CN113127926A - Method, system, storage medium and computer for analyzing statistical relevance of private data - Google Patents

Method, system, storage medium and computer for analyzing statistical relevance of private data Download PDF

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CN113127926A
CN113127926A CN202110270194.7A CN202110270194A CN113127926A CN 113127926 A CN113127926 A CN 113127926A CN 202110270194 A CN202110270194 A CN 202110270194A CN 113127926 A CN113127926 A CN 113127926A
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ciphertext
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CN113127926B (en
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谢敏
房春朋
裴庆祺
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Xi'an Xidian Lianrong Technology Co ltd
Xidian University
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Xidian University
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    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
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Abstract

The invention belongs to the technical field of private data analysis and block chain application, and discloses a private data statistics correlation analysis method, a system, a storage medium and a computer, wherein participants register identity information; generating a verification key and a signature key required by authentication according to an RSA signature algorithm; generating different public and private key pairs by using a Paillier encryption system, and publishing zero-knowledge proof parameters in a block chain network; submitting an information query request and authorization information to a blockchain network; the participator uses the parameters provided by the analyst and the parameters published by the supervisor to process data; when the required information is inquired, the obtained authorization information is provided to a block chain network, and the identity is verified through an intelligent contract; and after the ciphertext data on the block chain is obtained, decrypting the ciphertext data through a private key and calculating a related statistical relevance function by using the decrypted information value. According to the invention, the statistic correlation analysis of the private data is carried out on the block chain, so that the data can be monitored and the calculation process is credible.

Description

Method, system, storage medium and computer for analyzing statistical relevance of private data
Technical Field
The invention belongs to the technical field of private data analysis and block chain application, and particularly relates to a private data statistical correlation analysis method, a private data statistical correlation analysis system, a storage medium and a computer.
Background
Currently, as various activities in life are spread in computer networks, some government agencies, enterprises, large enterprise companies, etc. generate a large amount of sensitive data. Researchers expect to obtain more beneficial information from their data, but privacy concerns prevent researchers from mining and analyzing information, and data statistics correlation analysis schemes for privacy protection are compliant.
Due to various requirements on data information, data are analyzed and extracted, and joint calculation of the data is performed, but some privacy problems are also faced. Mainly when data is calculated, no one party is allowed to view other data. Secure multi-party computing is therefore proposed and applied, and a secure multi-party computing protocol allows a group of untrusted data owners to collaborate together to perform an analytical query against their data, while not revealing the entire data set. In the existing data sharing model, data transaction lacks transparency, data owners lose control right and ownership of data, and data safety cannot be guaranteed. For this reason, traceability and non-tamper of data are increased by means of the block chain technique. The method can realize statistical correlation analysis of data while protecting private data, compile a calculation contract according to the calculation requirements of data demand parties, and guarantee calculation and output of a data owner by means of safe multi-party calculation.
Through the above analysis, the problems and defects of the prior art are as follows: in the existing data sharing model, data transaction lacks transparency, a data owner loses control right and ownership of data, and data safety cannot be guaranteed.
The difficulty in solving the above problems and defects is: under the condition that no trusted third party exists, how the participant computer obtains ciphertext data of other participant computers can not reveal the privacy of each participant computer, how fairness in the whole computing process is ensured, and the non-tampering property and traceability of a computing result are ensured, how statistical relevance analysis is realized while privacy data is protected, and how the problem of data supervision is solved. The method solves the problem of how to ensure fairness, safety and low efficiency by the participation of a third party.
The significance of solving the problems and the defects is as follows: under the condition of no centralized service provider, the traditional mode of carrying out privacy calculation by using a server is broken through, and the participators can trust each other to carry out data calculation, so that the traceability, the accuracy and the supervision of the whole calculation process are ensured, and meanwhile, the problems of low efficiency on a chain and increased storage cost cannot be caused.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method, a system, a storage medium and a computer for analyzing the statistical relevance of private data.
