Storage Volume Dependency Mapping for Security Threat Detection
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Solution Overview
Problem
Existing storage systems face challenges in efficiently managing data storage and retrieval across multiple storage nodes, particularly in ensuring data security and availability in the face of potential failures or disruptions.
Innovation Solution
The implementation of a storage system that utilizes non-volatile solid state storage units with embedded processors and flash memory, coupled with a distributed architecture that includes multiple storage nodes and a cloud-based storage system, to provide scalable, secure, and fault-tolerant data storage solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in a centralized storage system, then data access is simple and fast, but data availability and security deteriorate when failures occur
Solution Approach 1:
The patent divides the storage system into multiple storage nodes distributed across different locations. Each node stores portions of data independently, allowing the system to maintain data availability even when individual nodes fail. This segmentation transforms a single point of failure into multiple redundant access points.
Solution Approach 2:
The patent introduces a storage management system that acts as an intermediary between clients and storage nodes. This mediator handles data routing, redundancy management, and failure recovery, abstracting the complexity of distributed storage from end users while maintaining simple data access interfaces.
2Reliability
If data is replicated across multiple storage nodes, then data availability improves, but storage overhead and complexity increase
Solution Approach 1:
The patent employs erasure coding that transforms data into multiple coded fragments with adjustable redundancy levels. By changing the coding parameters, the system can optimize the balance between data security and storage overhead, achieving robust data protection without simply duplicating entire data sets across all nodes.
Solution Approach 2:
The patent implements selective replication where only critical data portions or metadata are fully replicated, while less critical data uses更高效的重建机制。This partial replication strategy provides adequate data security for essential information while minimizing overall storage overhead.
3Reliability
If distributed storage architecture is implemented, then fault tolerance improves, but system complexity and management difficulty increase
Solution Approach 1:
The patent implements automated failure detection and recovery mechanisms where storage nodes continuously monitor each other's health status. When failures are detected, the system automatically triggers data reconstruction and redistributes data across remaining nodes without requiring manual intervention, thereby maintaining fault tolerance while simplifying operations.
Solution Approach 2:
The storage management system continuously collects performance and health data from all storage nodes, analyzing this feedback to optimize data placement, predict potential failures, and dynamically adjust redundancy levels. This feedback-driven approach automates complex management tasks and maintains optimal system performance.
Data Source
AI summary
An example method for monitoring volume dependencies for security threats comprises: detecting a request to perform an operation with respect to a volume included in a plurality of volumes included in a storage system; determining, based on a dependency mapping that specifies dependencies between the plurality of volumes, that performance of the operation would affect a dependency between the volume and one or more other volumes included in the plurality of volumes; and determining, based on the determining that the performance of the operation would affect the dependency between the volume and the one or more other volumes, that the request is possibly associated with a security threat against data stored by the storage system.