calculations. ;2) Bilinear: for any , as well as ,satisfy 3) Non-degeneracy: For generators , ,have , of which 1 is The unit element in the text.

[0069] Homomorphic authenticator:

[0070] Homomorphic authenticaters are the foundation for building public auditing mechanisms. When instantiated as a homomorphic authenticated signature scheme, in addition to being unforgeable, the system must also satisfy the following two key properties: 1) Block-free verifiability: given a data block , Corresponding authenticator , and random coefficients and aggregated data blocks The validator can do so without retrieving the original data block. and Verify aggregated data blocks in the case of 1) Integrity; 2) Non-extensibility: Given a data block , Corresponding authenticator , and random coefficients For aggregated data blocks Without a private key In this situation, the adversary cannot computationally overcome solely through linear combinations. and Derivation Valid signature .

[0071] Ring signatures with user-controlled linkability:

[0072] Traditional ring signatures allow users to sign on behalf of any chosen set of public keys while concealing the identity of the actual signer. However, complete anonymity is undesirable when proof of ownership of a particular signature is required. While chainable ring signatures have been introduced, existing schemes typically rely on public chainability or require the involvement of a trusted third party. Therefore, ring signatures with user-controlled chainability have been proposed, allowing signers to generate proof of ownership for a particular signature in a user-controlled manner, without relying on a trusted third party.

[0073] Figure 1 This is a schematic diagram of the system model of the present invention. The system model of the present invention is provided by the data owner ( ), cloud server ( ), data buyers ( ) and third-party auditors ( )composition.

[0074] 1) Data owner ( ): The data owner is a set of... Users collaboratively generate multi-ownership data and outsource it for storage and trading. In data transactions, each data owner autonomously quantifies their contribution to the traded data. However, they may falsify proof of contribution to gain greater benefits.

[0075] 2) Cloud server ( A cloud server is an entity with abundant storage and computing resources that provides storage and collaboration services to data owners. It addresses auditing challenges, facilitates data transactions for data buyers, and distributes benefits based on quantified contributions. However, when outsourced data is corrupted, it may falsify integrity certificates to pass audits.

[0076] 3) Data buyers ( Data buyers are entities that post data requests on cloud servers, purchase the requested data, and pay the corresponding fees. However, they may infer the type distribution of unsold data from the purchased data.

[0077] 4) Third-party auditors ( The third-party auditor is a semi-trusted entity, established through communication with... The system interacts to verify the integrity and ownership of outsourced data. However, it may attempt to infer the identity of the corresponding data owner based on metadata generated during the audit process.

[0078] Specifically, the technical solution adopted in this invention is as follows:

[0079] This invention can be divided into four stages: initialization, tag generation, public auditing, and transaction and contribution quantification. The process flow is as follows: Figure 2 As shown.

[0080] The specific algorithm of this invention is as follows:

[0081] 1) System parameter generation algorithm The system executes this algorithm to generate the public parameters required by the system, while the algorithm uses security parameters. The system parameters are output with the number of data types d as input. .

[0082] 2) Key generation algorithm The data owner executes the algorithm with system parameters. As input, generate a set of private keys. and the corresponding set of public keys.

[0083] 3) Tag generation algorithm The data owner executes this algorithm for data blocks. Generate data tags Based on system parameters File identifier Value The i-th data block Owner's private key and public key set As a parameter, output the corresponding block marker. .

[0084] 4) Auditing Algorithm The audit is jointly performed by the cloud server and a third-party auditor; the specific audit steps are: 1) The third-party auditor first generates a challenge set Q and sends it to CS; 2) Given... The cloud server calculates an integrity certificate P and returns it to the third-party auditor. 3) The third-party auditor uses the public key set of all data owners. Verify P. Output 1 if verification is successful, otherwise output 0.

[0085] 5) Contribution Quantification Algorithm This algorithm is executed by the data owner during the transaction process, identifying the block index set in which their contribution is determined. Then, set the system parameters File identifier and the corresponding block tags Public key set Transaction information As input, and output contribution value and corresponding proof of contribution .

[0086] 6) Contribution Verification Algorithm The algorithm is executed by a cloud server, given system parameters. Block tags Public key set and transaction information Cloud servers through The indexed data verifies the claimed contribution value for each data owner. and corresponding proof of contribution The correctness of the verification is evaluated. If all verifications pass, output 1; otherwise, output 0.

