Semantic Taxonomy Validation for Immutable Ledger Requests
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Blockchain systems face challenges in managing illegal or malicious content due to their immutable and decentralized nature, making it difficult to remove such content once added, and conventional methods are either ineffective or disruptive.
Innovation Solution
Implementing a semantic-taxonomy-based system using a semantic graph to validate and enforce predefined templates for blockchain requests, preventing illegal or malicious content from being added by leveraging RDF for extensibility and interoperability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If blockchain systems allow free input fields for transaction requests, then usability and flexibility are improved, but the risk of illegal or malicious content being added to the ledger increases
Solution Approach 1:
The system performs preliminary validation of transaction requests against a semantic taxonomy before they are added to the blockchain. By checking input fields against predefined templates and semantic rules in advance, the system prevents illegal or malicious content from being recorded, while still allowing users flexible input fields for legitimate transactions.
Solution Approach 2:
A semantic taxonomy validation layer is introduced as an intermediary between users and the blockchain ledger. This intermediary component evaluates transaction requests against semantic rules and templates, blocking harmful content while permitting legitimate transactions, thus resolving the contradiction between usability and content safety.
2Adaptability or versatility
If conventional methods are used to remove illegal content from blockchain, then content management is improved, but the immutable and decentralized nature of blockchain is compromised
Solution Approach 1:
Instead of attempting to remove content after it is added to the blockchain, the system performs preliminary validation to prevent illegal or malicious content from being recorded in the first place. This approach maintains blockchain immutability while enabling effective content management through proactive prevention rather than reactive removal.
3Object-affected harmful factors
If semantic taxonomy validation is implemented for all input fields, then content safety is improved, but system complexity increases
Solution Approach 1:
The validation system is segmented into modular components: a semantic taxonomy definition layer, a validation engine layer, and a template management layer. This segmentation allows the complex validation functionality to be implemented in a structured, maintainable way that prevents illegal content while managing system complexity through modular design.
Data Source
AI summary
Techniques are disclosed for evaluating immutable ledger requests using a semantic taxonomy. An example system includes a memory comprising instructions, and a processor configured to execute the instructions. Example instructions include providing a semantic taxonomy of semantically linked terms and phrases; using the semantic taxonomy to validate input fields of requests for immutable ledger transactions according to one or more predefined templates; and submitting the validated requests to an immutable ledger.


