Line-Point Zero-Knowledge Proof System for Scalable Verification
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Solution Overview
Problem
Existing zero-knowledge proof systems face inefficiencies in computation, communication, and storage overhead, limiting their scalability and adoption for large-scale verification tasks.
Innovation Solution
A secure multiparty computation protocol is employed between two computing devices to verify arithmetic circuit satisfiability using private information, where a first computing device inputs a random data element and receives an affine linear function evaluation from a second computing device, allowing for privacy-preserving verification with low overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing zero-knowledge proof systems are used for verification, then privacy-preserving verification is achieved, but computation, communication, and storage overhead increases significantly
Solution Approach 1:
The patent segments the verification process into two distinct roles: a prover computing device that generates proof data structures, and a verifier computing device that validates them. This segmentation allows complex zero-knowledge proof operations to be distributed, with the computationally intensive generation phase separated from the lighter validation phase, thereby reducing overall system overhead while maintaining privacy guarantees
Solution Approach 2:
The patent uses proof data structures that are generated once by the prover and then copied/verified multiple times by the verifier without requiring repeated access to the original private information. This copying mechanism enables efficient verification of the same proof instance multiple times, reducing communication and computation overhead for repeated verification tasks
2Reliability
If existing zero-knowledge proof systems are implemented for large verification tasks, then verification capability is provided, but scalability is limited due to overhead
Solution Approach 1:
The patent changes key parameters of the verification process by using optimized proof data structures with specific mathematical properties (such as succinct representations and efficient hashing). These parameter changes enable the verification complexity to scale more favorably with input size, allowing large verification tasks to be handled efficiently while maintaining high probability of correctness
Data Source
AI summary
Non-transitory computer readable storage mediums have instructions executed by processors to access a first random data element at a first computing device. A first vector and a second vector are generated at a second computing device. A communication channel is utilized to execute a secure multiparty computation protocol between the first computing device and the second computing device. The first computing device alternately identifies a polynomial relations satisfied state and a polynomial relations unsatisfied state. A first selected instruction set is executed at the first computing device in response to the polynomial relations satisfied state. A second selected instruction set is executed at the first computing device in response to the polynomial relations unsatisfied state.