AI-Enhanced Ledger Computing Environment System
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Solution Overview
Problem
Current informational systems rely heavily on manual inputs, leading to data integrity and accountability challenges, especially in analytics and decision-making processes, and existing ledger technologies like blockchain require significant computational power and external validators, which are environmentally unfriendly and insecure.
Innovation Solution
A self-sovereign, artificially intelligent computing-based ledger system with dual-layer entropic floating encryption that operates in both quantum and non-quantum environments, eliminating the need for external validators and using AI to create an irrefutable audit trail and enhance security, scalability, and user accountability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If blockchain and HDSS are used for ledger technology, then data integrity and security are improved, but energy consumption increases and environmental friendliness deteriorates
Solution Approach 1:
The system employs self-sovereign encryption where each user generates their own encryption keys and the system automatically manages key distribution and rotation without requiring energy-intensive external validators or mining processes. The AI component autonomously monitors and maintains encryption integrity, eliminating the need for continuous external validation computations.
Solution Approach 2:
The patent transitions from blockchain's fixed cryptographic hash parameters to dynamic AI-generated encryption parameters that adapt to each transaction's complexity and sensitivity. This allows the system to use computational resources efficiently by applying stronger encryption only when needed, rather than uniformly across all transactions.
2Reliability
If blockchain and HDSS are used for ledger technology, then data integrity is improved, but system complexity and device requirements increase
Solution Approach 1:
The system extracts the validation function from external validators and mining processes, embedding it directly into the transaction structure through AI-generated cryptographic signatures. This eliminates the need for separate validation layers and reduces system complexity by integrating security functions within the ledger itself rather than requiring external infrastructure.
Solution Approach 2:
The patent introduces an AI-based intermediary layer that mediates between data entry and encryption, automatically generating appropriate cryptographic parameters and managing key distribution. This intermediary simplifies the system architecture by centralizing security management functions rather than requiring complex peer-to-peer validation protocols.
3Ease of operation
If manual inputs are used in informational systems, then ease of operation is maintained, but data integrity and accountability deteriorate
Solution Approach 1:
The system implements real-time feedback mechanisms where the AI component monitors data entry processes and automatically generates cryptographic records of all inputs. This feedback loop provides immediate confirmation of data integrity while maintaining ease of operation, as users simply enter data normally while the system autonomously captures and verifies the input's authenticity.
Solution Approach 2:
The patent employs self-service automation where the system automatically generates, stores, and manages cryptographic records of all manual inputs without requiring user intervention. This maintains the simplicity of manual data entry while ensuring complete audit trails and accountability through autonomous recording mechanisms.
4Reliability
If external validators and mining are used in blockchain, then security is improved, but scalability and environmental friendliness deteriorate
Solution Approach 1:
The system eliminates external validators by implementing self-sovereign encryption where each transaction carries its own cryptographic verification. This self-validating mechanism scales linearly with transaction volume without requiring additional external computational resources, as each transaction independently verifies its own integrity through embedded AI-generated cryptographic signatures.
Solution Approach 2:
The patent segments the validation function from centralized external validators and distributes it across individual transactions through independent cryptographic signatures. This segmentation allows parallel processing of transactions without coordination overhead, significantly improving scalability while maintaining security through distributed cryptographic verification rather than centralized mining.
Data Source
AI summary
A method based on converging a platform-neutral, self-sovereign ledger technology and artificial intelligence in a virtual machine environment concerning the collective efforts and outcomes of an entity (e.g., person, team, or organization) or group of entities in both quantum and non-quantum computing environments. This method results in an artificially intelligent ledger with dual-layer floating encryption and available steganographic integration, which contains representations of things of value (past, current, and future outcomes, including data and other information) concerning entities (e.g., individuals, groups of people, or organizations) engaged in collective effort (e.g., trade, finance, work, or activism). Furthermore, this method produces a means of validating, auditing, and analyzing data and other information and automatically communicating that data and other information to stakeholders.