CN114239032A - Multi-party data interaction method and system based on secure multi-party computation - Google Patents
Multi-party data interaction method and system based on secure multi-party computation Download PDFInfo
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- CN114239032A CN114239032A CN202111572675.XA CN202111572675A CN114239032A CN 114239032 A CN114239032 A CN 114239032A CN 202111572675 A CN202111572675 A CN 202111572675A CN 114239032 A CN114239032 A CN 114239032A
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- G06F21/60—Protecting data
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Abstract
The invention relates to a multi-party data interaction method and system based on safe multi-party computation, and belongs to the technical field of big data. In the multi-party data interaction method, the participants distribute the secret sharing data associated with the input data of the participants to each safe multi-party computing node, and then each node computes the secret sharing value and sends the secret sharing value to the requesting party, and the requesting party decrypts the secret sharing value to obtain the computation result. In the process, the safe multi-party computing node provides privacy computing service for data interaction of a participant to a requester, and the requester only obtains a computing result and cannot reveal a privacy data set of the participant to the requester, so that a safe, efficient and reliable multi-party data interaction method and system with privacy protection are constructed.
Description
Technical Field
The invention relates to the technical field of big data, in particular to the technical field of data interaction and sharing, and specifically relates to a multi-party data interaction method and system based on safe multi-party computation.
Background
In the big data era, the data island problem is solved, and the data flow operation is more and more important to the development of the industry. The push information resource share is written to the national file multiple times. The use of big data can make prediction more accurate, and the decision-making is more optimized, and statistics is more accurate. However, in practice, multi-party data sets often belong to different interested parties, and leakage of the data sets will cause loss to data owners. Meanwhile, data users often only care about the 'result' calculated based on the data, but do not care about the data itself. A very natural problem is: can a calculation result based on multiparty data be obtained without revealing privacy data of the parties?
Secure multi-party computing (MPC) techniques solve this problem well. The secure multiparty computation can enable a plurality of participants to perform collaborative computation based on data of each party on the premise of ensuring that private data of the participants are not leaked, namely, the secure multiparty computation is a distributed protocol: n participants A1,A2,…,AnEach having its own secret input x1,x2,…,xnJointly computing a certain n-argument function (funtionality) without the aid of a third party
(y1,y2,…,yn)＝f(x1,x2,…,xn),
And at least two basic properties are satisfied: (1) correctness, i.e. each participant AiAll obtain the correct output y of the present inventioni(ii) a (2) Safety, i.e. either party AiInput x ofiAre not revealed to others (including other parties to the protocol and any other third parties).
It can be seen that, in reality, when a computation problem based on multi-party data is involved, the traditional computation mode is that data is firstly collected and then computed, and obviously, the data privacy of each party is not protected; in the safe multi-party computing mode, all the data are not required to be collected, and the required cooperative computing can be completed through a safe multi-party computing protocol, so that the computing result is ensured to be correct, and the privacy of the data is protected.
The privacy protection requirements of telecom operator data and business data in the banking and finance field are very high. On the one hand, it is desirable to maximize the value of data, and on the other hand, it is desirable that the privacy of sensitive data be protected. The privacy protection computing technology related to MPC has rich application scenes and huge demand space in the application scenes.
Disclosure of Invention
The invention aims to establish a safe, efficient and reliable privacy protection multi-party data interaction method and system based on safe multi-party calculation and related cryptographic technology.
In order to achieve the above object, the multiparty data interaction method based on secure multiparty computation of the present invention comprises the following steps:
(1) at least one participant distributes secret sharing data associated with the local input data to each secure multiparty computing node;
(2) each safe multi-party computing node obtains a secret sharing value according to the obtained secret sharing data;
(3) each of said secure multi-party computing nodes sending said secret sharing value to at least one requesting party;
(4) and the requester decrypts the secret sharing value to obtain a calculation result.
In the secure multiparty data interaction method based on multiparty computing, the step (1) specifically comprises:
(11) at least one participant calls the local input data participating in interaction from the local database through the PC terminal;
(12) the participator divides the local input data in a secure secret sharing mode to form a plurality of secret sharing data;
(13) distributing each of said shares of secret sharing data to each of said secure multi-party computing nodes over a secure channel.
In the multiparty data interaction method based on safe multiparty computation, the safe secret sharing mode is any one or combination of multiple modes of arithmetic sharing, logic sharing and Yao sharing.
In the multiparty data interaction method based on secure multiparty computing, the step (2) is specifically as follows:
and each safe multi-party computing node executes a safe multi-party computing protocol according to the obtained secret sharing data, and obtains a sharing value of the calculation result of the objective function as the secret sharing value of each node.
