Data Storage Deduplication with Anonymized Data Separation
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Solution Overview
Problem
Conventional data storage systems face inefficiencies in deduplication due to data anonymization, leading to increased storage space occupation and reduced performance, as existing methods struggle to effectively handle frequent changes or small modifications in data.
Innovation Solution
A data storage arrangement and method that incorporates anonymization-aware deduplication, where the controller identifies and separates anonymized data portions from the original data elements, generates a modified data element for deduplication, and stores both the modified data element and the anonymized data portions separately, enabling efficient deduplication and storage utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data anonymization is applied to protect privacy, then confidentiality is improved, but deduplication effectiveness deteriorates
Solution Approach 1:
The data element is segmented into two distinct parts: anonymized data portions and non-anonymized data portions. This segmentation allows the system to apply different storage strategies to each part, enabling deduplication on the non-anonymized portions while maintaining privacy protection on the anonymized portions.
Solution Approach 2:
The anonymized data portions are extracted and separated from the non-anonymized data portions. By taking out the anonymized parts, the system can perform deduplication operations only on the non-anonymized portions, thereby maintaining deduplication effectiveness while still providing privacy protection through the separate storage of anonymized data.
2Quantity of substance
If conventional deduplication methods are used, then storage efficiency is improved for identical data, but performance deteriorates when frequent changes occur
Solution Approach 1:
Different quality treatments are applied to different parts of the data element. The non-anonymized portions undergo deduplication processing to maximize storage efficiency, while the anonymized portions are stored separately without deduplication. This local differentiation allows the system to maintain high storage efficiency for stable data while handling frequent changes in anonymized portions without performance degradation.
3Reliability
If all data is stored to ensure completeness, then data recovery capability is improved, but storage cost increases
Solution Approach 1:
The system creates selective copies rather than storing complete data elements. By copying only the non-anonymized portions for deduplication storage and keeping anonymized portions separate, the system reduces overall storage requirements while maintaining the capability to reconstruct complete data elements when needed, thus balancing storage cost with data recovery capability.
Data Source
AI summary
A data storage arrangement includes a memory and a controller, where the controller receives an indication of data to be anonymized. The controller further parses a data element to be stored and generates a copy of one or more data portions to be anonymized. The controller further deletes one or more data portions to be anonymized to generate a modified data element to be stored. The controller further generates a copy of the modified data element to be stored utilizing deduplication. The data storage arrangement thus takes in account data anonymization during deduplication (i.e. an anonymization aware deduplication).