[0087] In this invention, the main tasks of each stage are as follows:

[0088] The initialization phase primarily involves the data owner and aims to establish a secure foundation for the entire system and generate keys. The system is based on security parameters. Execute with the number of data types d Algorithm for generating system parameters Subsequently, the data owners in the group independently execute the key generation algorithm. Each entity generates its own public and private keys based on publicly available parameters. Specifically:

[0089] 1) The system first selects a prime number as its order. Multiplication cyclic group , and Construct a bilinear mapping Randomly select independent generators , ;

[0090] 2) The system defines two hash functions. and ,in , ;

[0091] 3) System determination and Value weight vector corresponding to each data type Set system parameters .

[0092] 4) Each data owner in the group generates a public-private key pair based on system parameters, and distributes the group private key to the legitimate data owner through a one-time registration process. The group public key is set to ;

[0093] 5) Each data owner has access to a limited domain. Randomly selected from Calculate the private key and the corresponding public key ;

[0094] 6) Collect all the private keys of all data owners to form a private key set. By combining the public keys of each user, a public key set is obtained. .

[0095] The tag generation phase primarily involves the data owner, who executes the tag generation algorithm during this phase. Using its private key and system parameters for each data block Generate authentication labels And upload it to the cloud server, specifically:

[0096] 1) The data owner uploads the required files. Divided into A file block of the same size, represented as and will Further divided into File blocks of the same size in , Same as the number of users in the group;

[0097] 2) The data owner first calculates , Next, the label components are calculated. ;in Representation block Corresponding value weight;

[0098] 3) The data owner randomly selects two elements. ,calculate And generate label components ,in The public key for the data owner u, and the tag component. ;

[0099] 4) The data owner calculates the label components: , ,in This is another private key component for the data owner u;

[0100] 5) The data owner constructs the data block. Full certification label and all data blocks and its corresponding tag set The data is uploaded to a cloud server, which receives and stores the data blocks and tags for remote storage and subsequent auditing and transaction verification.

[0101] The public auditing phase primarily involves the data owner, a third-party auditor, and the cloud server. In this phase, the data owner collaborates with the cloud server to generate multi-ownership data and outsources it for storage and transactions. To ensure data integrity and ownership of the outsourced data, the data owner entrusts the audit to a third-party auditor. The cloud server and the third-party auditor jointly execute the audit algorithms. The third-party auditor generates an audit challenge set and sends it to the cloud server. The cloud server receives the challenge set and generates an integrity certificate P. The third-party auditor verifies the integrity certificate P to ensure that the stored data has not been tampered with, and reports the final audit results to the data owner. Specifically:

[0102] 1) The data owner commissions a third-party auditor to conduct a data integrity and ownership audit;

[0103] 2) The third-party auditor randomly selects a subset of data block indices and coefficients to generate an audit challenge set. And launched an audit challenge against the cloud server, among which From data block index Randomly selected and containing A subset of elements, each coefficient from Uniformly and randomly selected from the middle;

[0104] 3) The cloud server receives the challenge set. Then, retrieve all challenged data blocks. and their corresponding tags ,calculate:

[0105] , , ,

[0106] 4) The cloud server receives the challenge set. Then, retrieve all challenged data blocks. and their corresponding tags ,calculate:

[0107] , , ,

[0108] 5) Cloud server generates integrity certificate And return it to the third-party auditor;

[0109] 6) Third-party auditor receives storage proof Then, calculate Data integrity is verified by checking whether equation (1) holds true:

[0110] (1)

[0111] If the equation is true, the third-party auditor outputs 1 to confirm data integrity; otherwise, they output 0 to determine that data integrity has been compromised.

[0112] The Transaction and Contribution Quantification phase primarily involves data buyers, data owners, and cloud servers. Data buyers first publish their data requests on the cloud server, purchase the required data, and pay the corresponding fees. Simultaneously, each data owner participating in the transaction needs to execute a contribution quantification algorithm on the data blocks they contribute. The system generates contribution proofs for multi-ownership data and submits them to the cloud server. The cloud server then receives the contribution proofs and contribution values. Execute contribution verification algorithm Verify the validity of the contribution certificates and contribution values ​​submitted by each data owner, and complete the data transfer and transaction confirmation accordingly. If the verification is successful, the cloud server will process the data based on each data owner's contribution value. To distribute the profits, specifically:

[0113] 1) Data buyers first publish data procurement requirements on the cloud server, then initiate a data purchase request, and wait to receive the data after paying the fee. It is worth noting that after purchasing data, data buyers can know the type and distribution of the purchased data, but cannot infer the type and distribution of unsold data from it.