The invention is realized in such a way that a method for analyzing the statistical relevance of private data comprises the following steps:
step one, registering identity information by a participant;
step two, according to RSA signature algorithm, the supervisor generates verification key and signature key (pk) required by authentication*，sk*) (ii) a (ensuring authenticity of identity when a research analyst queries)
Thirdly, the supervisor generates a public and private key pair (Jpk, Jsk) by utilizing the Paillier encryption system, and a zero-knowledge proof parameter ZJAnd published in a blockchain network (Jpk, Z)J) (ii) a (verifying that the data involved in the calculation is the same as the data submitted to the supervisor, enabling data supervision)
Step four, the analyst submits the information inquiry request and the authorization information m to the blockchain networkωThe method comprises a data ciphertext calculation mode; (acquisition of demand data by a research analyst without revealing analyst identity)
Step five, the participator uses the parameters pk, Z provided by the analystYParameters JPk, Z published with supervisorJCarrying out data processing; (according to the needs of the research analystCiphertext processing)
Step six, when the analyst wants to inquire the needed information, the authorization information m obtained in the step two is obtainedωProviding to a blockchain network, verifying the identity of the analyst through the intelligent contract; (verifying the identity of the analyst, ensuring the validity of the identity)
And seventhly, after the research analyst obtains the ciphertext data on the block chain, decrypting the ciphertext data through the private key and calculating a related statistical relevance function by using the decrypted information value. (analyst performs statistical correlation analysis based on ciphertext data)
By combining the technical scheme, the invention has the advantages and positive effects that: the invention designs a scheme for carrying out the correlation analysis of the privacy data statistics by combining a block chain and safe multiparty computation, realizes that the data analysis is completed while the identity information of a data provider and a data analyzer is not leaked, prevents the computation result error caused by malicious input of some participants by storing the computation process and the result on the block chain, and can realize the supervision of a supervision department on the data; the cryptograph calculation is completed without revealing respective data through a homomorphic encryption algorithm, the multi-party calculation is carried out under the chain, and the result is fed back to the block chain, so that the storage cost of the data on the chain is reduced, and the efficiency of the whole system is improved.
Further, in the step one, registering the identity information by the participant specifically includes:
a research analyst generates a public and private key pair (pk, sk) by utilizing a Paillier encryption algorithm and a zero-knowledge proof parameter ZY；
A research analyst needs to register to access the linked data, a supervisor stores the hash value of the user information into a user information pool, and the supervisor maintains one user information pool;
analyst registration identity information MI D ═ { ID, pk, ZY，MiIn which ID is the user's personal information, pk is a public key generated by a research analyst using Paillier, ZYFor zero knowledge proof parameters, MiQuery the analyst for information commands.
Further, in the second step, the specific process of the supervisor generating the verification key and the signature key required for authentication includes:
after registering the information, the manager confirms that the information is a normal research analyst, and feeds back authorization information m to the trusted research analystωAnd the generated signature key sk*The authorization information includes public keys of research analysts, available authorities, authorization deadlines, and the like.
Further, in the fifth step, data processing mainly encrypts data and performs ciphertext calculation through a Paillier encryption algorithm, and each step and processing results of the data processing are provided to a block chain network, so that the traceability and the non-falsification of the data are ensured;
the supervisor obtains the data submitted to the blockchain network by the participating computer, decrypts the ciphertext by using the private key Jsk of the supervisor, sees all circulating data, and verifies through zero knowledge proof that the data provided by the participating computer to the analyst is consistent with the data provided to the supervisor, thereby realizing the supervision of the data.
Further, in the fifth step, the data is processed into some common statistical functions, and the centralized data set summation is calculated as follows:
after receiving the query command, the participating computer encrypts the data by using the public key to obtain a ciphertext Epk(mi) Then ciphertext (E) with the field of query command Mpk(mi) M) submitting to a blockchain network;
through the intelligent contract compiled in advance, the participating calculator can obtain the ciphertext with the query command M; after the participator obtains all the ciphertext data with the query command M, the ciphertext calculation is carried out to obtain Epk＝Epk(m1)+Epk(m2)+……+Epk(mn) Will (E)pk，mω) Submitting to a blockchain network, where mωAuthorization information for the supervisor to the research analyst;
by the above process, the sum of the data can be received without actual data in each of the participating calculators, and there may be a plurality of variables in other statistical functions, by which the calculation can also be performed.
Further, the average value calculation:
in a centralized data set by
Figure BDA0002974017540000041
Calculating an average value, and calculating the average value by the following formula for the distributed data set:
Figure BDA0002974017540000042
further, the fifth step specifically comprises the following steps:
after the participator receives the command, the data is encrypted by using the public key to obtain a ciphertext
Figure BDA0002974017540000043
Then, the ciphertext with the field of the query command M is transmitted
Figure BDA0002974017540000044
(E(ni)，M2) Submitting to a blockchain network, where M1，M2Respectively judging data and information fields and judging the number of data calculators participating in the data;
acquisition of a participant computer with a query M by a previously compiled intelligent contract1，M2The ciphertext of (1);
the participating calculator obtains all the query commands M1，M2After the ciphertext data is obtained, ciphertext calculation is carried out to obtain
Figure BDA0002974017540000045
Will (E)pk，E(n)，mω) Submitting to a blockchain network, where mωAuthorization information for the supervisor to the research analyst;
after the ciphertext is obtained, the private key is used for decryption to obtain:
Figure BDA0002974017540000051
D(E(n))＝n1+n2+……+ni；
finally, the data analyst calculates
Figure BDA0002974017540000052
Average of the distributed data set.
