Automated Corporate Data Segmentation for Backup Systems
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Solution Overview
Problem
Conventional backup and archival systems fail to distinguish between corporate and personal data, leading to unnecessary storage space usage, legal ramifications, and employee discomfort, as well as the risk of sensitive corporate data being included in personal backups.
Innovation Solution
A computing device categorizes data items using DLP systems, applying techniques like indexed document matching, exact data matching, and vector machine learning to separate corporate and personal data, providing them to respective backup systems, with a file system filter driver intercepting access to ensure only appropriate data is backed up.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional backup systems backup all data without distinction, then all data (both corporate and personal) is preserved, but storage space is unnecessarily consumed and legal issues arise
Solution Approach 1:
The backup system segments data into corporate and personal categories using classification algorithms and metadata analysis. The system automatically identifies and separates personal data from corporate data, creating distinct backup streams for each category, thereby reducing unnecessary storage consumption while maintaining reliability of corporate data backup.
Solution Approach 2:
The system extracts personal data from the mixed corporate data stream before backup operations. By identifying personal data through classification rules and removing it from the corporate backup set, the system reduces storage space requirements while ensuring only necessary corporate data is preserved.
2Reliability
If conventional backup systems backup all data, then complete data protection is achieved, but legal ramifications and employee discomfort occur
Solution Approach 1:
The system segments data into corporate and personal domains with clear boundaries. By classifying and separating personal data from corporate data, the system creates legally compliant backup processes that respect employee privacy rights while maintaining protection of corporate assets, thereby eliminating legal risks associated with unauthorized personal data collection.
Solution Approach 2:
The system introduces an intermediary classification layer between data collection and backup processes. This intermediary layer analyzes data characteristics, applies classification rules, and determines which data should be backed up, thereby mediating between complete data protection goals and legal/privacy requirements.
3Reliability
If employees perform personal backups of corporate resources, then personal data is protected, but sensitive corporate data may be inadvertently copied
Solution Approach 1:
The system extracts and identifies corporate data within personal backup operations through classification algorithms. By detecting corporate data patterns and markers, the system can alert employees or automatically prevent copying of sensitive corporate information, thereby protecting personal data while preventing corporate data exposure.
4Ease of operation
If mixed data is backed up without separation, then backup simplicity is maintained, but data management complexity increases when accessing specific data types
Solution Approach 1:
The system segments data into organized categories (corporate/personal) with automatic classification. This segmentation provides clear data organization and simplifies access to specific data types, reducing management complexity while maintaining ease of operation through automated categorization processes.
Solution Approach 2:
The system implements self-service automatic classification that autonomously categorizes data without user intervention. The classification algorithms automatically identify and tag data types, providing simple backup operations while the system handles the complexity of data organization and management automatically.
Data Source
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AI summary
A computing device categorizes data items as a corporate data items when a first criterion is satisfied and as personal data items when a second criterion is satisfied. The computing device provides identified corporate data items to a first backup system that stores the corporate data items to a corporate data store. The computing device further provides identified personal data items to a second backup system that stores the personal data items to a personal data store.