CN116527322A - Combined credit investigation method and device based on block chain and privacy calculation - Google Patents

Combined credit investigation method and device based on block chain and privacy calculation Download PDF

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CN116527322A
CN116527322A CN202310347195.6A CN202310347195A CN116527322A CN 116527322 A CN116527322 A CN 116527322A CN 202310347195 A CN202310347195 A CN 202310347195A CN 116527322 A CN116527322 A CN 116527322A
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public
random number
ciphertext
private key
honest
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李佳
刘晓蕾
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Telephase Technology Development Beijing Co ltd
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Telephase Technology Development Beijing Co ltd
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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    • H04L9/3218—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using proof of knowledge, e.g. Fiat-Shamir, GQ, Schnorr, ornon-interactive zero-knowledge proofs
    • H04L9/3221—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using proof of knowledge, e.g. Fiat-Shamir, GQ, Schnorr, ornon-interactive zero-knowledge proofs interactive zero-knowledge proofs
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    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
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    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees
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Abstract

The invention relates to the technical field of artificial intelligence, and discloses a combined credit investigation method and device based on block chain and privacy calculation, wherein the method comprises the following steps: generating a primary public-private key of user information in a target mechanism; performing validity verification on the primary public and private key by using a preset public key correctness proving algorithm to obtain a trust public and private key of the primary public and private key; generating a trusted random number of the user information according to the trusted public and private key, and carrying out signature processing on the trusted random number to obtain a digital signature of the trusted random number; carrying out distributed node sharing processing on the trusted random number according to the digital signature to obtain a shared ciphertext of the trusted random number; and acquiring a credit investigation task of the user to be investigated, and generating user credit investigation of the user to be investigated according to the shared ciphertext and the credit investigation task. The invention also provides a combined credit investigation device based on the block chain and the privacy calculation. The invention can improve the query efficiency when the target user is subjected to credit investigation.

Description

Combined credit investigation method and device based on block chain and privacy calculation
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a combined credit investigation method and device based on blockchain and privacy calculation.
Background
In the current digital economic age, the financial industry is facing an important strategic opportunity for digital transformation. As two-drive carriage for developing digital finance, industrial digital finance is developed, the prospect is wide, and the consumption ecology system of the consumption digital finance based on the Internet economy is deeply integrated into the daily life of residents. However, from the practical standpoint, there are still some problems to be solved in consuming digital finances, in which the multi-headed lending and excessive credit problems due to the asymmetry of information not only increase the credit risks faced by each financial institution, but also present certain challenges to the stability of the financial system in China due to the conductivity and complexity of the financial risks.
Today, for each financial institution, the loan amount of the borrower at the institution belongs to trade secrets, and the borrower is generally unwilling to share the data information with competitors, so that credit information cannot be shared, and the credit information of a target user is difficult to obtain; even though the financial institutions are willing to share the data information due to business expansion, due to the lack of a safe and reliable data information sharing means for protecting business secrets, the realization of financial data sharing under the increasingly strict supervision atmosphere of privacy data protection still has an obstacle, so that more time is required for screening false information and real information, the acquisition time of credit investigation information is increased, and therefore, how to improve the inquiry efficiency when credit investigation is carried out on target users becomes a problem to be solved urgently.
Disclosure of Invention
The invention provides a combined credit investigation method and device based on block chain and privacy calculation, which mainly aim to solve the problem of low inquiry efficiency when credit investigation is carried out on a target user.
In order to achieve the above purpose, the present invention provides a combined credit investigation method based on blockchain and privacy calculation, comprising:
acquiring user information in a target mechanism, and generating a primary public and private key of the user information;
performing validity verification on the primary public and private key by using a preset public key correctness proving algorithm to obtain a trust public and private key of the primary public and private key, wherein the preset public key correctness proving algorithm is as follows:
PkProof i ＝PkProofGen(x i ,y i )
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, pkProofGen is a public key correctness proving function, i is the information identifier corresponding to the user information, and PkProof i Is the public key correctness proving parameter of the ith user information;
generating a trusted random number of the user information according to the trusted public and private key, and carrying out signature processing on the trusted random number according to the trusted random number and a target mechanism corresponding to the user information to obtain a digital signature of the trusted random number;
carrying out distributed node sharing processing on the trusted random number according to the digital signature to obtain a shared ciphertext of the trusted random number;
and acquiring a credit inquiry task of the user to be inquired, and generating a user credit of the user to be inquired according to the shared ciphertext and the credit inquiry task.