Further, the authorization information m is verified in the sixth stepωIf all the verification is passed, the block chain network provides the analyst with partial authorization information m according to the query command of the research analystωThe research analyst will decrypt the ciphertext using the private key;
in the first step to the seventh step, a public key pk provided by a research analyst is used for encryption and then transmitted to a block chain; the data on the blockchain can only be decrypted by a research analyst, and the access authority of the research analyst to the blockchain is limited to a specific value due to the authorization of a supervisor, so that the information of the participating computer is not leaked.
Another object of the present invention is to provide a program storage medium for receiving user input, the stored computer program causing an electronic device to execute the method for statistical correlation analysis of private data, comprising the steps of:
step one, registering identity information by a participant;
step two, according to RSA signature algorithm, the supervisor generates verification key and signature key (pk) required by authentication*，sk*)；
Thirdly, the supervisor generates a public and private key pair (Jpk, Jsk) by utilizing the Paillier encryption system, and a zero-knowledge proof parameter ZJAnd published in a blockchain network (Jpk, Z)J)；
Step four, the analyst submits the information inquiry request and the authorization information m to the blockchain networkωThe method comprises a data ciphertext calculation mode;
step five, the participator uses the parameters pk, Z provided by the analystYParameters Jpk, Z published with supervisorJCarrying out data processing;
step six, when the analyst wants to inquire the needed information, the authorization information m obtained in the step two is obtainedωProviding to a blockchain network, verifying the identity of the analyst through the intelligent contract;
and seventhly, after the research analyst obtains the ciphertext data on the block chain, decrypting the ciphertext data through the private key and calculating a related statistical relevance function by using the decrypted information value.
It is a further object of the invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing said method of statistical relevance analysis of private data when executed on an electronic device.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention provides a safe multi-party calculation and block chain combined mode, and a scheme capable of carrying out privacy data statistic correlation analysis on the block chain is constructed by utilizing the characteristics of distributed storage, non-tampering property, privacy and the like, so that the data verification and the calculation process credibility are ensured as much as possible. The block chain technology is utilized to increase the transparency and accessibility of data, and a Paillier cryptosystem is used to protect the confidentiality of private data. The invention is designed for a network with multiple participating calculators and research analysts, where the participating calculators join the blockchain network and maintain and share the distributed ledger, and the research analysts do not join the blockchain network. The main body of the privacy data statistical relevance analysis system is a research analyst, a supervisor and a participating calculator, wherein the supervisor and the participating calculator are block link points, the research analyst does not add a block chain network, an intelligent contract is deployed in the block chain network in advance, and the intelligent contract is used for verifying the identity of the research analyst to determine whether to provide on-chain data for the research analyst.
In the invention, a research analyst sends a requirement to a block chain network and requires a participating computer to provide required data information, and each participating computer encrypts the inquired data information and performs ciphertext calculation by using a Paillier cryptosystem. The participating calculators transmit the information processed by the cryptographic system into a blockchain network. The participating computer may be any organization or organization, such as an insurance company, a bank, a health information provider, and so forth. The participating calculators in the blockchain network are also sharers and maintainers of the distributed ledger, thus reading all ciphertext information on the chain. The research analyst is the end-user of the blockchain network and may control access to data on the blockchain through intelligent contracts.
Drawings
Fig. 1 is a flowchart of a method for analyzing statistical relevance of private data according to an embodiment of the present invention.
Fig. 2 is a diagram of a statistical correlation architecture for private data according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a method for analyzing the statistical relevance of private data, and the invention is described in detail below with reference to the accompanying drawings.
One skilled in the art can also use other steps to implement the statistical correlation analysis method for private data provided by the present invention, and fig. 1 shows that the statistical correlation analysis method for private data provided by the present invention is only one specific embodiment.
As shown in fig. 1, a method for analyzing statistical relevance of private data according to an embodiment of the present invention includes:
s101: the participant registers identity information.
