Secure Multi-Party Computation Data Processing via Logical-Arithmetic Conversion
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Solution Overview
Problem
Current data transmission methods in secure multi-party computation (MPC) over public networks are inefficient, requiring the transmission of multiple data components, which puts pressure on the network and is not optimized for reducing data amount.
Innovation Solution
The method involves the data provider splitting private data into logical components and each MPC computation party converting these components into arithmetic components, reducing the data amount transmitted by performing zero-sharing and arithmetic sharing processes, thereby minimizing network pressure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the data provider transmits multiple data components to each MPC computation party, then the MPC processing can be performed securely, but the data amount transmitted over the public network increases, putting pressure on transmission
Solution Approach 1:
The patent segments the data components into two types: logical components (transmitted over public network) and arithmetic components (computed locally). Each MPC computation party receives only the logical component from the data provider, then converts it to an arithmetic component through local computation. This segmentation reduces the transmitted data amount while maintaining security, as the critical arithmetic operations are performed locally rather than requiring transmission of all data components.
Solution Approach 2:
The patent introduces logical components as intermediaries between the data provider and MPC computation parties. Instead of transmitting arithmetic components directly, the data provider transmits logical components that serve as intermediaries. Each MPC computation party then converts these logical components to arithmetic components through local computation. This intermediary approach reduces network transmission pressure while enabling secure MPC processing.
2Productivity
If the data provider transmits all data components to each MPC computation party, then the MPC computation can proceed, but the network transmission pressure increases significantly
Solution Approach 1:
The patent segments the data transmission process into two stages: (1) The data provider transmits only logical components to each MPC computation party over the public network; (2) Each MPC computation party converts the received logical component to an arithmetic component through local computation. This segmentation dramatically reduces network transmission pressure while maintaining full MPC computation capability, as the heavy arithmetic operations are performed locally rather than requiring large data transmissions.
Solution Approach 2:
The patent enables each MPC computation party to perform self-service by converting the received logical component to an arithmetic component through local computation. Instead of receiving pre-computed arithmetic components from the data provider, each computation party independently performs the conversion using its own computational resources. This self-service approach eliminates the need for the data provider to transmit all data components, significantly reducing network transmission pressure while maintaining computation capability.
Data Source
AI summary
Data processing methods, apparatuses, and computer-readable media are applied to a system including a data provider and N secure multi-party computation (MPC) computation parties. N is an integer greater than 3. In an example method, each MPC computation party obtains a first data component from a data message sent by the data provider. The first data component is a part of a plurality of data components obtained after the data provider splits private data, and the first data component is a logical component. Then, the first data component is converted from the logical component to an arithmetic component, to obtain a second data component, so as to perform MPC processing.