Binary Matrix Checksum Verification for Quantum-Resistant Integrity
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Solution Overview
Problem
Traditional hash functions for data integrity verification are vulnerable to mathematical and quantum attacks due to their reliance on calculations, requiring significant computational resources and being prone to brute-force defeat.
Innovation Solution
A checksum generation method that counts the appearances of '0' and '1' in rows, columns, and diagonals of a data matrix, forming keys and assembling a checksum through ordering and applying XOR or XNOR operators, without relying on mathematical functions, to create a unique and tamper-resistant data integrity system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional hash functions are used for data integrity verification, then data verification capability is provided, but computational resources are heavily consumed and vulnerability to attacks increases
Solution Approach 1:
The patent replaces traditional mathematical calculation-based hash functions with a counting-based checksum system. Instead of performing complex mathematical operations, the system counts the occurrences of '0' and '1' in binary data and uses these counts to generate checksum values. This substitution of mechanical counting for mathematical computation reduces computational resource consumption while maintaining data verification capability
Solution Approach 2:
The patent changes the fundamental parameter of data verification from mathematical hash values to counting-based checksum values. By transforming the verification mechanism from calculating complex mathematical functions to simply counting binary digit occurrences, the system achieves lower computational overhead and reduced energy consumption while providing equivalent data integrity verification
2Reliability
If traditional hash functions are used for data integrity verification, then data verification capability is provided, but vulnerability to brute-force and quantum attacks increases
Solution Approach 1:
The patent replaces mathematical calculation systems with a counting-based system that is inherently more resistant to attacks. By using simple counting of binary digit occurrences rather than complex mathematical functions, the system eliminates vulnerabilities to mathematical attacks and quantum computing threats that target traditional hash functions
Solution Approach 2:
The patent employs a checksum generation method that uses simple, easily computable counting operations instead of complex mathematical functions. This approach creates a verification system that is computationally inexpensive and difficult to attack through brute-force methods, as the counting mechanism does not rely on mathematical complexity that can be compromised
3Productivity
If counting-based checksum method is used, then computational resources consumption is reduced and attack resistance is improved, but complexity in handling multiple data dimensions is introduced
Solution Approach 1:
The patent segments the data verification process into multiple independent counting operations along different dimensions (rows, columns, diagonals). Each dimension is processed separately by counting '0' and '1' occurrences independently, then the results are combined to form the final checksum. This segmentation simplifies the overall complexity by breaking down the multi-dimensional problem into manageable one-dimensional counting tasks
Data Source
AI summary
A checksum generator of a data matrix is provided that comprises counting at least one of:the numerals “0” and “1” in at least one row of the data matrix so that the number of appearances of each numeral is sequentially placed,the numerals “0” and “1” in at least one column of the data matrix so that the number of appearances of each numeral is sequentially placed,the numerals “0” and “1” in at least one left diagonal of the data matrix so that the number of appearances of each numeral is sequentially placed, andthe numerals “0” and “1” in at least one right diagonal of the data matrix so that the number of appearances of each numeral is sequentially placed.The method further comprises ordering the number of appearances of each numeral to form a key and sequentially positioning the key to assemble the checksum. In addition, counting the numerals “0” and “1” is performed in a predetermined order. Further provided are methods of implementing the checksum generated according to the counting method.


