Merkle Tree Record Segmentation for Low-Latency Secure Storage
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Solution Overview
Problem
Existing datastores face security vulnerabilities from internal attackers who can modify or exfiltrate confidential data, and traditional security measures impose high latency during read and write operations, especially in blockchain-based systems handling large data sets.
Innovation Solution
A tree structure is used to segment and distribute records across decentralized, acyclic graphs of cryptographic hash pointers, ensuring data integrity and reducing latency through direct data storage in Merkle Trees, with secure translation and merging of data between lower-trust and higher-trust databases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security measures are implemented to protect data from internal attackers, then data security is improved, but latency during read and write operations increases
Solution Approach 1:
The patent segments data into multiple blocks that are distributed across different storage locations. Each block is independently secured with cryptographic hashing, allowing parallel processing and retrieval operations. This segmentation enables security measures to be applied at the block level rather than requiring full-data verification, thereby reducing overall operation latency while maintaining security.
Solution Approach 2:
The patent introduces cryptographic hash pointers as intermediaries between data blocks and the verification system. These hash pointers serve as lightweight proxies that enable rapid verification of data integrity without requiring direct inspection of the actual data content. This intermediary mechanism significantly reduces verification latency while maintaining strong security guarantees.
2Ease of operation
If data is stored in a centralized datastore, then access and retrieval are simplified, but security vulnerabilities from internal attackers increase
Solution Approach 1:
The patent divides centralized data storage into distributed blocks across multiple locations in the decentralized graph structure. Each block maintains independent security credentials through cryptographic hashing, allowing the system to achieve both distribution for security and logical centralization for ease of access through unified API interfaces.
Solution Approach 2:
The patent transforms the trust model parameter from centralized authority-based trust to cryptographic proof-based trust. By changing the fundamental parameter of how trust is established (from institutional trust to mathematical proof), the system achieves enhanced security without sacrificing operational simplicity for end users.
3Reliability
If cryptographic verification is performed on all data operations, then data integrity is ensured, but processing speed decreases
Solution Approach 1:
The patent implements partial cryptographic verification by applying full cryptographic checks only to critical data blocks and using lighter-weight verification methods for non-critical blocks. This selective approach ensures data integrity for essential information while maintaining high processing speeds for less sensitive operations, thereby resolving the contradiction between thorough verification and processing speed.
Data Source
AI summary
Provided is a process including: receiving, with one or more processors, a first request to store a record from a computing entity; encoding, with one or more processors, the record in a first plurality of segments; arranging, with one or more processors, the first plurality of segments in respective content nodes of a first content graph, wherein at least some content nodes of the first content graph have two or more content edges of the first content graph pointing to two or more respective other content nodes of the first content graph; and storing, with one or more processors, the content nodes of the first content graph in a verification graph.