Secret Sharing Inconsistency Detection via Checksum Segmentation
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Solution Overview
Problem
Existing secret sharing technologies face inefficiencies in reducing communication traffic volume when detecting inconsistencies in shares, particularly in handling large data sets.
Innovation Solution
The method involves generating public random numbers, calculating a common random number, and using checksums to detect inconsistencies in shares through a series of steps that minimize communication traffic, including generating random number distributed values and judging values, and restoring shares to identify potential inconsistencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If existing secret sharing technology is used to detect inconsistencies in shares, then the number of communications stages is reduced, but the volume of communications traffic remains large when handling large data
Solution Approach 1:
The patent segments the inconsistency detection process into multiple phases: preprocessing phase where shares are divided and checksums are calculated locally, and main detection phase where only necessary shares are transmitted. This segmentation allows the system to reduce communication traffic volume by performing local calculations before the main detection phase, thereby resolving the contradiction between reducing communication stages and reducing traffic volume.
Solution Approach 2:
The patent performs preliminary actions by calculating checksums and preparing share divisions before the main inconsistency detection process. Each participant pre-calculates checksums for their shares and prepares the necessary data structures, so that during the main detection phase, only minimal communication is required. This preliminary action significantly reduces the volume of communications traffic needed for inconsistency detection.
2Measurement precision
If shares are transmitted to another calculation entity for inconsistency detection, then detection accuracy is improved, but communication security and data privacy are compromised
Solution Approach 1:
The patent implements self-service by enabling each calculation entity to perform inconsistency detection using only their own shares and the publicly available checksums. Each participant independently calculates the consistency of their share against the expected value derived from public checksums, eliminating the need to transmit shares to other entities. This maintains both detection accuracy and data privacy.
Solution Approach 2:
The patent introduces public checksums as an intermediary mechanism that enables inconsistency detection without direct share transmission. The checksums serve as a mediator that allows each participant to verify their share's consistency using only public information and their local shares, thereby maintaining security and privacy while achieving accurate detection.
Data Source
AI summary
An inconsistency in shares is detected with a small volume of communications traffic. n inconsistency detecting devices generate random numbers si and make the random numbers si public. The n inconsistency detecting devices generate a common random number s which is the sum total of the random numbers s0, . . . , sn−1. The n inconsistency detecting devices calculate shares [c]i. The n inconsistency detecting devices generate shares [r]i, each of which would become a random number r by reconstruction. The n inconsistency detecting devices calculate shares [d]i, each of which would become a judgment value d by reconstruction. One inconsistency detecting device receives shares [d]1, . . . , [d]n−1 from n−1 inconsistency detecting devices. The one inconsistency detecting device restores n−k shares [d]′k, . . . , [d]′n−1 from k shares [d]0, . . . , [d]k−1. The one inconsistency detecting device judges, for j=k, . . . , n−1, whether or not a share [d]j and a share [d]′j coincide with each other.