Multi-party secure multiplication calculation algorithm based on trusted blockchain

Abstract

The present invention relates to the technical field of blockchain, and in particular to a multi-party secure multiplication calculation algorithm based on a trusted blockchain, comprising an interconnected server, a client and a trusted node, and adopting a hash encryption mechanism to protect and chain the data of an institution authenticated by the blockchain, comprising the following method: step S1: in the server, splitting matrix data X into matrix data X0+X1, and sending the matrix data X1 to the client; step S2: in the client, splitting matrix data Y into matrix data Y0+Y1, and sending the matrix data Y1 to the server; step S3: the trusted node randomly generates matrix data U, V, Z, wherein the matrix data Z=U*V, splits the matrix data U into matrix data U0+U1, splits the matrix data V into matrix data V0+V1, splits the matrix data Z into matrix data Z0+Z1, and sends the matrix data U0, V0, Z0 to the server, and sends the matrix data U1, V1, Z1 to the client.

Description

[Technical field]

[0001] The present invention relates to the field of blockchain technology, and in particular to a multi-party secure multiplication calculation algorithm based on a trusted blockchain. [Background technology]

[0002] Some manufacturers' products on the market directly transmit and calculate the data of each participant in plain text, which poses many risks in information security, privacy protection, and mutual data access rights. At the same time, since user data needs to be protected from privacy, it is not easy to share data between enterprises, resulting in data silos.

[0003] Therefore, the prior art is insufficient and needs to be improved. [Summary of the invention]

[0004] In order to overcome the above-mentioned technical problems, the present invention provides a multi-party secure multiplication calculation algorithm based on a trusted blockchain.

[0005] The solution to the technical problem of the present invention is to provide a multi-party secure multiplication calculation algorithm based on a trusted blockchain, including an interconnected server, a client and a trusted node, and a hash encryption mechanism to protect the data of the organization authenticated by the blockchain and upload it to the chain, including the following methods:

[0006] Step S1: In the server, the matrix data X is split into matrix data X0+X1, and the matrix data X1 is sent to the client;

[0007] Step S2: In the client, the matrix data Y is split into matrix data Y0+Y1, and the matrix data Y1 is sent to the server;

[0008] Step S3: The trusted node randomly generates matrix data U, V, and Z, where matrix data Z=U*V, splits matrix data U into matrix data U0+U1, splits matrix data V into matrix data V0+V1, splits matrix data Z into matrix data Z0+Z1, and sends matrix data U0, V0, and Z0 to the server, and sends matrix data U1, V1, and Z1 to the client;

[0009] Step S4: In the server, set matrix data E0 and F0, wherein matrix data E0=X0-U0, F0=Y0-V0, and send matrix data E0 and F0 to the client;

[0010] Step S5: In the client, set matrix data E1, F1, wherein matrix data E1 = X1-U1, F1 = Y1-V1, and send matrix data E1, F1 to the server;

[0011] Step S6: In the server, set matrix data C0, where matrix data C0 = X0*F0+E0*Y0+Z0, and send matrix data C0 to the client;

[0012] Step S7: In the server, set matrix data C1, wherein matrix data C1 = -E1*F1+X1*F1+E1*Y1+Z1, and send matrix data C1 to the client;

[0013] Step S8: Set matrix data C, wherein matrix data C=C0+C1, ​​and matrix data C is the result of multiplying matrix data X and Y.

[0014] Compared with the prior art, the multi-party secure multiplication calculation algorithm based on the trusted blockchain of the present invention has the following advantages:

[0015] By setting up clients, servers and trusted nodes, the overall computing efficiency is improved, and through multi-party secure computing, the protection of user data privacy is achieved while also realizing encrypted data transmission. The respective data sets are sent to the common authentication party to achieve the effect of secure computing, sharing the data computing workload of the client and server, which is conducive to reducing time waste, speeding up the speed of data on the chain, and improving the user experience.