In the multiparty data interaction method based on the secure multiparty computation, when the executing secure multiparty computation protocol is shared based on the secret sharing data summation, each node completes computation locally; when the executing secure multi-party computing protocol is the sharing of the product based on the secret sharing data, the nodes communicate with each other, and the executing secure multi-party computing protocol realizes the product sharing computation.
In the multiparty data interaction method based on secure multiparty computing, the step (3) is specifically as follows:
and the various safe multi-party computing nodes send the secret sharing value obtained by the respective computation to the requesting party through a safe channel.
The invention also provides a multi-party data interaction system based on safe multi-party computation, which comprises: at least one requesting party, at least one participating party, and a plurality of secure multi-party computing nodes, said participating party distributing secret sharing data associated with the local input data to each of said secure multi-party computing nodes; each safe multi-party computing node obtains a secret sharing value according to the obtained secret sharing data; and sending said secret shared value to said requesting party; and the requester decrypts the secret sharing value to obtain a calculation result.
By adopting the secure multi-party computing-based multi-party data interaction method and system, the participants distribute the secret sharing data associated with the input data of the participants to each secure multi-party computing node, and then each node computes the secret sharing value and sends the secret sharing value to the requesting party, and the requesting party decrypts the secret sharing value to obtain the computing result. In the process, the safe multi-party computing node provides privacy computing service for data interaction of a participant to a requester, and the requester only obtains a computing result and cannot reveal a privacy data set of the participant to the requester, so that a safe, efficient and reliable multi-party data interaction method and system with privacy protection are constructed.
Drawings
FIG. 1 is a flow chart illustrating the steps of a secure multiparty computing based multiparty data interaction method of the present invention.
FIG. 2 is a schematic diagram of a secure multiparty computing-based multiparty data interaction system according to the present invention.
FIG. 3 is a schematic diagram illustrating the operation principle of the secure multiparty computing based multiparty data interaction system of the present invention.
Fig. 4 is a schematic diagram of data segmentation performed on input data by a participant in the present invention.
Fig. 5 is a schematic diagram of a participant securely sharing a partitioned share to an MPC node in the present invention.
FIG. 6 is a schematic diagram of a multi-party computing protocol MPC adopted by the present invention.
Fig. 7 is a schematic diagram of a data secret sharing conversion scheme employed by the present invention.
Fig. 8 is a schematic diagram of a secure output process employed by the present invention.
Detailed Description
In order to clearly understand the technical contents of the present invention, the following examples are given in detail.
Referring to fig. 1, a flow chart of steps of a multi-party data interaction method based on secure multi-party computing according to the present invention is shown.
In one embodiment, the secure multiparty computing based multiparty data interaction method, as shown in fig. 1, comprises the following steps:
(1) at least one participant distributes secret sharing data associated with the local input data to each secure multiparty computing node;
(2) each safe multi-party computing node obtains a secret sharing value according to the obtained secret sharing data;
(3) each of said secure multi-party computing nodes sending said secret sharing value to at least one requesting party;
(4) and the requester decrypts the secret sharing value to obtain a calculation result.
In a more preferred embodiment, the step (1) specifically comprises:
(11) at least one participant calls the local input data participating in interaction from the local database through the PC terminal;
(12) the participator divides the input data of the party in a secure secret sharing mode to form a plurality of secret sharing data, wherein the secure secret sharing mode can be any one of arithmetic sharing, logic sharing and Yao sharing, and can also be the combination of the multiple sharing modes;
(13) distributing each of said shares of secret sharing data to each of said secure multi-party computing nodes over a secure channel.
In another more preferred embodiment, the step (2) is specifically:
and each safe multi-party computing node executes a safe multi-party computing protocol according to the obtained secret sharing data, and obtains a sharing value of the calculation result of the objective function as the secret sharing value of each node. When the executing secure multiparty computing protocol is shared based on the 'sum' of the secret sharing data, each node completes computation locally; when the executing secure multi-party computing protocol is the sharing of the product based on the secret sharing data, the nodes communicate with each other, and the executing secure multi-party computing protocol realizes the product sharing computation.
In a more preferred embodiment, the step (3) is specifically: and the various safe multi-party computing nodes send the secret sharing value obtained by the respective computation to the requesting party through a safe channel.