Optionally, the generating the primary public-private key of the user information includes:
generating a primary public and private key of the user information by using a preset public and private key generation algorithm, wherein the preset public and private key generation algorithm is as follows:
(x i ,y i )＝PSGen()
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, PSGen () is a random password generation function, and i is the information identification corresponding to the user information.
Optionally, the verifying the validity of the primary public-private key by using a preset public-key correctness proving algorithm to obtain a trusted public-private key of the primary public-private key includes:
generating a public key correctness proving parameter of the primary public and private key by using a preset public key correctness proving algorithm, and performing public processing on the public key correctness proving parameter and the public key in the primary public and private key to obtain public information of the primary public and private key;
and carrying out information correctness verification on the public information, and determining that the primary public and private key corresponding to the public information passing the information correctness verification is a trust public and private key.
Optionally, the generating the trusted random number of the user information according to the trust public-private key includes:
the method comprises the steps of obtaining a target mechanism of the trust public and private key, performing honest verification on the target mechanism according to a secret sub-share of the target mechanism to obtain a honest mechanism of the target mechanism, and determining the honest sub-share of the target mechanism according to the honest mechanism and the secret sub-share;
homomorphism addition processing is carried out on the honest sub-share, so that homomorphism ciphertext of the honest sub-share is obtained;
and performing share reconstruction on the homomorphic ciphertext to obtain a reconstructed ciphertext of the homomorphic ciphertext, and generating a trusted random number of the user information by using the reconstructed ciphertext.
Optionally, the performing honest verification on the target mechanism according to the secret sub-share of the target mechanism to obtain a honest mechanism of the target mechanism includes:
the target mechanism generates a secret random number locally, and generates a secret sub-share of the target mechanism by using a preset polynomial function and the secret random number, wherein the preset polynomial function is as follows:
wherein a is j (x) Is the secret sub-share corresponding to the decryption private key of the jth target mechanism, t is the total number of random numbers of the secret random numbers, k is the random number identifier of the secret random numbers, a jk Is the j-th target machineA secret random number of a kth secret random number, x is a decryption private key of a jth target mechanism, mod (x) is a mod function, N is a product of randomly selecting two large prime numbers, and j is a mechanism identification of the target mechanism;
determining a promise value of the target institution according to the secret sub-share, and carrying out effective promise verification on the target institution by utilizing the promise value to obtain a promise institution of the target institution;
and obtaining the sub-share ciphertext of the promise mechanism, carrying out ciphertext correctness verification on the sub-share ciphertext by using a preset ciphertext correctness verification algorithm, and determining that the target mechanism corresponding to the sub-share ciphertext passing the ciphertext correctness verification is an honest mechanism.
Optionally, the homomorphic adding the honest sub-share to obtain homomorphic ciphertext of the honest sub-share includes:
generating an encryption total of the honest sub-share according to the honest sub-share and the honest ciphertext corresponding to the honest sub-share, wherein the encryption total is as follows:
wherein e pj Is the encrypted sum of the honest sub-shares, p is the honest sub-share identity of the honest sub-shares, enc is the encryption algorithm, enc (α j (p),y j ,r pj ) By means of public key y j For the honest seed share alpha j (p) encrypting, j is the organization identity of the target organization, n is the total number of honest sub-shares of the honest sub-shares, α j (p) is the jth target mechanism's jth honest share, y j Is the public key of the jth target institution, r pj Is a random integer selected during encryption;
and carrying out decryption processing on the encryption total to obtain the decryption total of the encryption total, and determining the decryption total as homomorphic ciphertext of the honest sub-share.
Optionally, the performing share reconstruction on the homomorphic ciphertext to obtain a reconstructed ciphertext of the homomorphic ciphertext includes:
and calculating the homomorphic ciphertext and the retrograde interpolation by using a preset interpolation algorithm to obtain a reconstructed ciphertext of the homomorphic ciphertext, wherein the preset interpolation algorithm is as follows:
wherein A is the reconstructed ciphertext of the homomorphic ciphertext, m is the total homomorphic ciphertext of the homomorphic ciphertext, g is the homomorphic ciphertext identification of the homomorphic ciphertext,is the g homomorphic ciphertext, B m Is the mth interpolation point, B g Is the g-th interpolation point.
Optionally, the signing process is performed on the trusted random number according to the target mechanism corresponding to the trusted random number and the user information to obtain a digital signature of the trusted random number, which includes:
generating index information of the trusted random number according to a target mechanism corresponding to the user information;
and carrying out ring signature processing on the trusted random number according to the index information to obtain a digital signature of the trusted random number.
