Third-Party Agent Broker for Context-Based Data Access Validation
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Solution Overview
Problem
Existing data exchange systems involving AI agents face challenges in validating data access requests, potentially compromising ethical, legal, privacy, or personal standards due to the integration of sensitive personal data with external resources.
Innovation Solution
A third-party agent broker is deployed to validate data access requests using personalized access models generated from user-specific data, applying machine learning techniques to determine the validity of requests and generate valid access tokens, while adhering to corporate governance and user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If AI agents directly access external resources and databases containing sensitive personal data, then the AI agents can perform autonomous tasks and achieve predetermined goals, but ethical, legal, privacy, or personal standards may be compromised
Solution Approach 1:
The patent introduces an intermediary validation system that sits between AI agents and external resources/databases. This intermediary validates data access requests by checking contextual information against ethical, legal, and privacy standards before allowing access, thus maintaining autonomous task execution while ensuring compliance with standards.
2Reliability
If manual validation of data access requests is performed to ensure ethical and legal compliance, then privacy and personal standards are protected, but system latency increases and productivity decreases
Solution Approach 1:
The patent implements preliminary action by pre-establishing validation rules, contextual parameters, and access policies before data exchange occurs. The validation system is pre-configured with ethical, legal, and privacy standards, enabling automated real-time validation without manual intervention during actual data exchanges, thus maintaining both privacy protection and high productivity.
3Reliability
If comprehensive validation of data access requests is implemented to prevent unauthorized access, then network security is improved, but system complexity and processing time increase
Solution Approach 1:
The patent applies segmentation by dividing the validation system into modular components that handle different aspects of security validation independently. Each module validates specific contextual parameters or ethical/legal criteria, allowing comprehensive security checks while maintaining manageable system complexity through modular architecture and clear separation of validation functions.
Data Source
AI summary
Techniques (e.g., software, hardware, and/or machine-learned model(s)) may generate a third-party agent broker for validating data access requests on behalf of a resource provider. This third-party agent broker may validate the data access requests against a personalized access model associated with the resource provider. The context of the data access requests may be checked for similarity to the personalized access model (e.g., via embedding the data access request and the personalized access model). The data access requests may then be fulfilled based on validating the context of the data access requests.