Conditional Immutable Data Storage with Policy-Based State Transitions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Information handling systems face challenges in managing data that requires immutability at certain times and mutability at others, due to regulatory requirements, which existing technologies struggle to address efficiently.
Innovation Solution
The implementation of a data storage system that provides conditional immutable data storage, allowing data to be treated as immutable in specific circumstances and mutable in others, using a Write-Once Read-Many (WORM) storage system with a data handler that manages write, read, and delete requests through universally unique identifiers (UUIDs) and authentication keys, enabling flexible access control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored as immutable using WORM systems, then data retention compliance is improved, but data flexibility and update capability deteriorate
Solution Approach 1:
The patent applies dynamics by making the immutability property changeable over time. Data objects transition between mutable and immutable states based on retention policies. The system dynamically adjusts data protection levels, allowing data to be modified during the retention period and then locked for permanent preservation, resolving the contradiction between flexibility and compliance.
Solution Approach 2:
The system changes the immutability parameter of data objects based on temporal conditions and policy rules. By modifying the state parameter from mutable to immutable, the system enables data to adapt to different regulatory requirements at different time points, simultaneously achieving flexibility when needed and compliance when required.
2Adaptability or versatility
If data is stored as mutable for easy access and modification, then data flexibility is improved, but data integrity and protection deteriorate
Solution Approach 1:
The system dynamically transitions data between mutable and immutable states based on policy conditions. During active retention periods, data remains mutable for access and modification. When retention periods expire or compliance requirements are met, data automatically transitions to immutable state, ensuring integrity protection without permanently sacrificing flexibility.
Solution Approach 2:
The system performs preliminary actions by establishing retention policies and immutability rules in advance. Data objects are pre-configured with metadata indicating their retention requirements, allowing the system to automatically enforce integrity protection at the appropriate time without manual intervention, balancing flexibility and protection proactively.
3Reliability
If WORM storage is used for permanent data retention, then data protection is improved, but data deletion capability deteriorates
Solution Approach 1:
The system makes deletion capability dynamic by allowing data to be deleted during mutable periods when retention requirements are not yet met. Once data transitions to immutable state for permanent retention, deletion is prevented. This dynamic approach enables easy deletion when appropriate while providing strong protection when required, resolving the contradiction between deletion flexibility and protection.
4Reliability
If conditional immutability is implemented with policy management, then regulatory compliance is improved, but system complexity deteriorates
Solution Approach 1:
The system implements self-service by automatically enforcing retention policies without requiring manual intervention. Data objects carry metadata about their retention requirements, and the system automatically transitions them between mutable and immutable states based on policy rules. This automation reduces operational complexity while maintaining compliance, as the system manages itself according to predefined policies.
Solution Approach 2:
The patent applies universality by creating a unified data object structure that handles both mutable and immutable operations through a common interface. The same data object model supports both modification and protection modes, eliminating the need for separate systems for different data states. This multi-functional approach reduces overall system complexity while enabling regulatory compliance.
Data Source
AI summary
A data storage system includes a storage device and a data handler that receives an object, creates metadata for the object that includes a key and an authorization, stores the object on the storage device, receives a request for the object, determines if the request includes the key, and, if the request has authorization information, permits access to the object. The data handler receives another request for the object, determines if the request includes the key, and, if the request does not have the authorization information, denies access to the object.