Optionally, the performing distributed node sharing processing on the trusted random number according to the digital signature to obtain a shared ciphertext of the trusted random number includes:
establishing a hash tree of the trusted random number according to the digital signature, and determining an on-chain information table of the trusted random number according to the hash tree;
establishing an under-chain storage layer of the trusted random number, and collecting node data of the trusted random number in the on-chain information table and the under-chain storage layer;
and performing node distribution on the node data according to a preset node frame to obtain the shared ciphertext of the trusted random number.
In order to solve the above problems, the present invention further provides a joint credit investigation device based on blockchain and privacy calculation, the device comprising:
the primary public and private key module is used for acquiring user information in a target mechanism and generating a primary public and private key of the user information;
the trust public-private key module is used for verifying the validity of the primary public-private key by using a preset public-key correctness proving algorithm to obtain a trust public-private key of the primary public-private key, wherein the preset public-key correctness proving algorithm is as follows:
PkProof i ＝PkProofGen(x i ,y i )
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, pkProofGen is a public key correctness proving function, i is the information identifier corresponding to the user information, and PkProof i Is the public key correctness proving parameter of the ith user information;
the trusted random number module is used for generating a trusted random number of the user information according to the trusted public and private key, and carrying out signature processing on the trusted random number according to the trusted random number and a target mechanism corresponding to the user information to obtain a digital signature of the trusted random number;
the shared ciphertext module is used for carrying out distributed node sharing processing on the trusted random number according to the digital signature to obtain a shared ciphertext of the trusted random number;
and the credit inquiry module is used for acquiring a credit inquiry task of the user to be inquired and generating a user credit of the user to be inquired according to the shared ciphertext and the credit inquiry task.
The embodiment of the invention eliminates malicious participants in a blockchain by generating the primary public and private keys of user information in the target mechanism and verifying the validity of the primary public and private keys, ensures that the target mechanism in the blockchain is an honest participant, shares information input by a hidden participant by using a threshold secret, ensures the verifiability of interaction information through zero knowledge proof and homomorphic promise, generates a trusted random number of the honest participant, ensures the privacy and safety of data on the blockchain, generates a digital signature of the trusted random number, improves the queriability of credit and reduces the inquiring time, so the invention provides the combined credit investigation method and device based on the blockchain and privacy calculation, which can solve the problem of lower inquiring efficiency when the target user is subjected to credit investigation.
Drawings
FIG. 1 is a flow chart of a combined credit investigation method based on blockchain and privacy calculation according to an embodiment of the present invention;
FIG. 2 is a flow chart of generating a trusted random number according to an embodiment of the present invention;
FIG. 3 is a flow chart of sharing trusted random numbers according to an embodiment of the present invention;
FIG. 4 is a functional block diagram of a combined credit investigation apparatus based on blockchain and privacy calculations according to an embodiment of the present invention;
the achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a joint credit investigation method based on blockchain and privacy calculation. The execution subject of the combined credit investigation method based on the blockchain and the privacy calculation comprises, but is not limited to, at least one of a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the application. In other words, the combined credit investigation method based on the blockchain and the privacy calculation can be executed by software or hardware installed in the terminal device or the server device. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a combined credit investigation method based on blockchain and privacy calculation according to an embodiment of the present invention is shown. In this embodiment, the combined credit investigation method based on blockchain and privacy calculation includes:
s1, acquiring user information in a target mechanism, and generating a primary public and private key of the user information.
In the embodiment of the invention, the target mechanism refers to a mechanism for sharing information in a blockchain, and the user information refers to information of a user related to the target mechanism, wherein the user information includes but is not limited to: user account, user base information, user credit conditions, etc.
In detail, since each target organization has its own public and private key, the target organization refers to a participant on the blockchain, and the primary public and private key is generated by using an encryption algorithm, where the encryption algorithm may be an elliptic curve encryption algorithm or a public and private key generation algorithm, and the primary public and private key may be used for information sharing of the target organization on the blockchain.
In an embodiment of the present invention, the generating the primary public-private key of the user information includes:
generating a primary public and private key of the user information by using a preset public and private key generation algorithm, wherein the preset public and private key generation algorithm is as follows:
(x i ,y i )＝PSGen()
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, PSGen () is a random password generation function, and i is the information identification corresponding to the user information.
S2, verifying the validity of the primary public and private key by using a preset public key correctness proving algorithm to obtain a trust public and private key of the primary public and private key.
In the embodiment of the invention, the validity verification refers to whether the target organization is a trusted organization, if the target organization is not a trusted organization, a primary public-private key generated by the target organization will not be recorded, and if the target organization is a trusted organization, an initial public-private key of the target organization is a trusted public-private key, and the trusted public-private key refers to a public-private key recorded in a blockchain.