The invention also provides a multi-party data interaction system based on secure multi-party computing, which comprises: at least one requesting party, at least one participating party, and a plurality of secure multi-party computing nodes, said participating party distributing secret sharing data associated with the local input data to each of said secure multi-party computing nodes; each safe multi-party computing node obtains a secret sharing value according to the obtained secret sharing data; and sending said secret shared value to said requesting party; and the requester decrypts the secret sharing value to obtain a calculation result.
In practical application, the structure of the multi-party data interaction system based on secure multi-party computing of the present invention is shown in FIG. 2. Take the telecom operator as the requesting party (needing to obtain the calculation result) and the banking financial institution as the participating party (providing data). The method comprises the following steps that a participant calls input data of the participant to be calculated from a database through a PC (personal computer) end, and distributes the input data to each MPC (multimedia personal computer) node through a secure channel in a secret sharing mode; and the MPC protocol is executed among the MPC nodes, and the secure calculation is completed on the basis of secret shared data. After the safety calculation is completed, each MPC point has a secret shared value of the calculation result, but not the calculation result per se; each MPC node finally returns the secret shared value of the computation result to the computation requester (i.e. the one that needs to compute the result) through the secure channel, and the computation requester decrypts and recovers the final computation result, and the overall operation principle is as shown in fig. 3.
The multi-party data interaction based on the safe multi-party calculation of the invention is realized by the following steps:
(1) creation and management
Including creating new projects, as well as managing established projects, inviting members to participate in projects, etc.
(2) Data distribution
Each party uploads the input data as required, and the input data of each party is divided in a secure secret sharing manner as shown in fig. 4. The split different shares are then distributed over a secure channel to each MPC node as shown in fig. 5. The data sharing mode comprises arithmetic sharing, Boolean sharing and Yao sharing. Since each node owns only a certain share of the data, the privacy of the incoming data is well protected.
(3) Secure computing
After the data shares are uploaded to the MPC nodes, each node only has the share of the data, not the real data itself, and therefore, between the MPC nodes, a secure multiparty computation protocol based on the share as shown in fig. 6 needs to be executed. The method aims to obtain the shared value of the calculation result of the objective function by each node after the calculation is finished. When the shared data is used for obtaining the 'sum' based on the shared data, the calculation can be completed only by locally using each node; however, when the "product" is shared, the MPC nodes need to communicate with each other, and a shared multiplexing scheme is implemented to realize the "product" shared computation. For some more complex operations, such as model training of a neural network, due to the non-linear function involved, the non-linear function can be converted into an approximate logic function for processing, which requires high-speed conversion of data secret sharing among arithmetic sharing, logic sharing and yao sharing to improve the efficiency of data processing, and the sharing conversion scheme is shown in fig. 7.
(4) Secure output
After the multi-party calculation process is completed, each MPC node has the secret shared value of the final calculation result, and when the user requests the calculation result, as shown in fig. 7, each MPC node sends the secret shared value to the user through a secure channel, and the user decrypts and recovers the final technical result, thereby well protecting the privacy of the output data.
The core technology of the invention comprises cryptography, privacy protection, safe multiparty computation and the like, and the core technology comprises the technologies of data encryption and decryption, Hash algorithm, secret sharing (arithmetic sharing, logic sharing and Yao sharing), Yao confusion circuit, careless transmission (OT), zero knowledge proof, homomorphic encryption, searchable encryption and the like.
The invention has the advantage that the invention is a decentralized and scalable distributed architecture. By adopting an MPC distributed architecture and secret sharing calculation, the model can be trained on the basis of secret sharing data, and secret sharing of the model is sent to a user for deployment. The system is in a distributed architecture, calculation is carried out on MPC nodes, the confidentiality of communication is guaranteed through an OT protocol when interaction among the nodes is achieved, and calculation is carried out when the nodes are in agreement without being controlled by a central node. Secondly, only one round of communication is needed to realize safe privacy calculation. Encrypted data retrieval is achieved by uploading data queries and search criteria using a secret sharing approach, storing the processing results in a secret sharing approach, and distributed secret computing. Because the information transmission between the user and the MPC node is carried out through a secure channel, the data is stored on the server in a distributed manner through a secret sharing mode, and the intermediate data is always in a secret sharing state in the whole process of the node executing the MPC protocol, the privacy of the data is effectively guaranteed. Through distributed secret sharing computation, the security statistics of data can be realized. Meanwhile, the package of the bottom secret sharing calculation is adopted to provide API interface calling of basic calculation, and the rapid development and application of the upper layer can be realized.
