Blockchain Reliability Database for External Data Verification
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Solution Overview
Problem
Blockchain systems face challenges in verifying the reliability of external data sources, as they typically rely on external sources without mechanisms to assess or update their reliability, leading to potential fraud and improper transactions.
Innovation Solution
A system that retrieves reliability data from multiple external sources, determines a combined reliability value, and stores this information in a distributed ledger, allowing for proactive updates and consensus among peer nodes to ensure the reliability of external data sources is accurately tracked and maintained.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If blockchain systems rely on external data sources without verification mechanisms, then data access simplicity is improved, but data reliability deteriorates due to potential fraud and improper transactions
Solution Approach 1:
The patent introduces an intermediary verification mechanism that acts as a mediator between external data sources and the blockchain system. This intermediary layer validates external data through multiple checks including data format verification, source authentication, and cross-referencing with existing blockchain records, thereby maintaining data access simplicity while ensuring data reliability through systematic verification protocols
Solution Approach 2:
The patent implements a feedback mechanism where the blockchain system continuously monitors and evaluates the reliability of external data sources. Based on this feedback, the system dynamically adjusts verification levels and updates trust scores for external sources, enabling automatic adaptation to changing reliability conditions while maintaining operational simplicity through automated decision-making
2Device complexity
If no reliability tracking mechanism is implemented for external data sources, then system complexity is reduced, but fraud detection capability deteriorates
Solution Approach 1:
The patent applies preliminary action by establishing reliability tracking mechanisms and verification protocols before external data sources are utilized. The system pre-establishes trust criteria, authentication methods, and monitoring frameworks in advance, enabling fraud detection capability to be built-in rather than added reactively, thus managing complexity through proactive system design
Solution Approach 2:
The patent segments the reliability tracking function into distinct modular components including data validation modules, source authentication modules, trust scoring modules, and monitoring modules. This segmentation allows each component to handle specific aspects of fraud detection independently, reducing overall system complexity while comprehensively addressing fraud detection capabilities through specialized sub-systems
Data Source
AI summary
An example operation may include one or more of receiving a request for trust information of an off-chain data source from a client, detecting that the trust information of the off-chain data source is not stored in a distributed ledger shared among a plurality of peer nodes, retrieving reliability data recursively identified and retrieved from a plurality of external sources having different reliability information of the off-chain data source, determining a reliability value based on a combination of the retrieved reliability data from the plurality of external sources, and transmitting the determined reliability value to the client.