S102: according to the RSA signature algorithm, a supervisor generates an authentication key and a signature key (pk) required by authentication*，sk*)。
S103: the supervisor utilizes Paillier encryption system to generate public and private key pair (Jpk, Jsk), zero knowledge proof parameter ZJAnd published in a blockchain network (Jpk, Z)J)。
S104: the analyst submits information inquiry request and authorization information m to the blockchain networkωThe method comprises a data ciphertext calculation mode and the like.
S105: the participating calculators use the parameters pk, Z provided by the analystsYParameters Jpk, Z published with supervisorJAnd (6) carrying out data processing.
S106: when the analyst wants to inquire the required information, the authorization information m obtained at S102ωThe block chain network is provided, and the identity of the analyst is verified through the intelligent contract.
S107: after the research analyst obtains the ciphertext data on the block chain, the ciphertext data is decrypted through a private key, and the decrypted information value is used for calculating a related statistical relevance function.
In S101 provided by the embodiment of the present invention, the registering of the identity information by the participant specifically includes:
a research analyst generates a public and private key pair (pk, sk) by utilizing a Paillier encryption algorithm and a zero-knowledge proof parameter ZY。
Research analysts must register to access the linked data, supervisors store the hash values of the user information into a user information pool, and supervisors maintain one user information pool.
Analyst registration identity information MI D ═ { ID, pk, ZY，MiIn which ID is the user's personal information, pk is a public key generated by a research analyst using Paillier, ZYFor zero knowledge proof parameters, MiQuery the analyst for information commands.
In S102 provided by the embodiment of the present invention, a specific process of a supervisor generating a verification key and a signature key required for authentication includes:
after registering the information, the manager confirms that the information is a normal research analyst, and feeds back authorization information m to the trusted research analystωAnd the generated signature key sk*The authorization information includesThe research analyst public key, the permissions available, the authorization deadline, etc.
In S105 provided by the embodiment of the present invention, data processing mainly encrypts data and performs ciphertext calculation through a Paillier encryption algorithm, and provides each step and processing result of data processing to a block chain network, so as to ensure that data is traceable and not falsifiable;
the supervisor can obtain the data submitted to the blockchain network by the participating computer, the ciphertext in the data can be decrypted by using the private key Jsk of the supervisor, all circulating data can be seen, and the data provided to the analyst by the participating computer and the data provided to the supervisor are verified to be consistent through zero knowledge proof, so that the data can be supervised.
In S105 provided in the embodiment of the present invention, data processing is performed as some common statistical functions, as follows:
the summation function calculates:
after receiving the query command, the participating computer encrypts the data by using the public key to obtain a ciphertext Epk(mi) Then cipher text (E) with "query command M" fieldpk(mi) M) submitting to a blockchain network;
through the intelligent contract compiled in advance, the participating calculator can obtain the ciphertext with the query command M;
after the participator obtains all the ciphertext data with the 'query command M', the ciphertext calculation is carried out to obtain Epk＝Epk(m1)+Epk(m2)+……+Epk(mn) Will (E)pk，mω) Submitting to a blockchain network, where mωAuthorization information given to the research analyst by the supervisor.
Using these three simple steps, the research analyst can receive the sum of the data without the actual data in each of the participating calculators, but in other statistical functions there may be multiple variables, and more statistical functions can be calculated using similar methods.
Calculating an average value function:
in a centralized data setTo pass through
Figure BDA0002974017540000091
The average is calculated, which can be calculated for a distributed data set (see table 1) by the following formula:
Figure BDA0002974017540000092
TABLE 1 distributed data set
Figure BDA0002974017540000093
The method comprises the following specific steps:
after the participator receives the command, the data is encrypted by using the public key to obtain a ciphertext
Figure BDA0002974017540000094
Then, the ciphertext with the 'query command M' field is encrypted
Figure BDA0002974017540000095
(E(ni)，M2) Submit to blockchain network (see Table 2), where M1，M2The field for judging data and information and the field for judging the number of the data-participating calculators are respectively.
Acquisition of a document with a query command M by a pre-compiled intelligent contract participant1，M2"is encrypted; the participating calculator obtains all the data with "query command M1，M2After ciphertext data, ciphertext calculation is carried out to obtain
Figure BDA0002974017540000096
Will (E)pk，E(n)，mω) Submitting to a blockchain network, where mωAuthorization information given to the research analyst by the supervisor.
After obtaining the ciphertext, the research analyst decrypts the ciphertext by using the private key to obtain:
Figure BDA0002974017540000101
D(E(n))＝n1+n2+……+ni。
finally, the data analyst calculates
Figure BDA0002974017540000102
Average of the distributed data set.
X can be calculated in the same way3And other statistical correlation functions, which are not listed.