By adopting the secure multi-party computing-based multi-party data interaction method and system, the participants distribute the secret sharing data associated with the input data of the participants to each secure multi-party computing node, and then each node computes the secret sharing value and sends the secret sharing value to the requesting party, and the requesting party decrypts the secret sharing value to obtain the computing result. In the process, the safe multi-party computing node provides privacy computing service for data interaction of a participant to a requester, and the requester only obtains a computing result and cannot reveal a privacy data set of the participant to the requester, so that a safe, efficient and reliable multi-party data interaction method and system with privacy protection are constructed.
In this specification, the invention has been described with reference to specific embodiments thereof. It will, however, be evident that various modifications and changes may be made thereto without departing from the broader spirit and scope of the invention. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.
Claims (7)
1. A multi-party data interaction method based on secure multi-party computing is characterized by comprising the following steps:
(1) at least one participant distributes secret sharing data associated with the local input data to each secure multiparty computing node;
(2) each safe multi-party computing node obtains a secret sharing value according to the obtained secret sharing data;
(3) each of said secure multi-party computing nodes sending said secret sharing value to at least one requesting party;
(4) and the requester decrypts the secret sharing value to obtain a calculation result.
2. The secure multiparty computing based multiparty data interaction method according to claim 1, wherein said step (1) comprises:
(11) at least one participant calls the local input data participating in interaction from the local database through the PC terminal;
(12) the participator divides the local input data in a secure secret sharing mode to form a plurality of secret sharing data;
(13) distributing each of said shares of secret sharing data to each of said secure multi-party computing nodes over a secure channel.
3. The secure multiparty data interaction method based on secure multiparty computing according to claim 2, wherein said secure secret sharing means is any one or combination of arithmetic sharing, logic sharing and sharing with Yao.
4. The secure multiparty computing based multiparty data interaction method according to claim 1, wherein said step (2) is specifically:
and each safe multi-party computing node executes a safe multi-party computing protocol according to the obtained secret sharing data, and obtains a sharing value of the calculation result of the objective function as the secret sharing value of each node.
5. The secure multiparty computing based multiparty data interaction method of claim 4, wherein each of said nodes performs computation locally when said executing secure multiparty computing protocol is a sharing based on said secret sharing data summing; when the executing secure multi-party computing protocol is the sharing of the product based on the secret sharing data, the nodes communicate with each other, and the executing secure multi-party computing protocol realizes the product sharing computation.
6. The secure multiparty computing based multiparty data interaction method according to claim 1, wherein said step (3) is specifically:
and the various safe multi-party computing nodes send the secret sharing value obtained by the respective computation to the requesting party through a safe channel.
7. A secure multiparty computing based multiparty data interaction system, the system comprising: at least one requesting party, at least one participating party, and a plurality of secure multi-party computing nodes, said participating party distributing secret sharing data associated with the local input data to each of said secure multi-party computing nodes; each safe multi-party computing node obtains a secret sharing value according to the obtained secret sharing data; and sending said secret shared value to said requesting party; and the requester decrypts the secret sharing value to obtain a calculation result.
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| CN114448631A (en) * | 2022-04-07 | 2022-05-06 | 华控清交信息科技(北京)有限公司 | Multi-party security computing method, system and device for multi-party security computing |
| CN114513304A (en) * | 2022-04-19 | 2022-05-17 | 浙商银行股份有限公司 | Decentralized secure multiparty privacy summation calculation method and system |
| CN114584396A (en) * | 2022-04-25 | 2022-06-03 | 北京原语科技有限公司 | Data conversion method of multi-party secure computing protocol |
| CN114884675A (en) * | 2022-04-29 | 2022-08-09 | 杭州博盾习言科技有限公司 | Multi-party privacy intersection method, device, equipment and medium based on bit transmission |
| CN115080615A (en) * | 2022-06-07 | 2022-09-20 | 蚂蚁区块链科技(上海)有限公司 | Data query method and device based on multi-party security calculation |
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| CN114448631B (en) * | 2022-04-07 | 2022-06-07 | 华控清交信息科技(北京)有限公司 | Multi-party security computing method, system and device for multi-party security computing |
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| CN115455488A (en) * | 2022-11-15 | 2022-12-09 | 哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院) | Secret database query method and device based on secret copy sharing |
| CN115455488B (en) * | 2022-11-15 | 2023-03-28 | 哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院) | Secret database query method and device based on secret copy sharing |
| CN116248266A (en) * | 2022-12-16 | 2023-06-09 | 北京海泰方圆科技股份有限公司 | Secure multiparty computing method and system based on secret sharing |
| CN116248266B (en) * | 2022-12-16 | 2023-11-14 | 北京海泰方圆科技股份有限公司 | Secure multiparty computing method and system based on secret sharing |
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