In the embodiment of the present invention, the verifying the validity of the primary public and private key by using a preset public key correctness proving algorithm to obtain a trusted public and private key of the primary public and private key includes:
generating a public key correctness proving parameter of the primary public and private key by using a preset public key correctness proving algorithm, and performing public processing on the public key correctness proving parameter and the public key in the primary public and private key to obtain public information of the primary public and private key;
and carrying out information correctness verification on the public information, and determining that the primary public and private key corresponding to the public information passing the information correctness verification is a trust public and private key.
In detail, the preset public key correctness checking algorithm is as follows:
PkProof i ＝PkProofGen(x i ,y i )
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, pkProofGen is a public key correctness proving function, i is the information identifier corresponding to the user information, and PkProof i Is the public key correctness proving parameter of the ith user information.
S3, generating a trusted random number of the user information according to the trusted public and private key, and carrying out signature processing on the trusted random number according to the trusted random number and a target mechanism corresponding to the user information to obtain a digital signature of the trusted random number.
In the embodiment of the invention, the trusted random number is generated by mutually-untrusted participants under the premise of no third-party trust mechanism, the information input by the hidden participants is shared by using threshold secrets in the random number generation process, the verifiability of the interaction information is ensured through zero knowledge proof and homomorphic promise, the participants are mainly responsible for the generation of the random number, and all people can verify the correctness of the random number generation through the information published in the process of executing a protocol by the participants.
In detail, a plurality of participants generate system random numbers together, each participant generates a public and private key pair according to system parameters, then generates a secret random number locally, encrypts and shares sub-shares of the secret random number to other participants through a threshold secret sharing scheme, uses zero knowledge proof and homomorphic promise to ensure that secret sub-shares can be verified under ciphertext, then calculates secret sub-shares under ciphertext by using homomorphic property, decrypts the sub-shares, publishes calculated sub-share values to other participants, and uses homomorphic promise values to verify correctness of share calculation. Finally, each participant collects a certain number of valid sub-shares, so that the random number can be reconstructed, wherein the participant refers to a target organization passing the validity verification.
In an embodiment of the present invention, referring to fig. 2, the generating, according to the trust public-private key, a trusted random number of the user information includes:
s21, acquiring a target mechanism of the trust public and private key, performing honest verification on the target mechanism according to the secret sub-share of the target mechanism to obtain a honest mechanism of the target mechanism, and determining the honest sub-share of the target mechanism according to the honest mechanism and the secret sub-share;
s22, homomorphism addition processing is carried out on the honest sub-share, and homomorphism ciphertext of the honest sub-share is obtained;
s23, performing share reconstruction on the homomorphic ciphertext to obtain a reconstructed ciphertext of the homomorphic ciphertext, and generating a trusted random number of the user information by using the reconstructed ciphertext.
In detail, the honest verification is to find out that the target mechanism has malicious participants, provide error information or malicious identities, and reject the malicious information, the mechanism set of the target mechanism after rejection and the user information provided by the mechanism set are the honest mechanisms, the random numbers provided by the honest mechanisms are the needed random numbers, and the shares corresponding to the random numbers are honest sub-shares.
In detail, the homomorphic addition processing is generated by utilizing the addition homomorphism of ciphertext, wherein the addition homomorphism is an operation result that ciphertext of two plaintext sums is equal to ciphertext corresponding to the two plaintext.
In detail, the performing honest verification on the target mechanism according to the secret sub-share of the target mechanism to obtain a honest mechanism of the target mechanism includes:
the target mechanism generates a secret random number locally, and generates a secret sub-share of the target mechanism by using a preset polynomial function and the secret random number, wherein the preset polynomial function is as follows:
wherein a is j (x) Is the secret sub-share corresponding to the decryption private key of the jth target mechanism, t is the total number of random numbers of the secret random numbers, k is the random number identifier of the secret random numbers, a jk A secret random number which is the kth secret random number of the jth target mechanism, x is the decryption private key of the jth target mechanism, mod (x) is a mod function, N is the product of randomly selecting two large prime numbers, and j is the mechanism identification of the target mechanism;
determining a promise value of the target institution according to the secret sub-share, and carrying out effective promise verification on the target institution by utilizing the promise value to obtain a promise institution of the target institution;
and obtaining the sub-share ciphertext of the promise mechanism, carrying out ciphertext correctness verification on the sub-share ciphertext by using a preset ciphertext correctness verification algorithm, and determining that the target mechanism corresponding to the sub-share ciphertext passing the ciphertext correctness verification is an honest mechanism.
In detail, each participant generates a secret random number locally, then respectively serves as a leader to share the secret sub-shares to other participants after encryption, and generates a ciphertext correctness proving parameter so that the participant can verify the correctness of the secret sub-shares under the ciphertext.
