Distributed Blockchain Storing File Differentials via Merkle Trees
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Solution Overview
Problem
Traditional databases and blockchain systems face challenges in securely storing and managing large data sets, particularly in preventing tampering and ensuring data integrity, especially when dealing with large files and high-latency access, and they often lack robust security features to protect against internal threats and data modification.
Innovation Solution
The implementation of a tamper-evident, immutable data repository using Merkle Trees and directed acyclic graphs (DAGs) within a distributed blockchain system, which allows for low-latency operations and secure storage of large data sets by storing data directly in the Merkle Trees, using cryptographic hash pointers to ensure data integrity and prevent tampering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional databases are used to store large data sets, then storage capacity is sufficient, but security and data integrity cannot be trusted due to potential tampering by attackers
Solution Approach 1:
The patent segments large files into smaller chunks and stores them in a distributed blockchain network. Each chunk is individually hashed and linked to form a Merkle Tree structure, which is then stored on the blockchain. This segmentation allows verification of individual chunks without exposing the entire file, enhancing security while maintaining storage capacity.
Solution Approach 2:
The patent introduces cryptographic hash functions and Merkle Trees as intermediaries between the stored data and the blockchain. These intermediaries transform the original data into verified hashes that can be stored on the blockchain without storing the actual large files, providing a trusted verification layer that prevents tampering while maintaining storage efficiency.
2Loss of time
If full versions of documents are stored in the immutable data repository, then data retrieval is simple, but storage space is wasted and latency increases as the data set grows
Solution Approach 1:
The patent extracts only the essential verification elements (cryptographic hashes and Merkle Tree roots) from the full documents and stores them on the blockchain. The actual large files are stored off-chain in distributed storage systems. This extraction reduces on-chain storage requirements dramatically while maintaining fast verification through hash comparison.
Solution Approach 2:
The patent performs preliminary hashing and Merkle Tree construction before storing data on the blockchain. By pre-computing the cryptographic fingerprints of files and their chunks, the system enables rapid verification without needing to store or process the full files on-chain, reducing both storage space and access latency.
3Reliability
If cryptographic hash pointers are used to ensure data integrity, then tampering detection is improved, but computational complexity increases
Solution Approach 1:
The patent segments the computational work of hash verification into a tree structure where only the root hash needs to be verified on the blockchain. Individual chunk hashes are computed locally and linked in a Merkle Tree, requiring minimal computational resources compared to verifying entire files. This segmentation makes tamper detection computationally efficient.
Data Source
AI summary
Provided is a process including: receiving a request to write a new version of a document to a tamper-evident, immutable data repository; determining that the new version of the document is different from the previous version of the document; and in response to determining, storing a difference between the previous version of the document and the new version of the document in the tamper-evident, immutable data repository.