Parallel Secret Sharing for Polynomial Evaluation
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Solution Overview
Problem
In the context of cooperative data processing models, determining the value of a polynomial expression while protecting data privacy is inefficient due to the need for multiple interactions between data parties, which can lead to time-consuming network interactions and reduced efficiency.
Innovation Solution
A method and apparatus for secretly sharing the values of polynomial expression terms between data parties using a secret sharing algorithm, allowing parallel determination of shares without leaking service data, thereby reducing interactions and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional sequential secret sharing is used to determine polynomial expression values, then data privacy is protected, but the number of interactions and time consumption increase
Solution Approach 1:
The patent segments the polynomial expression into multiple terms, where each term is processed independently through parallel secret sharing. This allows different terms to be evaluated simultaneously by different data parties, reducing the total time while maintaining privacy through secure multi-party computation for each term.
Solution Approach 2:
The patent transitions from sequential processing to parallel processing by introducing a dimensional aspect of simultaneous computation. Multiple data parties perform secret sharing operations in parallel across different terms of the polynomial expression, effectively adding a time dimension to the computation process.
2Measurement precision
If multiple interactions are performed between data parties to determine polynomial values, then computation accuracy is maintained, but network interaction time increases
Solution Approach 1:
The patent merges multiple sequential interaction steps into a single parallel operation. By combining the secret sharing of different polynomial terms into a unified parallel process, data parties can compute multiple terms simultaneously, reducing network interaction time while maintaining computational accuracy through coordinated parallel computation.
Solution Approach 2:
The patent ensures continuous useful action by performing secret sharing operations for multiple polynomial terms simultaneously rather than sequentially. This continuous parallel processing eliminates idle time between interactions and maintains computation accuracy through ongoing coordinated calculations across all terms.
Data Source
AI summary
This disclosure relates to secret sharing data exchange for generating a data processing model. In some aspects, first data party device determines respective values of first coefficients based on a first share of service data. The first coefficients are corresponding coefficients of respective target variables in different terms of a polynomial expression and the target variables are variables that are in the polynomial expression and associated with the first share of the service data. A second data party device determines respective values of second coefficients based on a second share of the service data. The second coefficients include coefficients other than the first coefficients in the different terms of the polynomial expression. The first data party device secretly shares respective values of the different terms in the polynomial expression in parallel based on the respective values of the first coefficients.