In detail, the target mechanism selects a random integer to construct a polynomial function, calculates a sub-share and a commitment value according to the polynomial function and the random integer, encrypts a public key of the target mechanism to obtain a ciphertext of the target mechanism, generates the ciphertext correctness verification parameter, and finally judges the integrity of the target mechanism, wherein the integrity judgment mainly verifies from the commitment value and the sub-share ciphertext published by the participant, and if the verification passes, the participant honest shares all secret sub-shares.
Further, each participant is used as a leader to share the secret random number sub-share, and the correctness of the sub-shares obtained by other participants can be verified under the ciphertext condition, so that malicious participants can be screened out in time, and the honest participants can be ensured to obtain the correct secret sub-shares.
In detail, the homomorphic addition processing is performed on the honest sub-share to obtain homomorphic ciphertext of the honest sub-share, which includes:
generating an encryption total of the honest sub-share according to the honest sub-share and the honest ciphertext corresponding to the honest sub-share, wherein the encryption total is as follows:
wherein e pj Is the encrypted sum of the honest sub-shares, p is the honest sub-share identity of the honest sub-shares, enc is the encryption algorithm, enc (α j (p),y j ,r pj ) By means of public key y j For the honest seed share alpha j (p) encrypting, j is the organization identity of the target organization, n is the total number of honest sub-shares of the honest sub-shares, α j (p) is the j-thThe p-th honest share of the target mechanism, y j Is the public key of the jth target institution, r pj Is a random integer selected during encryption;
and carrying out decryption processing on the encryption total to obtain the decryption total of the encryption total, and determining the decryption total as homomorphic ciphertext of the honest sub-share.
In detail, the participant uses the additive homomorphism of the cryptosystem to solve the ciphertext of all secret sub-shares.
In detail, the decrypting the encrypted total is performed using a decryption function, wherein a ciphertext decrypting process using a private key is represented as m=dec (e, x), where e is a ciphertext and x is a private key.
In detail, the same-station ciphertext is obtained by decrypting the ciphertext.
In detail, the performing share reconstruction on the homomorphic ciphertext to obtain a reconstructed ciphertext of the homomorphic ciphertext includes:
and calculating the homomorphic ciphertext and the retrograde interpolation by using a preset interpolation algorithm to obtain a reconstructed ciphertext of the homomorphic ciphertext, wherein the preset interpolation algorithm is as follows:
wherein A is the reconstructed ciphertext of the homomorphic ciphertext, m is the total homomorphic ciphertext of the homomorphic ciphertext, g is the homomorphic ciphertext identification of the homomorphic ciphertext,is the g homomorphic ciphertext, B m Is the mth interpolation point, B g Is the g-th interpolation point.
In detail, the method for generating the trusted random number of the user information by using the reconstructed ciphertext is characterized in that the reconstructed ciphertext calculated by each participant is uniquely determined, and then the reconstructed ciphertext is mapped to a value in a finite field by using a one-way hash function with uniform distribution output, so that the trusted random number is generated.
In detail, all the participants execute the protocol honestly, and finally, a credible random number can be generated, wherein the output value of the protocol has randomness.
Further, all interactive information of the participants in the execution protocol can be publicly verified, so that dishonest participants can be rapidly judged.
In detail, in the key generation stage, the participants disclose the public key and the public key correctness proving parameter, and the rest participants verify the public key correctness proving parameter, when the verification is passed, the public key is a valid public key, and can be used for encryption. In the sub-share sharing stage, each participant as a leader publishes the promise value of the secret sub-share, the ciphertext of the secret sub-share and the ciphertext correct trust proving parameter, and the other participants verify the correctness of all promise values first, then verify the correctness of the encrypted content and the encrypted form of the ciphertext of the secret sub-share, which is publicly verifiable, and each participant can verify the validity of the secret sub-share of itself and the correctness of the secret sub-share obtained by other participants in the ciphertext state, so that the parties commonly identify malicious participants. In the sub-share reconstruction stage, each participant discloses the calculated reconstructed ciphertext, and the other participants can verify the correctness of the reconstructed ciphertext, so that the correctness and uniqueness of a calculation result are effectively ensured.
In the embodiment of the present invention, the signing process is performed on the trusted random number according to the target mechanism corresponding to the trusted random number and the user information, so as to obtain a digital signature of the trusted random number, which includes:
generating index information of the trusted random number according to a target mechanism corresponding to the user information;
and carrying out ring signature processing on the trusted random number according to the index information to obtain a digital signature of the trusted random number.