[0114] 2) Data owner Receive aggregated tags from the cloud server Using hash functions calculate and and aggregate them into ,in Indicates the data owner Data blocks owned The set of indices;

[0115] 3) Data owner Select an element ,calculate and use transaction messages Calculate contribution proof components and ,in Used to uniquely identify the current transaction and ensure the timeliness of the proof;

[0116] 4) Data owner Calculate the other two contribution proof components. , ;

[0117] 5) Data owners based on value weight vector Calculate your contribution value And construct contribution proof );

[0118] 6) Data Owner Contribution value, contribution proof, and transaction messages The data is sent to the cloud server for subsequent contribution verification and transaction confirmation. It is important to note that the cloud server can only verify the contribution value. This does not expose the fine-grained contribution details of each data owner;

[0119] 7) Cloud servers utilize hash functions calculate , And for each data owner j, calculate its corresponding aggregation label. and ,in , ;

[0120] 8) Proof of contribution to cloud server usage and the amount of data contributed. calculate And check whether equation (2) holds true:

[0121] (2)

[0122] If any data owner's verification fails, the cloud server returns 0, deeming the transaction invalid; if all users' contribution proofs pass verification, the total contribution value of all data owners is compared with the purchase amount of the data buyer. Whether they are consistent, that is, whether equation (3) holds true:

[0123] (3)

[0124] If the equation is true, the cloud server outputs 1, confirming the group transaction is valid and distributing it according to the contribution values ​​of each data owner. Distribute the profits; otherwise, output 0, indicating the transaction is invalid.

[0125] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Those skilled in the art can modify or make equivalent substitutions to the technical solutions of the present invention without departing from the spirit and scope of the present invention. The protection scope of the present invention should be determined by the claims.

Claims

1. A publicly verifiable, high-privacy group data contribution measurement method without a third party, characterized in that, The method includes the following steps: S1. Generate public system parameters based on security parameters; S2. Each data owner in the group generates a public-private key pair based on system parameters: The group private key is distributed to the legitimate data owners in the group through a one-time registration process, and the corresponding group public key is set based on the system parameters and the group private key; Each data owner sets a personal private key based on the group private key, and calculates the personal public key corresponding to the personal private key based on the system parameters; The personal public keys of all data owners and the group public key constitute a public key set; S3. Divide the original file to be uploaded into multiple data blocks, and divide each data block into sub-blocks with the same number as the data owner; the data owner constructs an audit tag for each data block based on system parameters, file identifier, data block value weight, personal private key, personal public key, group private key, and public key set; upload all data blocks and corresponding audit tags to the cloud server; S4. The verifier randomly selects a portion of the data block indices and coefficients and sends an audit challenge request to the cloud server. After receiving the challenge request, the cloud server retrieves all the challenged data blocks and their corresponding tags, calculates the storage proof, and returns it to the verifier. The verifier receives the storage proof and verifies the data integrity. After successful verification, the verifier executes the subsequent steps. S5. The data owner quantifies their own data contribution value and generates a verifiable contribution certificate, and sends the contribution value, contribution certificate and current transaction message to the cloud server; S6. The cloud server verifies the validity of the contribution certificates and contribution values ​​submitted by each data owner, completes the determination of the validity of group transactions, and realizes the allocation of rights and interests based on the contribution values.

2. The method for measuring the contribution of high-privacy group data that is publicly verifiable without a third party, as described in claim 1, is characterized in that... The process of generating public system parameters based on security parameters is as follows: Based on security parameters Determine prime numbers The length of the position; Choose three prime numbers. Multiplication cyclic group , and And define a bilinear mapping Three independent generators are randomly selected. , , ,in , Define two hash functions and ,in , ; For prime numbers Defined finite field; Determine and Value weight vector corresponding to each data type ; Configure system parameters .