TABLE 2 participant data information upload Table
Figure BDA0002974017540000103
The authentication authorization information m in S106 provided by the embodiment of the inventionωIf all the verification is passed, the block chain network provides the analyst with partial authorization information m according to the query command of the research analystωThe research analyst will decrypt the ciphertext using the private key.
In all S101-S107 provided by the embodiment of the invention, a public key pk provided by a research analyst is adopted for encryption and then transmitted to a block chain; the data on the blockchain can only be decrypted by a research analyst, and the access right of the research analyst to the blockchain is limited to a specific value due to the authorization of a supervisor, so that the information of the participating computer is not leaked. The invention provides a method for joint privacy calculation analysis and provides data security thereof to research analysts.
The technical solution of the present invention is further described with reference to the following specific examples.
A researcher A in a disease control center wants to study the average value, element, of the influence of an element B on human healthThe influence value of the element B on the human body is known, and a supervisor C and a participant P are assumed to exist on a block chain1，P2，P3The data owned by the three are 8, 18 and 7 respectively.
The method comprises the following steps: the research analyst registers identity information.
Researcher a chooses (p is 5, q is 7) to run Paillier cryptosystem to generate public and private key pair (pk is (35, 3), sk is 12), zero proof of knowledge parameter ZARegistering identity information MID (ID)A，pk，ZA，M1，M2In which M is1For the analyst to query the field of the data sum, M2A field to count the number of people participating in a query.
Step two: the supervisor C receives the registration information and verifies the signature through the public key pk of the analyst; generating a verification key and a signature key (pk) required for authentication according to RSA signature algorithm*，sk*). After confirming that the research analyst is a normal research analyst, the supervisor stores the analyst's information in the user information pool and feeds back a signature key sk to the trusted research analyst*And authorization information mω＝{pk，ZA，M1，M2Time, where time is the authorization deadline.
Step three: supervisor C generates public and private key pairs (Jpk, Jsk) and a zero knowledge proof parameter Z using the same Paillier encryption systemCAnd published in a blockchain network (Jpk, Z)C)。
Step four: the researcher A submits an information query request and authorization information m to the blockchain networkωThe method comprises a data ciphertext calculation mode.
Step five: p1，P2，P3After receiving the authorization information, the public key pk is passed*And verifying the authorization information. After the verification is passed, the encryption calculation is carried out, P1Selecting a random number r1＝2
Calculation of Epk(8)＝498，EJpk(8)，ZA(pk，8)，ZC(Jpk，8)，
Will { (E)pk(8)＝498，EJpk(8)，ZA(pk，8)，ZC(Jpk，8))，M11Sending to a block chain network;
P2selecting a random number r2Calculate E6 ═ 6pk(18)＝314，EJpk(18)，ZA(pk，18)，ZC(Jpk，18)，
Will { (E)pk(18)＝314，EJpk(18)，ZA(pk，18)，ZC(Jpk，8))，M11Sending to a block chain network;
P3selecting a random number r2Calculate E4 ═ 4pk(7)＝538，EJpk(7)，ZA(pk，7)，ZC(Jpk，7)，
Will { (E)pk(7)＝538，EJpk(7)，ZA(pk，7)，ZC(Jpk，7))，M11It is sent to the blockchain network.
Due to P1，P2，P3Are all blockchain network nodes, and can acquire other nodes with M11Calculation of ciphertext data of a field, e.g. P1Can calculate (E)pk(8)·Epk(21)·Epk(7)mod 352) 36, acquiring the ciphertext data and obtaining the number of people participating in the calculation, namely 3; after the computation is finished, P1Will { Epk(n)＝36，M1}{3，M2It is sent to the blockchain network.
P2，P3And performing ciphertext calculation by adopting the same method and sending the ciphertext to the block chain network.
Supervisor C verifies by zero knowledge proof ZA(pk，8)，ZC(Jpk, 8) whether "8" is the same or not, and also verifies P1，P2，P3Finally provided data EpkAnd (n) whether the data are consistent or not is judged to be 36, and the accuracy of the data is ensured.
Step six: a passes the authorization information mωWith M on the acquisition block chain1，M2Ciphertext data { Epk(n)＝36，M1}，(3，M2}。
(Note: encryption of the number of people participating in the calculation is mainly used in distributed data set calculation, so here the number of people 3 is not encrypted)
Step seven: a acquisition data { Epk(n)＝36，M1}，{3，M2After that, the average value is obtained by decrypting with the private key sk of 12
Namely:
Figure BDA0002974017540000121
the average influence value is solved to be 11.
