Intelligent Backup Versioning with Reputation Scoring
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Solution Overview
Problem
Ransomware attacks pose a significant threat by encrypting files, making it impractical to decrypt without the decryption key, and existing backup solutions face challenges in efficiently storing and retrieving versioned backups, leading to storage issues and limited protection against data corruption.
Innovation Solution
An intelligent backup system with versioning that assigns a reputation to each backup based on contextual parameters, such as entropy, timing, and user presence, allowing for selective storage and retrieval of the most valuable backup versions, and moving less valuable versions to less expensive storage or archiving them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all backup versions are stored to ensure complete protection against ransomware, then reliability of data recovery is improved, but storage space consumption increases
Solution Approach 1:
The system changes the parameter of backup version selection by introducing a reputation score based on multiple factors (entropy analysis, timing patterns, user presence). This allows dynamic prioritization of backup versions, storing high-reputation versions with higher fidelity while managing overall storage consumption through intelligent parameter-based selection.
Solution Approach 2:
Different backup versions are treated with different quality levels based on their reputation scores. High-reputation backups receive priority storage and retention, while low-reputation backups are archived or deleted. This local quality differentiation resolves the contradiction by ensuring reliable recovery from valuable backups while reducing storage for less valuable ones.
2Adaptability or versatility
If multiple backup versions are retained for ransomware protection, then data recovery options are improved, but storage costs increase
Solution Approach 1:
The system introduces reputation scoring as a new parameter to evaluate and prioritize backup versions. By analyzing entropy, timing, and user presence parameters, the system dynamically determines which backups to retain, archive, or delete, providing versatile recovery options while controlling storage costs through parameter-based decision making.
Solution Approach 2:
The backup retention strategy is made dynamic through continuous reputation assessment. As new backups are created and circumstances change (user presence, file entropy, timing patterns), the system dynamically adjusts which versions are retained, archived, or deleted, providing adaptability in recovery options while optimizing storage cost efficiency.
3Quantity of substance
If backup storage quota is increased to accommodate all versions, then backup completeness is improved, but storage resource efficiency deteriorates
Solution Approach 1:
Instead of uniformly increasing storage quota, the system changes the parameter of backup selection by introducing reputation scoring. This allows the system to maintain adequate backup storage capacity while improving resource efficiency through intelligent selection of which backups to retain based on multiple parameters including entropy, timing, and user presence.
Solution Approach 2:
The system selectively discards low-reputation backup versions and recovers only high-reputation versions when needed. This approach maintains backup completeness for valuable data while dramatically improving storage resource efficiency by eliminating redundant or low-value backup copies.
Data Source
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AI summary
There is disclosed in one example a computing apparatus, including : an interface to a backup source in a current state; a backup storage having stored thereon a first backup version of a previous state of the source; and a backup engine to: compute a delta between the current state and the previous state; save via the backup storage a second backup version sufficient to reconstruct the current state; and assign the second backup version a reputation relative to one or more previous backup versions.