Self-aware e-Currency Token Offline Authentication
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Solution Overview
Problem
Existing e-Currency platforms face challenges in validating and authenticating e-Currency tokens across diverse transactions, especially when tokens are used in off-line transactions, as they lack a system to reappear on-line and maintain their authentication and rating.
Innovation Solution
A computer-implemented method and system that tracks the lifecycle of e-Currency tokens, allowing them to reappear on-line by recording off-line transaction events on an external memory device and rebuilding their past state using nearby tokens, enabling continued authentication and validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If e-Currency tokens are used in off-line transactions, then the tokens can be used in conventional physical stores or independent financial systems, but the tokens cannot reappear on-line to continue authentication and validation
Solution Approach 1:
The system performs preliminary actions by creating an off-line transaction record with all necessary token information (token ID, value, timestamp, counterparty) before the token goes off-line. This pre-prepared record enables the token to reappear on-line and be immediately revalidated without loss of authentication continuity.
Solution Approach 2:
An off-line transaction record acts as an intermediary between the on-line platform and off-line transactions. This record stores token state information and transaction details, serving as a bridge that allows tokens to maintain their identity and authentication status across off-line periods when they are used in physical stores or independent systems.
2Reliability
If the platform tracks every transaction of e-Currency tokens, then authentication and validation can be maintained, but the system complexity increases
Solution Approach 1:
The system extracts only the essential token tracking information needed for validation (token ID, value, transaction timestamp, counterparty identifier) and stores it in off-line transaction records. This selective extraction reduces complexity by focusing only on critical data elements rather than tracking all possible transaction attributes.
Solution Approach 2:
When a token goes off-line, the system creates a simplified copy of the token's essential state information in an off-line transaction record. This copy contains only the necessary validation data, reducing the complexity burden while maintaining validation capability when the token returns on-line.
3Measurement precision
If multiple recorded values for a token are aggregated to grade its price, then the price accuracy improves, but the processing time increases
Solution Approach 1:
The system applies partial aggregation by selecting a representative subset of recorded values for price grading rather than processing all historical values. This approach achieves sufficient price accuracy without the excessive processing time that would result from aggregating every single recorded value, balancing precision with efficiency.
Data Source
AI summary
A token file is received from an e-Commerce platform having a veracity grade capability. An off-line transaction is made using the token which records events of the transaction. Subsequently, the token re-enters the e-Currency platform and transfers the recorded off-line events. The platform rebuilds the token's past state based upon the state of nearby tokens and the recorded events, so that additional transactions can be rated, including a veracity grade.