Cold Image Data Recovery Using Virtual Filesystem Parsing
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Solution Overview
Problem
Current technologies face challenges in recovering data from cold images, particularly due to difficulties in accessing and parsing application-specific data structures without an operating system or associated application, and the growing complexity with virtual machine image files.
Innovation Solution
A computer-implemented method that searches storage, identifies and parses data structures, and recovers data using an alternative boot process, leveraging metadata and application-specific utilities to facilitate full or granular recovery of data from cold images, including virtual machine and application data structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional data recovery methods are used on cold images, then access to the file system is attempted, but the ability to identify and parse application-specific data structures is lost
Solution Approach 1:
The patent introduces an intermediary recovery system that operates independently of the original operating system. This recovery system uses a standardized interface layer that translates between the cold image's native data structures and the recovery system's parsing mechanisms, enabling data recovery without requiring the original OS or applications to be running.
Solution Approach 2:
The patent creates a virtual copy of the cold image's file system and data structures in a controlled environment. By mounting the cold image as a virtual filesystem and creating virtual instances of applications, the system can parse and recover data without modifying the actual cold image, enabling analysis and recovery operations.
2Reliability
If application-specific formats are parsed without the application running, then data recovery is enabled, but parsing accuracy and interpretability deteriorate
Solution Approach 1:
The patent segments the data recovery process into distinct phases: identification phase (using metadata and heuristics to locate data structures), parsing phase (using virtual application instances to interpret formats), and recovery phase (extracting and validating data). This segmentation allows each phase to optimize for its specific requirements, improving overall reliability while maintaining parsing accuracy through specialized parsing components.
Solution Approach 2:
The patent implements feedback mechanisms where the recovery system validates parsed data structures against expected schemas and metadata information. Virtual application instances provide feedback on the correctness of parsed data, allowing the system to correct parsing errors and verify data integrity, thereby maintaining high parsing accuracy without requiring the original applications to run.
3Ease of operation
If virtual machine image files are accessed without the virtual machine running, then data accessibility is improved, but the complexity of identifying and parsing files increases
Solution Approach 1:
The patent creates a universal recovery platform that can handle multiple virtual machine formats (VMDK, VHX, VHD, etc.) and various application data structures through a single standardized interface. The system uses a plugin architecture where different parsers and validators can be dynamically loaded based on the detected data format, reducing overall system complexity while maintaining broad compatibility.
Solution Approach 2:
The patent dynamically changes the parsing parameters and detection heuristics based on the detected virtual machine format and data structure type. By adapting the recovery system's behavior to match the specific characteristics of each data format, the system simplifies the parsing process for each individual case while maintaining universal capability across different formats.
4Quantity of substance
If full data recovery is performed from cold images, then data completeness is improved, but the time required for recovery increases
Solution Approach 1:
The patent enables partial recovery operations that allow users to recover only specific data types, files, or time ranges from the cold image. By implementing selective recovery based on user-defined criteria and metadata filtering, the system can provide complete data recovery when needed while enabling faster partial recovery for common scenarios, reducing overall recovery time without sacrificing completeness when required.
Data Source
AI summary
Techniques for recovering data from cold images are disclosed. In one particular exemplary embodiment, the techniques may be realized as a computer implemented method for recovering data from cold images comprising searching storage associated with a target recovery device, identifying one or more data structures on the storage, parsing the one or more identified data structures, and recovering one or more portions of the one or more parsed data structures.