Blockchain Snapshot Verification via Data Segmentation
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Solution Overview
Problem
Current methods for obtaining and verifying snapshots of blockchain data at specific time points require significant computational resources, making them inefficient for auditors confirming transaction accuracy.
Innovation Solution
A system that includes snapshot nodes and auditor nodes, where snapshot nodes generate and verify snapshots using differences in blockchain data across time points, reducing the computational burden by utilizing hashes from multiple nodes and storing archival records, allowing auditors to confirm snapshot accuracy with less resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current methods are used to obtain and verify snapshots of blockchain data at specific time points, then snapshot accuracy is maintained, but computational resource consumption is high
Solution Approach 1:
The patent divides the blockchain data into multiple snapshots at different time points. Instead of processing all data at once, the system segments the data chronologically and only processes the specific time point requested by the auditor, significantly reducing computational resources while maintaining accuracy.
Solution Approach 2:
The system pre-generates and stores snapshots of blockchain data at various time points in advance. When an auditor needs to verify data at a specific time point, the pre-computed snapshot is already available, eliminating the need for expensive real-time computation and reducing energy consumption.
2Adaptability or versatility
If snapshots are generated for multiple time points, then auditor flexibility is improved, but storage requirements increase
Solution Approach 1:
The system creates simplified copies of blockchain data at specific time points in the form of snapshots. These copies contain only the essential state information needed for verification, not the entire blockchain history, thus providing auditor flexibility while controlling storage requirements.
Solution Approach 2:
Different snapshots are stored with different levels of detail based on their intended use. The system optimizes storage by storing only the necessary data for each time point rather than uniform high-detail storage for all snapshots, balancing flexibility and storage efficiency.
Data Source
AI summary
Verified snapshots are generated by obtaining, from one of a plurality of first nodes, a difference between a common data at a first time point and the common data at a second time point that is different from the first time point, generating a first snapshot of the common data at the first time point based on the difference, obtaining a hash of the common data at the first time point from one of the plurality of first nodes, and verifying the first snapshot at the first time point with the hash of the common data at the first time point.


