Evidence Chains and Timestamp Chains for Data Ordering Proof
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Solution Overview
Problem
Existing data management systems using distributed ledger technology face challenges in efficiently proving the ordering and integrity of data, particularly in verifying the ordering and times of confirmation across multiple ledgers.
Innovation Solution
A data management device and method that utilizes a distributed ledger with evidence chains and a timestamp chain, where hash values and timestamp tokens are used to efficiently update and verify the ordering and integrity of data, reducing verification costs by selectively processing only changed data and allowing for user-controlled verification processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If time stamp tokens are acquired for all evidence chains, then the ordering and integrity of all data can be verified, but the verification cost increases significantly
Solution Approach 1:
The system segments the verification process by dividing evidence chains into groups based on their terminal hash values. Instead of verifying all chains uniformly, the system identifies and processes only those chains whose terminal hash values have changed, thereby segmenting the verification workload according to actual changes in the data structure.
Solution Approach 2:
The system applies partial action by acquiring time stamp tokens only for the necessary subset of evidence chains rather than all chains. By determining which chains require verification based on terminal hash value changes, the system performs exactly the amount of verification needed—no more, no less—thereby reducing unnecessary verification costs while maintaining integrity.
2Reliability
If the update process is executed every time a file changes, then data integrity is maintained in real-time, but the processing workload increases
Solution Approach 1:
The system implements periodic action by executing the update process at predetermined intervals rather than continuously responding to every file change. This periodic execution allows the system to batch processing tasks, reducing the overall processing workload while still maintaining data integrity through regular updates.
Solution Approach 2:
The system employs self-service mechanisms by automatically detecting changes in terminal hash values and triggering verification only when necessary. The system monitors its own state, identifies which evidence chains require updates based on hash value changes, and executes verification processes autonomously without requiring external intervention for every file change.
3Reliability
If verification processes are executed frequently, then data tampering is detected quickly, but the system resources are consumed
Solution Approach 1:
The system uses feedback mechanisms by monitoring terminal hash values of evidence chains and using this information to determine when verification is necessary. The feedback loop compares current terminal hash values with previous values, and only triggers verification processes when changes are detected, thereby optimizing resource consumption while maintaining tampering detection capability.
Solution Approach 2:
The system changes the verification parameter from a fixed frequency-based approach to a state-based approach. Instead of verifying at regular intervals regardless of data state, the system changes its behavior based on whether terminal hash values have changed. This parameter change allows the system to adapt verification frequency to actual data changes, reducing resource consumption when no changes occur.
Data Source
AI summary
A device includes: a storage storing a distributed ledger, the distributed ledger including a plurality of evidence chains and a time stamp chain, the plurality of evidence chains storing in chronological order at least one hash value, the time stamp chain storing in chronological order at least one time stamp token; and a processor configured to repeatedly execute an update process such that the time stamp chain is updated, the update process including a process for identifying, out of the evidence chains, at least one evidence chain in which the hash value has been changed with a change in the file since previous execution of the update process, and acquiring the time stamp token for a terminal value generated based on a terminal hash value of the at least one evidence chain.