In detail, the ring signature processing means that the super node performs ring signature on the same random data, performs consistent sorting according to hash values of signature data, selects a plurality of first ranks to generate a block sequence table, each item in the sequence table is composed of ring signature data and corresponding hash values, and determines the sequence of issuing blocks by the witness node, wherein the ring signature can effectively protect identity privacy of the witness, and identity verification of a true signer is given when issuing the blocks, so that the identity verification of the block proposer can be proved to be owned by the accounting right.
In detail, the index information may include a data title, a ciphertext hash value, etc., and the index information is generated by a storage.
And S4, carrying out distributed node sharing processing on the trusted random number according to the digital signature to obtain a shared ciphertext of the trusted random number.
In the embodiment of the invention, the sharing process refers to uploading credit information, basic information and the like of the target mechanism about the user to the blockchain so as to enable other participants in the blockchain to carry out information retrieval.
In the embodiment of the present invention, referring to fig. 3, the performing, according to the digital signature, distributed node sharing processing on the trusted random number to obtain a shared ciphertext of the trusted random number includes:
s31, establishing a hash tree of the trusted random number according to the digital signature, and determining an on-chain information table of the trusted random number according to the hash tree;
s32, establishing an under-chain storage layer of the trusted random number, and collecting node data of the trusted random number in the on-chain information table and the under-chain storage layer;
and S33, performing node distribution on the node data according to a preset node frame to obtain the shared ciphertext of the trusted random number.
In detail, the preset node frame adopts a storage mode of combining on-chain and off-chain, and a re-encryption node is introduced to store and transmit mass data, so that the integrity, reliability and verifiability of user data are ensured. The on-chain-off-chain storage model is divided into a network layer (on-chain) and a data storage layer (off-chain), wherein a block head and a block body are stored in the network layer, the block head is used for maintaining normal running of a block chain, the block body is used for storing an index information list, a inquirer is used for searching information on the block chain, and massive encrypted data uploaded by a user are stored in the data storage layer.
Further, the index information is sent to the whole node and stored in the block body of the network layer on the chain to form an index information list. The frame has three types of nodes, namely a light node, a full node and a heavy encryption node. The light node is responsible for recording the block head of the blockchain and promoting the running of the blockchain; the full node is responsible for recording information on the whole chain, comprises a block head and a block body, and provides index information in the block body for a inquirer; the re-encryption nodes are responsible for storing a large amount of data of the data storage layer under the chain, and the number of honest re-encryption nodes is more than half of the number of all re-encryption nodes, so that the whole scheme data can be guaranteed not to be tampered.
S5, acquiring a credit inquiry task of the user to be inquired, and generating a user credit of the user to be inquired according to the shared ciphertext and the credit inquiry task.
In the embodiment of the invention, the step of generating the user credit of the user to be queried according to the shared ciphertext and the credit inquiry task means that the credit inquiry task is firstly subjected to task analysis to obtain task analysis data of the user to be queried, the shared data on a blockchain is called according to the task analysis data, and then the called data and the retrograde ciphertext are decrypted by using a private key to obtain the user credit of the user to be queried.
The embodiment of the invention eliminates malicious participants in a blockchain by generating the primary public and private keys of user information in the target mechanism and verifying the validity of the primary public and private keys, ensures that the target mechanism in the blockchain is an honest participant, shares information input by a hidden participant by using a threshold secret, ensures the verifiability of interaction information through zero knowledge proof and homomorphic promise, generates a trusted random number of the honest participant, ensures the privacy and safety of data on the blockchain, generates a digital signature of the trusted random number, improves the queriability of credit and reduces the inquiring time, so the invention provides a combined credit investigation method based on the blockchain and privacy calculation, and can solve the problem of lower inquiring efficiency when the target user is subjected to credit investigation.
Fig. 4 is a functional block diagram of a combined credit investigation device based on blockchain and privacy calculation according to an embodiment of the present invention.
The combined credit investigation device 100 based on blockchain and privacy calculation can be installed in an electronic device. Depending on the implementation, the combined credit investigation device 100 based on blockchain and privacy calculation may include a primary public-private key module 101, a trusted public-private key module 102, a trusted random number module 103, a shared secret module 104, and a credit investigation module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the primary public-private key module 101 is configured to obtain user information in a target mechanism, and generate a primary public-private key of the user information;
the trusted public-private key module 102 is configured to perform validity verification on the primary public-private key by using a preset public-key correctness proving algorithm, so as to obtain a trusted public-private key of the primary public-private key, where the preset public-key correctness proving algorithm is:
PkProof i ＝PkProofGen(x i ,y i )
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, pkProofGen is a public key correctness proving function, i is the information identifier corresponding to the user information, and PkProof i Is the public key correctness proving parameter of the ith user information;
the trusted random number module 103 is configured to generate a trusted random number of the user information according to the trusted public and private key, and perform signature processing on the trusted random number according to the trusted random number and a target mechanism corresponding to the user information to obtain a digital signature of the trusted random number;
the shared ciphertext module 104 is configured to perform distributed node sharing processing on the trusted random number according to the digital signature, to obtain a shared ciphertext of the trusted random number;
the credit inquiry module 105 is configured to obtain a credit inquiry task of a user to be inquired, and generate a user credit of the user to be inquired according to the shared ciphertext and the credit inquiry task.
