Secure Computation Polynomial Sharding for Accurate Feature Intersections
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Solution Overview
Problem
Existing secure multi-party computation methods fail to guarantee the accuracy of feature shards in scenarios where the first identification set is not a subset of the second identification set, leading to inaccurate results in tasks like SQL queries and machine learning model training.
Innovation Solution
A method is introduced where parties involved in secure computation convert the problem of sharding feature intersections into polynomial evaluation, using degree reduction and evaluation processes to ensure accurate feature shards by generating a target identification set based on synchronized index numbers, reducing communication volume and avoiding data leakage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing secure multi-party computation methods are used to compute feature intersections, then data privacy is maintained, but accuracy of feature shards cannot be guaranteed when the first identification set is not a subset of the second identification set
Solution Approach 1:
The patent introduces an intermediary polynomial evaluation mechanism to bridge the gap between secure computation and accurate feature shard generation. By converting the feature intersection problem into polynomial evaluation, the system achieves both privacy preservation and accuracy without directly exposing identification sets
Solution Approach 2:
The patent transforms the computation parameters from direct identification set operations to polynomial-based evaluations. This parameter transformation allows the system to work with algebraic structures that preserve accuracy while maintaining security, particularly through the use of polynomial coefficients and evaluation points
2Loss of energy
If direct computation of feature intersections is performed without polynomial transformation, then computation is simpler, but communication volume increases and data leakage risks arise
Solution Approach 1:
The patent replaces direct set intersection operations with polynomial evaluation mechanisms. This substitution transforms the computational approach from combinatorial set operations to algebraic polynomial arithmetic, reducing communication overhead while maintaining computational correctness
Solution Approach 2:
The patent creates polynomial representations (copies) of the identification sets that preserve the necessary computational properties without exposing the original data. These polynomial copies enable secure computation while minimizing direct data exchange between parties
Data Source
AI summary
A method of data processing for secure computation, a storage medium, and an electronic device are provided. The method includes: performing a data processing process based on a target protocol with the second party based on the first identification set, so that the second party obtains at least a first index number of an intersection of the first identification set and the second identification set in the first identification set; obtaining a first polynomial corresponding to each individual dimension of at least some dimensions in the h-dimensional features; computing values of the first polynomial on at least part of identifications in a target identification set with the second party to obtain a first shard of the values; and performing a target data processing task based at least on the first shard.