Automated Data Anonymization in Distributed Storage
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Solution Overview
Problem
Cloud storage systems face challenges in securely and efficiently storing sensitive information due to increasing cyber-attacks and data leaks, leading to significant burdens on service providers and performance impacts from implementing complex security measures.
Innovation Solution
Implementing a distributed storage system that automatically anonymizes data by removing or obfuscating sensitive information before persistent storage, using a software program to process data in non-persistent buckets and transfer anonymized versions to persistent storage, thereby reducing computational and security overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex security measures are implemented to protect sensitive information in cloud storage systems, then security and privacy protection is improved, but system performance deteriorates due to resource diversion
Solution Approach 1:
The system performs preliminary anonymization processing on data before it is stored in the distributed storage system. By removing or obfuscating sensitive information in advance, the system reduces the security overhead required during storage and retrieval operations, thus maintaining security while preserving system performance
Solution Approach 2:
The system extracts and removes sensitive information from data before storage. By separating sensitive elements from the main data body through anonymization, the system reduces the security burden on the storage system while maintaining protection for the remaining information
2Adaptability or versatility
If sensitive information is stored in cloud storage systems, then data storage capability is improved, but security risks worsen due to increasing cyber-attacks and data leaks
Solution Approach 1:
The system converts potentially harmful sensitive information into benign anonymized data before storage. By transforming sensitive elements into unusable forms for attackers while preserving data utility, the system enables storage capability while neutralizing security risks from cyber-attacks and data leaks
3Reliability
If complex security measures are implemented to comply with regulations, then regulatory compliance is improved, but computational overhead increases
Solution Approach 1:
The system performs preliminary anonymization processing to meet regulatory requirements before data is stored. By completing compliance-related security processing in advance, the system reduces ongoing computational overhead during normal storage operations while maintaining regulatory compliance
Data Source
AI summary
Data can be automatically anonymized in a distributed storage system. For example, a system can receive a notification indicating that an object is stored in a non-persistent bucket of a distributed storage system. The system can read the object from the non-persistent bucket in response to receiving the notification. The system can generate an anonymized version of the object by performing one or more anonymization operations with respect to the object. The system can store the anonymized version of the object in a persistent bucket of the distributed storage system. The system can then transmit a command for causing the object to be removed from the non-persistent bucket.