In the several embodiments provided in the present invention, it should be understood that the disclosed method and apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application that uses a digital computer or a digital computer-controlled machine to simulate, extend and expand human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the apparatus claims can also be implemented by means of one unit or means in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims (10)

1. A joint credit investigation method based on blockchain and privacy calculation, the method comprising:
acquiring user information in a target mechanism, and generating a primary public and private key of the user information;
performing validity verification on the primary public and private key by using a preset public key correctness proving algorithm to obtain a trust public and private key of the primary public and private key, wherein the preset public key correctness proving algorithm is as follows:
PkProof i ＝PkProofGen(x i ,y i )
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, pkProofGen is a public key correctness proving function, i is the information identifier corresponding to the user information, and PkProof i Is the public key of the ith user informationA corroborative proving parameter;
generating a trusted random number of the user information according to the trusted public and private key, and carrying out signature processing on the trusted random number according to the trusted random number and a target mechanism corresponding to the user information to obtain a digital signature of the trusted random number;
carrying out distributed node sharing processing on the trusted random number according to the digital signature to obtain a shared ciphertext of the trusted random number;
and acquiring a credit inquiry task of the user to be inquired, and generating a user credit of the user to be inquired according to the shared ciphertext and the credit inquiry task.
2. The blockchain and privacy computation based joint credit method of claim 1, wherein the generating the primary public-private key of the user information comprises:
generating a primary public and private key of the user information by using a preset public and private key generation algorithm, wherein the preset public and private key generation algorithm is as follows:
(x i ,y i )＝PSGen()
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, PSGen () is a random password generation function, and i is the information identification corresponding to the user information.
3. The method for combined credit investigation based on blockchain and privacy calculation according to claim 1, wherein the verifying the validity of the primary public-private key by using a preset public-key correctness proving algorithm to obtain a trusted public-private key of the primary public-private key comprises:
generating a public key correctness proving parameter of the primary public and private key by using a preset public key correctness proving algorithm, and performing public processing on the public key correctness proving parameter and the public key in the primary public and private key to obtain public information of the primary public and private key;
and carrying out information correctness verification on the public information, and determining that the primary public and private key corresponding to the public information passing the information correctness verification is a trust public and private key.
4. The blockchain and privacy computation based joint credit method of claim 1, wherein the generating the trusted random number of the user information from the trusted public-private key comprises:
the method comprises the steps of obtaining a target mechanism of the trust public and private key, performing honest verification on the target mechanism according to a secret sub-share of the target mechanism to obtain a honest mechanism of the target mechanism, and determining the honest sub-share of the target mechanism according to the honest mechanism and the secret sub-share;
homomorphism addition processing is carried out on the honest sub-share, so that homomorphism ciphertext of the honest sub-share is obtained;
and performing share reconstruction on the homomorphic ciphertext to obtain a reconstructed ciphertext of the homomorphic ciphertext, and generating a trusted random number of the user information by using the reconstructed ciphertext.
5. The blockchain and privacy computation-based joint credit investigation method of claim 4, wherein the performing honest verification on the target institution according to the secret sub-share of the target institution to obtain honest institutions of the target institution comprises:
the target mechanism generates a secret random number locally, and generates a secret sub-share of the target mechanism by using a preset polynomial function and the secret random number, wherein the preset polynomial function is as follows:
wherein a is j (x) Is the secret sub-share corresponding to the decryption private key of the jth target mechanism, t is the total number of random numbers of the secret random numbers, k is the random number identifier of the secret random numbers, a jk A secret random number which is the kth secret random number of the jth target mechanism, x being the jth target mechanismDecrypting the private key, mod (x) is a mod function, N is the product of randomly selecting two large primes, j is the organization identity of the target organization;
determining a promise value of the target institution according to the secret sub-share, and carrying out effective promise verification on the target institution by utilizing the promise value to obtain a promise institution of the target institution;
and obtaining the sub-share ciphertext of the promise mechanism, carrying out ciphertext correctness verification on the sub-share ciphertext by using a preset ciphertext correctness verification algorithm, and determining that the target mechanism corresponding to the sub-share ciphertext passing the ciphertext correctness verification is an honest mechanism.