3. The method for measuring the contribution of high-privacy group data that is publicly verifiable without a third party, as described in claim 2, is characterized in that... Each data owner within the group generates a public-private key pair based on system parameters, as follows: Group private keys are distributed to legitimate data owners through a one-time registration process. And set the corresponding group public key as ; Data owners from finite domains Randomly select private key components Set their personal private key And calculate the corresponding personal public key. ,in Index for data owner; Set the public key set as follows .

4. The method for measuring the contribution of high-privacy group data that is publicly verifiable without a third party, as described in claim 3, is characterized in that... The data owner constructs an audit tag for each data block based on system parameters, file identifier, data block value weight, personal private key, personal public key, group private key, and public key set, as follows: Data owner Construct data blocks The tag is ;in, All are data blocks The label component is specifically calculated as follows: , , ;in, Represents data block Corresponding value weight, For file identifier, For data block indexing, For data owners The private key component; Randomly select two elements ,calculate Generate label components , ;in, , Representing data blocks Data belongs to the data owner and data owners sub-blocks, For data owners Personal public key, , ,in For data owners The private key component.

5. The method for measuring the contribution of high-privacy group data that is publicly verifiable without a third party, as described in claim 4, is characterized in that... The calculation of the storage proof is as follows: The cloud server received the challenge request. Then, retrieve all challenged data blocks. and their corresponding tags , Computational storage proof ,in: ， ， ， ， ， ， in, From data block index Randomly selected and containing A subset of elements, each coefficient from The sample is randomly selected evenly from the middle.

6. The method for measuring the contribution of high-privacy group data that is publicly verifiable without a third party, as described in claim 5, is characterized in that... The verification of data integrity is as follows: Validator receives stored proof Then, calculate Data integrity is verified by checking whether equation (1) holds true: （1） The verifier outputs a corresponding identifier based on the equation verification result: if the equation is true, output a data integrity identifier; if the equation is false, output a data integrity verification failure identifier.

7. The method for measuring the contribution of high-privacy group data that is publicly verifiable without a third party, as described in claim 1, is characterized in that... The verifier is either the data owner or a third-party auditor.

8. A publicly verifiable, high-privacy group data contribution measurement method without a third party, as described in claim 6, is characterized in that... The data owner quantifies their own data contribution value and generates a verifiable contribution certificate, then sends the contribution value, contribution certificate, and current transaction message to the cloud server, specifically including the following steps: S5.1, Data Owner Receive aggregated tags from the cloud server Using hash functions calculate and and aggregate them into ,in Indicates the data owner The set of indexes for the data blocks it owns; S5.2 Select random numbers ,calculate ; and use transaction messages Calculate contribution proof ): ； in Used to uniquely identify the current transaction; S5.3, Based on Value Weight Vector Calculate data owner Contribution value ; S5.4, Contribution value, contribution proof, and transaction message. It is sent to the cloud server for subsequent contribution verification and transaction confirmation.

9. A publicly verifiable, high-privacy group data contribution measurement method without a third party, as described in claim 8, is characterized in that... The cloud server verifies the validity of the contribution proofs and contribution values ​​submitted by each data owner, completes the determination of the validity of group transactions, and allocates rights based on the contribution values. Specifically, this includes the following steps: S6.1 Cloud servers utilize hash functions calculate , And for each data owner j, calculate its corresponding aggregation label. and ,in , , This represents the set of indices representing the data blocks owned by data owner j; S6.2, Use contribution proof and the amount of data contributed. calculate And check whether equation (2) holds true: （2） If any data owner's verification fails, the cloud server returns 0, deeming the transaction invalid; if all users' contribution proofs pass verification, the total contribution value of all data owners is compared with the purchase amount of the data buyer. Whether they are consistent, that is, whether equation (3) holds true: （3） in, This represents the contribution value of each data owner; If the equation is true, the cloud server outputs 1, confirming the group transaction is valid and distributing it according to the contribution values ​​of each data owner. Distribute the profits; otherwise, output 0, indicating the transaction is invalid.

10. A publicly verifiable, high-privacy group data contribution measurement system without a third party, characterized in that, The system is implemented using the method described in any one of claims 1-9, including a data owner, a cloud server, a data purchaser, and a third-party auditor.

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