Hierarchical Hash Tree for Genomic Data Integrity
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Solution Overview
Problem
Current genomic data storage systems lack efficient integrity control, particularly in large files, where conventional methods are slow and unable to efficiently group data structures for integrity verification, update, or track changes, and do not protect the relationship between data components effectively.
Innovation Solution
A digital data structure utilizing a hierarchical Merkle tree or Verkle tree with partial hash trees, allowing for quick verification and updates while reducing storage size by excluding lower level parts, and using tree parameters to determine the included hash tree size and structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional integrity measures are applied to large genomic data files, then data integrity can be verified, but the computational time required becomes excessively long
Solution Approach 1:
The patent divides the large genomic data file into multiple blocks, where each block is assigned a unique identifier and processed independently. This segmentation allows parallel processing of integrity verification across different blocks, significantly reducing the total computational time compared to verifying the entire file as a single unit.
Solution Approach 2:
The patent introduces a hierarchical data structure with multiple levels (file level, dataset group level, dataset level, access unit level, and block level). This multi-dimensional hierarchy enables verification to proceed from smaller units upward, allowing partial verification of specific blocks or datasets without requiring verification of the entire file, thus reducing computational time for targeted verification scenarios.
2Reliability
If complete hash trees are stored for all genomic data blocks, then integrity verification is comprehensive, but storage requirements increase significantly
Solution Approach 1:
The patent extracts and stores only the essential integrity information (hash values and unique identifiers) at each hierarchical level, rather than storing complete hash trees for all data blocks. This selective extraction maintains verification capability while significantly reducing the storage overhead associated with comprehensive integrity protection.
Solution Approach 2:
The patent implements a nested hierarchical structure where hash values from lower levels (blocks, access units) are aggregated into higher levels (datasets, dataset groups, files). This nesting allows the system to store compact representations at each level, where the parent level hash encompasses the integrity information of child levels, reducing total storage requirements while maintaining comprehensive verification capability.
Data Source
AI summary
Some embodiments are directed to a data structure. The data structure includes multiple blocks and part of a first hash tree. The hash tree is computed from multiple hash values of the multiple genomic blocks. The part of the first hash tree includes at least the first two highest levels of the first hash tree but excluding one or more lower levels of the first hash tree.