Proof-of-Work Difficulty Adjustment via LFSR Polynomial Segmentation
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Solution Overview
Problem
Conventional computational puzzles are difficult to fine-tune for adjusting difficulty levels, which is a challenge in proof-of-work systems used for security, such as in cryptocurrencies, as they lack flexibility in controlling the computational effort between verifiers and provers.
Innovation Solution
The method involves using linear feedback shift register sequences (LFSR-S) computed with polynomials where a first polynomial divides a second polynomial, allowing a verification computing device to generate challenges and solutions that can be verified by recomputing the solution using initial state parameters and coefficients, enabling easy adjustment of proof-of-work difficulty.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional computational puzzles are used, then proof-of-work security is provided, but the difficulty level cannot be easily adjusted
Solution Approach 1:
The patent applies parameter changes by modifying the degree of the first polynomial to control the number of iterations required to generate the first LFSR sequence. By adjusting this parameter, the computational difficulty can be easily tuned without changing the overall puzzle structure, directly resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The patent introduces dynamics by making the polynomial degree a variable parameter that can be adjusted based on required difficulty levels. This dynamic parameter allows the system to adapt to different security requirements while maintaining a consistent verification process, enabling easy fine-tuning of proof-of-work difficulty.
2Reliability
If polynomial degree is increased to increase iterations, then proof-of-work difficulty increases, but verification complexity also increases
Solution Approach 1:
The patent segments the verification process into two distinct parts: the verifier computes only the second LFSR sequence using the second polynomial, while the prover computes the first LFSR sequence using the first polynomial. This segmentation allows the verifier's complexity to remain independent of the first polynomial's degree, resolving the contradiction between security strength and verification complexity.
Solution Approach 2:
The patent introduces an intermediary relationship where the second LFSR sequence serves as a mediator that the verifier can independently compute and use to verify the prover's solution. This intermediary structure enables the verifier to validate proofs without needing to perform the computationally intensive first LFSR sequence generation, maintaining verification efficiency even as security strength increases.
Data Source
AI summary
A method for providing a proof-of-work includes computing, by a verification computing device (VCD), a first linear feedback shift register sequence (LFSR-S) using a first polynomial having a first degree and computing, by the VCD, a second LFSR-S based on a second polynomial. A challenge, generated by the VCD and using elements of the second LFSR-S, is transmitted to the PCD. The PCD recursively computes all elements of the first LFSR-S by using the elements and coefficients of the second LFSR-S. A solution for the received challenge is computed based on the computed elements of the first LFSR-S. A proof-of-work is provided by verifying, by the VCD, the transmitted solution by: recomputing a solution to the challenge using initial state parameters and coefficients of the first LFSR-S, and comparing the computed solution of the PCD with the recomputed solution of the VCD.