Secure multi-party multiplication method and system

A multiplication operation and multi-party technology, applied in the field of distributed joint computing, can solve problems such as low efficiency, impossible sharing of medical data and bank personal credit data, etc., achieve less communication overhead, easy parallel computing, and improve computing efficiency Effect

Active Publication Date: 2021-02-19
GUIZHOU EDUCATION UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, medical data and bank personal credit data cannot be shared to public cloud servers due to regulations and liability avoidance, and can only be stored in local servers of each institution
[0004] However, when the existing solutions perform multiplication calculations, each party needs to in...

Method used

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  • Secure multi-party multiplication method and system
  • Secure multi-party multiplication method and system
  • Secure multi-party multiplication method and system

Examples

Experimental program
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Embodiment 1

[0048] The invention discloses a safe multi-party multiplication operation method, including:

[0049] Step S1. Determine the number of multiplication sharing participants, and abstract the communication and calculation process of the shared components into a shared bipartite graph.

[0050] refer to figure 1 , with n participants P greater than or equal to 4 1 ,P 2 …P n Calculate z=xy together, share x and y with n parties, P i have (x i ,y i ); share x i Form a set A={x i}, share y i Form a set B={y i}, i=1...n, take A and B as the vertex set in graph G; take each summation component x i the y j As the corresponding edge (x i ,y j ), i, j=1...n; data sharing bipartite graph G=(V,{E}), where E={(x i ,y j )}, side (x i ,y j ) corresponding to the weight x i the y j , V={A∪B}, sum the weights corresponding to all edges to get:

[0051] z=xy=(x 1 +x 2 +…+x n )(y 1 +y 2 +…+y n ) = ∑ i,j x i the y j .

[0052] Step S2, dividing the shared bipartite ...

Embodiment 2

[0084] This embodiment discloses a secure multi-party multiplication system, which includes a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, it implements the corresponding functions of the above embodiments. Method steps.

[0085] To sum up, the safe multi-party multiplication method and system respectively disclosed in the above-mentioned embodiments of the present invention have the following beneficial effects:

[0086] Based on the adjacency matrix of the present invention, the following constraints are satisfied:

[0087] E. 1 ∪E 2 ∪…∪E n =E

[0088] That is: all subgraphs can form the original bipartite graph, that is to say, after each participant calculates the multiplication share according to the division, the sum of all shares is the result of multiplication; and at the same time satisfy:

[0089]

[0090] That is: each subgraph is independent and has no commo...

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Abstract

The invention relates to the technical field of distributed joint computing, and discloses a secure multi-party multiplication method and system, so as to realize repeated sharing through a round of optimal communication. The method comprises the following steps that: based on a multiplication shared component calculation protocol of data sharing bipartite graph division, bipartite graph modelingis carried out on data sharing for multiplication calculation, and division of multiplication result shared components is represented by an adjacent matrix, so that n participants can locally calculate multiplication shared components only by one round of communication.

Description

technical field [0001] The invention relates to the technical field of distributed joint computing, in particular to a safe multi-party multiplication operation method and system. Background technique [0002] Secure multi-party computation MPC (Multy-party computation) is an important cryptographic technology, which can perform distributed joint computation among multiple distrusting parties without disclosing the private data of each party, and finally Parties may have the plaintext result of a function agreed to be computed. With the development of big data and artificial intelligence, how to realize efficient data utilization and collaborative computing between multiple network nodes under the premise of protecting data privacy has become a hot research issue. The main thing that affects the efficiency of secure multi-party computing is the overhead of computing shared multiplication among multiple participants. [0003] At present, the latest high-throughput secure mu...

Claims

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Application Information

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IPC IPC(8): G06F17/16G06F17/18
CPCG06F17/16G06F17/18Y02D10/00
Inventor 徐艺马敏耀刘卓
Owner GUIZHOU EDUCATION UNIV
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