Brief Description of the Drawings

[0016] Figure 1 It is a specific flow chart of the multi-party secure multiplication calculation algorithm based on the trusted blockchain of the present invention. [Specific implementation method]

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] See also Figure 1 The present invention provides a multi-party secure multiplication calculation algorithm based on a trusted blockchain, including an interconnected server, a client, and a trusted node, and adopts a hash encryption mechanism to protect the data of the organization authenticated by the blockchain and upload it to the chain, including the following steps:

[0019] Step S1: In the server, the matrix data X is split into matrix data X0+X1, and the matrix data X1 is sent to the client;

[0020] Step S2: In the client, the matrix data Y is split into matrix data Y0+Y1, and the matrix data Y1 is sent to the server;

[0021] Step S3: The trusted node randomly generates matrix data U, V, and Z, where matrix data Z=U*V, splits matrix data U into matrix data U0+U1, splits matrix data V into matrix data V0+V1, splits matrix data Z into matrix data Z0+Z1, and sends matrix data U0, V0, and Z0 to the server, and sends matrix data U1, V1, and Z1 to the client;

[0022] Step S4: In the server, set matrix data E0 and F0, wherein matrix data E0=X0-U0, F0=Y0-V0, and send matrix data E0 and F0 to the client;

[0023] Step S5: In the client, set matrix data E1, F1, wherein matrix data E1 = X1-U1, F1 = Y1-V1, and send matrix data E1, F1 to the server;

[0024] Step S6: In the server, set matrix data C0, where matrix data C0 = X0*F0+E0*Y0+Z0, and send matrix data C0 to the client;

[0025] Step S7: In the server, set matrix data C1, wherein matrix data C1 = -E1*F1+X1*F1+E1*Y1+Z1, and send matrix data C1 to the client;

[0026] Step S8: Set matrix data C, wherein matrix data C=C0+C1, ​​and matrix data C is the result of multiplying matrix data X and Y.

[0027] Compared with the prior art, the multi-party secure multiplication calculation algorithm based on the trusted blockchain of the present invention has the following advantages:

[0028] By setting up clients, servers and trusted nodes, the overall computing efficiency is improved, and through multi-party secure computing, the protection of user data privacy is achieved while also realizing encrypted data transmission. The respective data sets are sent to the common authentication party to achieve the effect of secure computing, sharing the data computing workload of the client and server, which is conducive to reducing time waste, speeding up the speed of data on the chain, and improving the user experience.

[0029] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any modifications, equivalent substitutions and improvements made within the concept of the present invention should be included in the patent protection scope of the present invention.

Claims

1. A multi-party secure multiplication calculation algorithm based on a trusted blockchain, characterized by: It includes interconnected servers, clients and trusted nodes, and uses hash encryption mechanism to protect the data of blockchain-certified institutions on the chain, including the following methods: Step S1: In the server, the matrix data X is split into matrix data X0+X1, and the matrix data X1 is sent to the client; Step S2: In the client, the matrix data Y is split into matrix data Y0+Y1, and the matrix data Y1 is sent to the server; Step S3: The trusted node randomly generates matrix data U, V, and Z, where matrix data Z=U*V, splits matrix data U into matrix data U0+U1, splits matrix data V into matrix data V0+V1, splits matrix data Z into matrix data Z0+Z1, and sends matrix data U0, V0, and Z0 to the server, and sends matrix data U1, V1, and Z1 to the client; Step S4: In the server, set matrix data E0 and F0, wherein matrix data E0=X0-U0, F0=Y0-V0, and send matrix data E0 and F0 to the client; Step S5: In the client, set matrix data E1, F1, wherein matrix data E1 = X1-U1, F1 = Y1-V1, and send matrix data E1, F1 to the server; Step S6: In the server, set matrix data C0, where matrix data C0 = X0*F0+E0*Y0+Z0, and send matrix data C0 to the client; Step S7: In the server, set matrix data C1, wherein matrix data C1 = -E1*F1+X1*F1+E1*Y1+Z1, and send matrix data C1 to the client; Step S8: Set matrix data C, wherein matrix data C=C0+C1, ​​and matrix data C is the result of multiplying matrix data X and Y.

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