Blockchain Ledger Stakeholder Access via Event Inference
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Solution Overview
Problem
Current systems face challenges in efficiently identifying and granting access to interested stakeholders in a blockchain ledger following an event, such as a traffic collision, which complicates insurance claim processing and recordkeeping.
Innovation Solution
A method is introduced that analyzes blocks in a blockchain ledger by deriving inferences from event data and historical data to identify interested stakeholders, adding them to a group with access to the ledger, thereby streamlining access and record management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all potential stakeholders are granted access to the blockchain ledger, then transparency and verification are improved, but system complexity and access management overhead increase
Solution Approach 1:
The system automatically identifies interested stakeholders through analysis of event data and historical blockchain data, eliminating the need for manual access management. The stakeholder identification and access granting process is performed autonomously by the system based on predefined criteria and event context.
Solution Approach 2:
The system pre-identifies and pre-grants access to stakeholders before they need to access the ledger. By analyzing event data and determining interested parties in advance, the system prepares the access structure proactively, reducing complexity during actual access operations.
2Reliability
If manual identification of stakeholders is used, then access control is secure, but processing time and operational complexity increase
Solution Approach 1:
The manual mechanical process of stakeholder identification is replaced with an automated computational system that analyzes event data and historical blockchain records. This substitution maintains security through systematic analysis while dramatically improving processing speed and eliminating human operational bottlenecks.
Solution Approach 2:
The system continuously monitors blockchain events and uses feedback from event data to automatically update stakeholder identification. This real-time feedback mechanism ensures access control remains secure and accurate while operating at automated speeds, as the system adjusts stakeholder lists dynamically based on current event context.
3Productivity
If automated stakeholder identification is implemented, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The automated identification system serves multiple functions: it analyzes event data, determines stakeholder interest, manages access control, and maintains records. This multi-functionality consolidates what would otherwise require separate systems into a single integrated solution, improving efficiency without proportionally increasing overall system complexity.
Data Source
AI summary
Approaches presented herein enable automatically fulfilling an obligation under a smart contract. A block is added to a blockchain ledger in response to an event that triggers the obligation. The block includes data related to the event. Inferences related to the event are derived based on an analysis of event data and historical data incorporated in prior blocks in the blockchain ledger. Based on the inferences, a potential cause of the event is derived. Based on the potential cause, an interested stakeholder to the fulfilling of the obligation is identified. The interested stakeholder is added to a group that is allowed access to the blockchain ledger corresponding to the smart contract.