AI Data Management System for IP Document Security and Storage
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Solution Overview
Problem
Current data management systems for intellectual property documents face challenges in securely managing access rights and encryption, particularly in handling time-based tasks with critical deadlines, and lack flexibility to accommodate varying security levels and complex tasks associated with intellectual property rights management.
Innovation Solution
A data management system employing advanced computing architecture with artificial intelligence (AI) capabilities to manage security levels (L0 to L3) by encrypting and decrypting documents, using pseudo-analog variable-state machines to mimic human cognitive functions, and integrating with a resource management system to handle time-based tasks efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If encryption techniques are used to secure documents in a server system, then document security is improved, but data storage capacity requirements increase
Solution Approach 1:
The patent segments encrypted data into multiple shards distributed across different storage locations. This segmentation allows the system to maintain high security through encryption while optimizing storage efficiency by storing only essential metadata and encrypted fragments rather than complete encrypted copies, thereby resolving the contradiction between security and storage capacity requirements
Solution Approach 2:
The patent introduces an intermediary encryption layer that transforms documents into encrypted format before storage, while maintaining an indexing system that allows efficient retrieval without storing full encrypted copies. This intermediary approach ensures document security through encryption while managing storage capacity by storing only necessary encrypted fragments and metadata
2Adaptability or versatility
If multiple security levels are implemented for different documents, then access control flexibility is improved, but system complexity increases
Solution Approach 1:
The patent applies local quality by assigning different security levels (L0-L3) to different documents or data segments based on their sensitivity requirements. Each document can have its own encryption level and access control policy, allowing flexible access control while managing system complexity through localized security policies rather than uniform system-wide complexity
Solution Approach 2:
The patent implements dynamic security level assignment where documents can be moved between security levels based on their current state (e.g., published vs. unpublished patent applications). This dynamic approach provides access control flexibility while managing complexity through automated level transitions rather than static complex configurations
3Productivity
If AI processes are implemented in computing hardware, then data processing efficiency is improved, but hardware complexity increases
Solution Approach 1:
The patent replaces traditional mechanical computing systems with AI-based computing hardware that uses neural networks and machine learning algorithms. This substitution improves data processing efficiency for tasks like document classification, security level determination, and metadata extraction, while managing hardware complexity through specialized AI accelerators rather than general-purpose complex hardware
Data Source
AI summary
There are provided various systems for performing tasks associated with IPR procurement. The systems employ a computing architecture that is operable to provide characteristics of artificial intelligence. The computing architecture employs a configuration of pseudo-analog variable-state machines that is implemented by disposing the pseudo-analog variable-state machines in a hierarchical arrangement, wherein pseudo-analog variable-state machines higher in the hierarchical arrangement are operable to mimic behavior of a human claustrum for performing higher cognitive functions when processing information associated with one or more service requests and for performing quality checking of the one or more work products. Moreover, the computing architecture is susceptible to being implemented by employing a novel configuration of data processing devices.