6. The method of claim 4, wherein homomorphism adding and processing the honest sub-shares to obtain homomorphism ciphertext of the honest sub-shares comprises:
generating an encryption total of the honest sub-share according to the honest sub-share and the honest ciphertext corresponding to the honest sub-share, wherein the encryption total is as follows:
wherein e pj Is the encrypted sum of the honest sub-shares, p is the honest sub-share identity of the honest sub-shares, enc is the encryption algorithm, enc (α j (p),y j ,r pj ) By means of public key y j For the honest seed share alpha j (p) encrypting, j is the organization identity of the target organization, n is the total number of honest sub-shares of the honest sub-shares, α j (p) is the jth target mechanism's jth honest share, y j Is the public key of the jth target institution, r pj Is a random integer selected during encryption;
and carrying out decryption processing on the encryption total to obtain the decryption total of the encryption total, and determining the decryption total as homomorphic ciphertext of the honest sub-share.
7. The method for combined credit investigation based on blockchain and privacy calculation of claim 4, wherein the performing share reconstruction on the homomorphic ciphertext to obtain a reconstructed ciphertext of the homomorphic ciphertext comprises:
and calculating the homomorphic ciphertext and the retrograde interpolation by using a preset interpolation algorithm to obtain a reconstructed ciphertext of the homomorphic ciphertext, wherein the preset interpolation algorithm is as follows:
wherein A is the reconstructed ciphertext of the homomorphic ciphertext, m is the total homomorphic ciphertext of the homomorphic ciphertext, g is the homomorphic ciphertext identification of the homomorphic ciphertext,is the g homomorphic ciphertext, B m Is the mth interpolation point, B g Is the g-th interpolation point.
8. The method for combined credit investigation based on blockchain and privacy calculation according to claim 1, wherein the signature processing is performed on the trusted random number according to the target mechanism corresponding to the trusted random number and the user information to obtain the digital signature of the trusted random number, comprising:
generating index information of the trusted random number according to a target mechanism corresponding to the user information;
and carrying out ring signature processing on the trusted random number according to the index information to obtain a digital signature of the trusted random number.
9. The method for combined credit investigation based on blockchain and privacy calculation according to any of claims 1 to 8, wherein the performing distributed node sharing processing on the trusted random number according to the digital signature to obtain a shared ciphertext of the trusted random number comprises:
establishing a hash tree of the trusted random number according to the digital signature, and determining an on-chain information table of the trusted random number according to the hash tree;
establishing an under-chain storage layer of the trusted random number, and collecting node data of the trusted random number in the on-chain information table and the under-chain storage layer;
and performing node distribution on the node data according to a preset node frame to obtain the shared ciphertext of the trusted random number.
10. A joint credit investigation apparatus based on blockchain and privacy computation, the apparatus comprising:
the primary public and private key module is used for acquiring user information in a target mechanism and generating a primary public and private key of the user information;
the trust public-private key module is used for verifying the validity of the primary public-private key by using a preset public-key correctness proving algorithm to obtain a trust public-private key of the primary public-private key, wherein the preset public-key correctness proving algorithm is as follows:
PkProof i ＝PkProofGen(x i ,y i )
wherein x is i Is the primary private key of the ith user information, y i Is the primary public key of the ith user information, pkProofGen is a public key correctness proving function, i is the information identifier corresponding to the user information, and PkProof i Is the public key correctness proving parameter of the ith user information;
the trusted random number module is used for generating a trusted random number of the user information according to the trusted public and private key, and carrying out signature processing on the trusted random number according to the trusted random number and a target mechanism corresponding to the user information to obtain a digital signature of the trusted random number;
the shared ciphertext module is used for carrying out distributed node sharing processing on the trusted random number according to the digital signature to obtain a shared ciphertext of the trusted random number;
and the credit inquiry module is used for acquiring a credit inquiry task of the user to be inquired and generating a user credit of the user to be inquired according to the shared ciphertext and the credit inquiry task.
CN202310347195.6A 2023-04-03 2023-04-03 Combined credit investigation method and device based on block chain and privacy calculation Pending CN116527322A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117728963A (en) * 2024-02-18 2024-03-19 深圳市纽创信安科技开发有限公司 Zero knowledge proving method and safe multiparty computing system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117728963A (en) * 2024-02-18 2024-03-19 深圳市纽创信安科技开发有限公司 Zero knowledge proving method and safe multiparty computing system
CN117728963B (en) * 2024-02-18 2024-04-16 深圳市纽创信安科技开发有限公司 Zero knowledge proving method and safe multiparty computing system

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