Blockchain Audit Data Segmentation for Efficiency
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Solution Overview
Problem
Current blockchain audit ledgers lack full audit capabilities, fail to achieve reading-writing separation and reading-writing-verifying separation, resulting in low audit efficiency due to the absence of distinct current and history record tables and implicit storage of audit data.
Innovation Solution
A data processing method that acquires target activity data and operation data, stores them in separate record tables based on time periods, and generates audit data using a full audit data table with specific fields to ensure complete and correct audits, enabling reading-writing and reading-writing-verifying separation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If audit data is stored implicitly in blockchain without separate record tables, then the system structure remains simple, but audit efficiency is low and full audit cannot be realized
Solution Approach 1:
The patent divides the blockchain audit system into separate functional modules: current record tables for new data, history record tables for archived data, and full audit data tables for comprehensive verification. This segmentation enables efficient audit operations while maintaining data completeness, resolving the contradiction between audit efficiency and system complexity.
2Ease of operation
If current and history activity data are stored together in the same table, then the storage structure is simple, but reading-writing separation cannot be achieved
Solution Approach 1:
The patent implements separate current record tables and history record tables to achieve reading-writing separation. Current tables handle active transactions while history tables store archived data, enabling independent read and write operations without interference, thus improving ease of operation despite increased storage structure complexity.
Solution Approach 2:
The patent introduces a time-based dimension to the storage structure by separating data into current and history tables based on time periods. This temporal dimension organization enables reading-writing separation while maintaining a systematic approach to data management.
3Productivity
If all activity data is stored in a single blockchain ledger, then data completeness is maintained, but audit verification becomes inefficient
Solution Approach 1:
The patent creates full audit data tables that selectively store comprehensive audit information for verification purposes while maintaining separate current and history tables for operational data. This segmentation enables efficient audit verification by providing dedicated audit structures without losing overall data completeness.
Solution Approach 2:
The patent creates audit copies of essential data in full audit data tables that are optimized for verification operations. These copies contain the necessary information for complete audit verification while allowing the original operational tables to maintain their optimized structures, thus improving verification efficiency without compromising data completeness.
Data Source
AI summary
The present disclosure provides a data processing method, a computer device and a storage medium, wherein the method includes: acquiring target activity data and operation data after a target transaction operation being performed on individual target activity data; storing first activity data in a current record table, and storing second activity data in a history record table; generating, based on preset fields in a full audit data table, first audit data of the individual target activity data in individual fields and second audit data of individual operation data in the individual fields; and storing the first audit data and the second audit data in the full audit data table.