It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus and its modules of the present invention may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of hardware circuits and software, e.g., firmware.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.

Claims (10)

1.一种隐私数据统计相关性分析方法，其特征在于，所述隐私数据统计相关性分析方法，包括：1. a privacy data statistical correlation analysis method, is characterized in that, described privacy data statistical correlation analysis method, comprises: 步骤一，参与者注册身份信息；Step 1: Participants register identity information; 步骤二，根据RSA签名算法，监管者生成认证需要的验证钥与签名钥(pk*，sk*)；Step 2, according to the RSA signature algorithm, the supervisor generates the verification key and the signature key (pk * , sk * ) required for authentication; 步骤三，监管者利用Paillier加密系统生成公私钥对(Jpk，Jsk)，零知识证明参数ZJ并在区块链网络公布(Jpk，ZJ)；Step 3, the supervisor uses the Paillier encryption system to generate a public-private key pair (Jpk, Jsk), and the zero-knowledge proof parameter Z J is published on the blockchain network (Jpk, Z J ); 步骤四，分析者向区块链网络提交信息查询请求以及授权信息mω，包括对数据密文计算方式；Step 4, the analyst submits an information query request and authorization information m ω to the blockchain network, including the calculation method of the data ciphertext; 步骤五，参与计算者利用分析者提供的参数pk，ZY与监管者公布的参数Jph，zJ进行数据处理；Step 5, the participating calculators use the parameters pk, Z Y provided by the analyst and the parameters Jph, z J published by the regulator to process data; 步骤六，当分析者想要查询需要的信息时，将在步骤二得到的授权信息mω提供到区块链网络，查询密文信息；Step 6, when the analyst wants to query the required information, the authorization information m ω obtained in Step 2 is provided to the blockchain network to query the ciphertext information; 步骤七，研究分析者获取区块链的上的密文数据后，通过私钥进行解密并使用解密后的信息值计算相关的统计相关性函数。Step 7: After the research analyst obtains the ciphertext data on the blockchain, he decrypts it with the private key and uses the decrypted information value to calculate the relevant statistical correlation function. 2.如权利要求1所述隐私数据统计相关性分析方法，其特征在于，所述步骤一中，参与者注册身份信息具体，包括：2. The method for analyzing the statistical correlation of privacy data as claimed in claim 1, wherein in the step 1, the participant registration identity information is specific, comprising: 研究分析者利用Paillier加密算法生成公私钥对(pk，sk)，零知识证明参数ZY；The research analyst uses the Paillier encryption algorithm to generate a public-private key pair (pk, sk), and the zero-knowledge proof parameter Z Y ; 研究分析者必须进行注册才能访问链上数据，监管者将用户信息的哈希值存储到用户信息池，监管者维护一个用户信息池；Research analysts must register to access the data on the chain. The supervisor stores the hash value of user information in the user information pool, and the supervisor maintains a user information pool; 分析者注册身份信息MID＝{ID，pk，ZY，Mi}，其中ID为用户个人信息，pk为研究分析者利用Paillier生成的公钥，ZY为零知识证明参数，Mi为分析者查询信息命令。The analyst's registered identity information MID={ID, pk, Z Y , Mi }, where ID is the user's personal information, pk is the public key generated by the research analyst using Paillier, Z Y is a zero knowledge proof parameter, and Mi is the analysis User query information command. 3.如权利要求1所述隐私数据统计相关性分析方法，其特征在于，所述步骤二中，监管者生成认证需要的验证钥与签名钥具体过程为：3. the statistical correlation analysis method of privacy data as claimed in claim 1, is characterized in that, in described step 2, supervisor generates the verification key and signature key concrete process that authentication needs: 注册信息后，确认是正常的研究分析者，监管者反馈给信任的研究分析者一个授权信息mω和上述生成的签名钥sk*，授权信息里包括研究分析者公钥、可使用的权限、授权期限等。After registering the information, it is confirmed that it is a normal research analyst, and the supervisor feeds back an authorization information m ω and the above-generated signature key sk * to the trusted research analyst. The authorization information includes the research analyst's public key, available permissions, Authorization period, etc. 4.