Blockchain Exception Blocks Using Voice Hash Identity Verification
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Solution Overview
Problem
Existing systems face challenges in efficiently generating blocks in a blockchain network and handling exceptions or anomalies in user requests, which are prone to human error and labor-intensive processes, compromising security and reliability.
Innovation Solution
A system that generates blocks using voice-based hash values derived from unique user signatures, identifies exceptions, and resolves them using machine learning algorithms to improve security and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual evaluation of user requests is performed to identify incomplete or incorrect information, then exceptions can be detected, but the process becomes labor-intensive and prone to human error
Solution Approach 1:
The patent replaces manual mechanical evaluation with an automated system that uses voice-based hash values and blockchain technology to detect exceptions. The system extracts voice features, generates hash values, and automatically compares them against stored values to identify incomplete or incorrect information, eliminating human labor and associated errors.
Solution Approach 2:
The system enables self-service by allowing the blockchain network to automatically detect and flag exceptions without human intervention. The automated comparison of voice-based hash values against stored values allows the system to self-identify processing errors, information mismatches, and exceptions.
2Reliability
If voice-based hash values are used to generate blocks, then user identity verification and security are improved, but the block generation process becomes more complex
Solution Approach 1:
The system performs preliminary actions by pre-extracting voice features and pre-generating hash values before block creation. Voice features are extracted and stored as reference data, allowing for rapid verification during block generation without adding significant complexity to the main process.
Solution Approach 2:
The voice-based hash value serves multiple functions: it acts as a unique identifier for the user, provides security verification, enables exception detection, and serves as a key for blockchain block generation. This multi-functionality reduces the need for separate systems for each purpose.
3Productivity
If automated processing is implemented to reduce human error, then productivity increases, but the system may struggle to evaluate complex user requests
Solution Approach 1:
The system implements feedback mechanisms by automatically comparing generated hash values against stored reference values and providing immediate exception flags. This feedback loop allows the automated system to identify and handle complex cases by comparing them against established patterns and previously processed requests.
Solution Approach 2:
The system dynamically adapts by using machine learning models that can learn from processed requests and improve their evaluation capabilities. The blockchain network dynamically adjusts by storing new exception patterns and refining the automated evaluation criteria based on accumulated data.
Data Source
AI summary
A system for resolving exceptions in requests determines that a request comprises an exception. The exception impeded processing the request. The system generates a block in a blockchain network. Based on the stored details in the block, the type of exception is identified. Accordingly, the block is segregated for exception processing based on its exception type. The system stores the exception in the block. The system compares the request with user information previously provided by the user. The system determines a similarity score between the request and the user information. The system compares the similarity score with a threshold percentage. In response to determining that the similarity score exceeds the threshold percentage, the system determines that the exception can be resolved and resolves the exception.