Blockchain Reputation Records from DFA Transaction Fulfillment
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Solution Overview
Problem
Existing systems for providing user-related data, such as reputational information, are susceptible to attack and manipulation and are not well-suited for implementation in a distributed system like a blockchain.
Innovation Solution
A method and system for generating and storing user-related data, particularly reputational information, using a deterministic finite automaton (DFA) to evaluate transaction fulfillment and publish it on a blockchain, ensuring objective and efficient data generation and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If user-related data is stored in traditional centralized systems, then data retrieval and processing is simple, but the systems are susceptible to attack and manipulation
Solution Approach 1:
The patent introduces a blockchain as an intermediary layer between data generation and data access. The blockchain serves as a decentralized mediator that stores user-related data in a tamper-proof manner, eliminating the need for trust in centralized authorities while maintaining data integrity and resistance to manipulation.
Solution Approach 2:
The patent replaces traditional centralized mechanical data storage systems with a distributed blockchain system. This substitution involves replacing centralized databases with decentralized ledger technology, using cryptographic hashing and consensus mechanisms to ensure data integrity without requiring complex centralized security infrastructure.
2Reliability
If user-related data is stored on a blockchain, then the data becomes resistant to manipulation and decentralized, but the complexity of generating and extracting data increases
Solution Approach 1:
The patent implements self-service mechanisms where the blockchain system automatically generates user-related data through deterministic finite automaton (DFA) evaluation of transactions. The system also provides self-service data extraction through filter mechanisms that allow users to query their own data without requiring complex external processing, reducing overall system complexity despite the decentralized storage.
Solution Approach 2:
The patent changes the parameters of data storage by transforming user-related data into blockchain-specific formats (transactions with inputs and outputs). This parameter transformation simplifies the generation process by using standardized blockchain protocols and makes extraction easier through filter mechanisms that search for specific data patterns in the blockchain ledger.
3Reliability
If traditional systems are used for user data, then ease of operation is maintained, but the data can be manipulated and attacked
Solution Approach 1:
The blockchain acts as an intermediary that maintains security through decentralized storage while preserving ease of operation through standardized data formats and filter mechanisms. Users can access their data through simple queries without needing to understand the underlying blockchain complexity, thus maintaining operational simplicity while enhancing security.
4Reliability
If user-related data is stored on a blockchain, then the system becomes more secure and decentralized, but the speed of data retrieval decreases
Solution Approach 1:
The patent extracts relevant user-related data from the blockchain through filter mechanisms that efficiently search for specific data patterns. This extraction approach maintains security by keeping the full blockchain intact while enabling fast retrieval of needed information by filtering and extracting only the relevant data without scanning the entire blockchain.
Data Source
AI summary
A computer implemented system and a method for providing user related data, such as reputational information, on users of a blockchain involved in transactions is detailed. The method includes an approach for evaluating fulfilment of transactions, particularly in the context of contracts, and then providing a record of that on the blockchain through reputational information. As a result, at a late time, this reputational information can be retrieved. Similar reputational information for other transactions can be retrieved and linked to the same user, for instance based on the use of a hash of the master public key for a user. Aggregate reputational information can be computed from the pieces of reputational information retrieved.