如权利要求1所述隐私数据统计相关性分析方法，其特征在于，所述步骤五中，数据处理主要通过Paillier加密算法对数据进行加密以及进行密文计算，并将数据处理的每个步骤以及处理结果提供到区块链网络，保证数据可溯源，不可篡改；4. the statistical correlation analysis method of privacy data as claimed in claim 1, is characterized in that, in described step 5, data processing mainly encrypts data and carries out ciphertext calculation by Paillier encryption algorithm, and each data processing is carried out. The steps and processing results are provided to the blockchain network to ensure that the data is traceable and cannot be tampered with; 监管者得到参与计算者提交到区块链网络的数据，用自己的私钥Jsk解密其中的密文，看到所有流通的数据，并通过零知识证明验证参与计算者提供给分析者的数据与提供给监管者的数据是一致的，从而实现对数据的监管。The supervisor gets the data submitted by the participating calculators to the blockchain network, decrypts the ciphertext with his own private key Jsk, sees all the circulating data, and verifies the data provided by the participating calculators to the analyst through zero-knowledge proof. The data provided to the regulator is consistent, thereby realizing the supervision of the data. 5.如权利要求1所述隐私数据统计相关性分析方法，其特征在于，所述步骤五中，数据处理为一些常用的统计函数，集中式数据集求和计算如下：5. The privacy data statistical correlation analysis method of claim 1, wherein in the step 5, data processing is some commonly used statistical functions, and the centralized data set summation is calculated as follows: 参与计算者接收到查询命令后，使用公钥对数据进行加密得到密文Epk(mi)，然后将带有查询命令M字段的密文(Epk(mi)，M)提交至区块链网络；After receiving the query command, the participants encrypt the data with the public key to obtain the ciphertext E pk (m i ), and then submit the cipher text (E pk (m i ), M) with the M field of the query command to the district. blockchain network; 通过提前编译好的智能合约，参与计算者可以获取带有查询命令M的密文；Through pre-compiled smart contracts, participants can obtain the ciphertext with the query command M; 参与计算者获得所有带有查询命令M密文数据后，进行密文计算得到Epk＝Epk(m1)+Epk(m2)+……+Epk(mn)，将(Epk，mω)提交至区块链网络，其中mω为监管者给研究分析者的授权信息；After the participants obtain all the ciphertext data with the query command M, the ciphertext calculation is performed to obtain E pk =E pk (m 1 )+E pk (m 2 )+...+E pk (m n ), (E pk (m n ) pk , m ω ) are submitted to the blockchain network, where m ω is the authorization information given by the supervisor to the research analyst; 通过上述过程，可接收到数据的总和，而无需每个参与计算者中的实际数据，在其他统计功能中可能存在多个变量，通过上述过程也可进行计算。Through the above process, the sum of the data can be received without the actual data in each participant of the calculation, and there may be multiple variables in other statistical functions, which can also be calculated through the above process. 6.如权利要求5所述隐私数据统计相关性分析方法，其特征在于，所述平均值计算：6. the privacy data statistical correlation analysis method as claimed in claim 5, is characterized in that, described average value is calculated: 在集中式数据集中可以通过
Figure FDA0002974017530000021
计算平均值，对于分布式数据集通过下列式子进行平均值计算：In centralized datasets can be done via
Figure FDA0002974017530000021
Calculate the mean, for a distributed data set by the following formula:
Figure FDA0002974017530000022
Figure FDA0002974017530000022
 7.如权利要求6所述隐私数据统计相关性分析方法，其特征在于，所述步骤五，具体过程为：7. The statistical correlation analysis method of privacy data as claimed in claim 6, wherein in the step 5, the specific process is: 参与计算者接收到命令后，使用公钥对数据进行加密得到密文
Figure FDA0002974017530000031
，然后将带有查询命令M字段的密文
Figure FDA0002974017530000036
提交至区块链网络，其中M1，M2分别为判断数据和信息的字段与判断参与数据计算者个数的字段；After receiving the command, the participating computer encrypts the data with the public key to obtain the ciphertext
Figure FDA0002974017530000031
, then convert the ciphertext with the M field of the query command
Figure FDA0002974017530000036
Submit to the blockchain network, where M 1 and M 2 are the fields for judging data and information and the fields for judging the number of participants in the data calculation; 通过提前编译好的智能合约参与计算者获取带有查询命令M1，M2的密文；Through the pre-compiled smart contract participants get the ciphertext with the query commands M 1 , M 2 ; 参与计算者获得所有带有查询命令M1，M2密文数据后，进行密文计算得到
Figure FDA0002974017530000033
将(Epk，E(n)，mω)提交至区块链网络，其中mω为监管者给研究分析者的授权信息；After the participant obtains all the ciphertext data with the query command M 1 , M 2 , the ciphertext calculation is performed to obtain
Figure FDA0002974017530000033
Submit (E pk , E(n), m ω ) to the blockchain network, where m ω is the authorization information given by the supervisor to the research analyst; 获得密文后，利用私钥进行解密得到：After obtaining the ciphertext, decrypt it with the private key to get:
