Data Recovery System Using Lineage-Based Selection
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Solution Overview
Problem
Existing data recovery methods, such as those described in US2021/0216628, often rely on recovering data from very old backups, leading to differences from the latest data and potential loss of business opportunities.
Innovation Solution
A data recovery system that includes a storage device for original data, an analyzing server for formatted copy data, a managing server for data history management, and a data recovery unit that selects the appropriate recovery data based on data lineage and history, allowing for recovery using the latest data possible.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is recovered from old backup data, then data security is improved, but data freshness and business continuity are worsened
Solution Approach 1:
The system performs preliminary actions by creating multiple copies of data at different stages (original data, formatted data, analysis data) and storing them with metadata information before any security incident occurs. This allows the system to have pre-prepared recovery options ready, eliminating the need to search for suitable recovery data when an incident happens, thus reducing recovery time while maintaining security through selective recovery from uninfected copies.
2Productivity
If data recovery frequency is increased, then data freshness is improved, but system resource consumption and complexity are worsened
Solution Approach 1:
The system segments the data lifecycle into distinct stages: original data storage, formatted data creation, and analysis data generation. Each stage produces a recoverable copy with associated metadata. This segmentation allows the system to increase recovery frequency by selecting from multiple staged copies without requiring complete system-wide backup operations, thus improving productivity while managing complexity through structured data organization.
3Adaptability or versatility
If multiple data copies are maintained for recovery options, then data recovery flexibility is improved, but storage resource consumption is worsened
Solution Approach 1:
The system applies local quality by maintaining different types of data copies at different locations in the data processing pipeline. Instead of duplicating full data sets everywhere, it creates formatted versions and analysis versions only where needed for specific purposes. The metadata associated with each copy enables flexible recovery selection without requiring all copies to be stored at full capacity, thus improving adaptability while optimizing storage utilization.
Data Source
AI summary
When the latest data and a backup of the latest data are infected, the data is recovered from the backup older than the data. Therefore, it is necessary to eliminate a difference from the latest data, leading to loss of business opportunities. A data recovery system that recovers data stored in a storage system includes a storage device that holds original data, an analyzing server that holds a copy of the original data, and generates formatted data by formatting the copy data for analysis, a managing server that holds the copy data and data history management information storing a history of the formatted data, and a data recovery unit that refers to the data history management information, selects the copy data or the formatted data as recovery data, and recovers the data from the selected recovery data when a security threat is detected in the data.