Database Model Authorization via Distributed Ledger Validation
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Solution Overview
Problem
There is a need for a system to authorize data source access using distributed ledger technology before creating a database, as existing methods lack efficient mechanisms for securing sensitive information from various data sources.
Innovation Solution
A system utilizing distributed ledger technology and machine learning models to authorize database creation by identifying and validating data sources, determining authentication levels, and generating transaction objects for validation, ensuring secure access to sensitive data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distributed ledger technology is implemented to authorize data source access before database creation, then security and authorization control are improved, but system complexity and processing time increase
Solution Approach 1:
The system performs authorization validation before database creation by broadcasting transaction objects to data sources in advance. The distributed ledger validates data source permissions prior to population, ensuring security requirements are met before the database is created, thus preventing unauthorized access while maintaining systematic organization.
Solution Approach 2:
The distributed ledger acts as an intermediary between the database creation system and data sources. It validates authorization requests by broadcasting transaction objects to data sources and receiving validation responses, mediating the authorization process to ensure security without requiring direct complex interactions between all system components.
2Measurement precision
If machine learning models are used to identify and validate data sources, then authorization accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system uses machine learning models to identify data sources that are likely to be triggered when populating the database, rather than validating all possible data sources. This partial action approach focuses computational resources on the most relevant data sources, improving authorization accuracy while reducing overall processing time and resource consumption.
Solution Approach 2:
The system replaces manual or rule-based data source identification with machine learning models. The trained machine learning model automatically identifies and validates relevant data sources based on patterns learned from training data, improving identification accuracy while the system manages computational efficiency through selective application.
3Reliability
If authentication levels are checked against authorization requirements, then access control security is improved, but system processing overhead increases
Solution Approach 1:
The system determines authentication levels and checks them against authorization requirements before database creation proceeds. By performing this security check in advance through the distributed ledger validation process, the system ensures access control security is maintained while allowing efficient database creation once authorization is confirmed.
Data Source
AI summary
Systems, computer program products, and methods are described herein for authorizing a database model using distributed ledger technology. The present invention is configured to receive, from a computing device of a user, a physical database model; determine one or more data sources; initiate a second machine learning model on the one or more data sources and the physical database model; determine at least one data source that is likely to be triggered when populating a database created using the physical database model; generate a new transaction object for the physical database model; broadcast the new transaction object for the physical database model to the at least one data source in a distributed ledger for validation; receive a validation of the physical database model; and authorize a generation of a database using the physical database model based on at least receiving the validation.