Figure FDA0002974017530000034
Figure FDA0002974017530000034
 D(E(n))＝n1+n2+……+ni；D(E(n))=n 1 +n 2 +...+n i ; 最终，数据分析者通过计算
Figure FDA0002974017530000035
分布式数据集的平均值。Ultimately, the data analyst calculates
Figure FDA0002974017530000035
The mean of the distributed dataset. 此处统计相关性函数不局限于求和函数与平均值函数，也包括其他统计函数，求和函数与平均值函数仅为举例说明。The statistical correlation function here is not limited to the summation function and the average value function, but also includes other statistical functions, and the summation function and the average value function are only examples. 8.如权利要求1所述隐私数据统计相关性分析方法，其特征在于，所述步骤六中验证授权信息mω的合法性，即验证分析者的权限是否在有效期内，查询命令是否在授权信息内等等，若所有验证都通过，根据研究分析者的查询命令，区块链网络将提供给分析人员带有部分授权信息mω的密文数据，研究分析者将使用私钥对密文进行解密；8. The method for analyzing the statistical correlation of privacy data as claimed in claim 1, characterized in that, in the step 6, verify the legitimacy of the authorization information m ω , i.e. verify whether the authority of the analyst is within the validity period, and whether the query command is in the authorization If all verifications pass, according to the research analyst's query command, the blockchain network will provide the analyst with ciphertext data with partial authorization information m ω , and the research analyst will use the private key to pair the ciphertext data. decrypt; 步骤一至步骤七中，都采用研究分析者提供的公钥pk进行加密，然后传输到区块链中；区块链上的数据只能由研究分析者进行解密，而且由于监管者的授权，研究分析者对区块链的访问权限限制为特定值，因此不会泄露参与计算者的信息。In steps 1 to 7, the public key pk provided by the research analyst is used for encryption, and then transmitted to the blockchain; the data on the blockchain can only be decrypted by the research analyst, and due to the authorization of the regulator, the research The analyst's access to the blockchain is restricted to a specific value, so no information about the participants in the calculation is revealed. 9.一种接收用户输入程序存储介质，所存储的计算机程序使电子设备执行权利要求1～8任意一项所述隐私数据统计相关性分析方法，包括下列步骤：9. A program storage medium for receiving user input, the stored computer program enables an electronic device to execute the privacy data statistical correlation analysis method according to any one of claims 1 to 8, comprising the following steps: 步骤一，参与者注册身份信息；Step 1: Participants register identity information; 步骤二，根据RSA签名算法，监管者生成认证需要的验证钥与签名钥；Step 2, according to the RSA signature algorithm, the supervisor generates the verification key and the signature key required for authentication; 步骤三，监管者利用Paillier加密系统生成公私钥对，零知识证明参数并在区块链网络公布；Step 3: The supervisor uses the Paillier encryption system to generate a public-private key pair, and the zero-knowledge proof parameters are published on the blockchain network; 步骤四，分析者向区块链网络提交信息查询请求以及授权信息，包括对数据密文计算方式；Step 4, the analyst submits an information query request and authorization information to the blockchain network, including the calculation method of the data ciphertext; 步骤五，参与计算者利用分析者提供的参数pk，ZY与监管者公布的参数，进行数据处理；Step 5, the participating calculators use the parameters pk provided by the analyst, Z Y and the parameters announced by the regulator to process the data; 步骤六，当分析者想要查询需要的信息时，将在步骤二得到的授权信息提供到区块链网络，通过智能合约验证分析者的身份；Step 6, when the analyst wants to query the required information, the authorization information obtained in step 2 is provided to the blockchain network, and the identity of the analyst is verified through the smart contract; 步骤七，研究分析者获取区块链的上的密文数据后，通过私钥进行解密并使用解密后的信息值计算相关的统计相关性函数。Step 7: After the research analyst obtains the ciphertext data on the blockchain, he decrypts it with the private key and uses the decrypted information value to calculate the relevant statistical correlation function. 10.一种存储在计算机可读介质上的计算机程序产品，包括计算机可读程序，供于电子装置上执行时，提供用户输入接口以实施如权利要求1～8所述隐私数据统计相关性分析方法。10. A computer program product stored on a computer-readable medium, comprising a computer-readable program for providing a user input interface to implement the statistical correlation analysis of privacy data according to claims 1 to 8 when executed on an electronic device method.
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