Hash Tree Proofs for Private Databases on Public Blockchains
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Solution Overview
Problem
Existing methods for securing private structured databases on public blockchains face challenges in ensuring data privacy and integrity while maintaining a decentralized and trustless consensus.
Innovation Solution
A method involving hash trees and blockchain objects is employed to secure private structured databases by generating hash trees representing data states, submitting transactions to create blockchain objects with root hashes, and using non-interactive proofs of inclusion to manage data updates and transactions, ensuring data privacy and integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If private structured databases are stored on public blockchains, then data privacy is improved, but data integrity and public inspection capability deteriorate
Solution Approach 1:
The database is segmented into individual data units that are independently hashed and stored on the blockchain. Each data unit can be individually verified through its hash without exposing the actual data content, resolving the contradiction between privacy protection and integrity verification.
Solution Approach 2:
Cryptographic hash functions serve as intermediaries between the private data and the public blockchain. The hash values are stored on-chain while the actual data remains private, allowing public verification of data integrity without compromising data privacy.
2Reliability
If hash trees are generated for each data state to ensure integrity, then data verification reliability is improved, but computational complexity and processing time worsen
Solution Approach 1:
The hash tree structure segments the computational work into manageable parts, where only the root hash needs to be stored on-chain while intermediate hashes are computed locally. This reduces on-chain data storage requirements and simplifies verification processes.
Solution Approach 2:
Hash trees are generated in advance for each data state before submission to the blockchain. This preliminary computation allows for efficient verification later, as the structural integrity checks are already performed and the root hash is ready for immediate comparison.
3Productivity
If non-interactive proofs of inclusion are used to manage data updates, then transaction processing efficiency is improved, but proof verification complexity worsens
Solution Approach 1:
Non-interactive proofs of inclusion act as intermediaries that enable efficient verification of data unit membership in the database without requiring interactive communication between nodes. The proofs are generated once and can be verified independently, improving transaction processing efficiency while maintaining verifiable security.
4Quantity of substance
If root hashes are stored in blockchain objects to represent data states, then data storage efficiency is improved, but data retrieval capability deteriorates
Solution Approach 1:
Only the essential root hash is extracted and stored on the blockchain, while the complete data can be retrieved locally or from off-chain storage. This extraction approach maintains storage efficiency on-chain while preserving full data retrieval capability through local copies and verifiable proofs.
Data Source
AI summary
A method includes: generating a hash tree representing a structured data object including a data unit, the hash tree including a root hash and a data unit hash representing the data unit; submitting a first transaction to a distributed network, the first transaction configured to generate a blockchain object including the root hash, the blockchain object configured to generate an announcement representing membership of the data unit hash in the hash tree; and submitting a second transaction to the distributed network, the second transaction configured to trigger the blockchain object to generate the announcement based on a proof of inclusion of the data unit hash within the hash tree.