Distributed Ledger Data Fragmentation for Secure Access Monetization
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Solution Overview
Problem
Existing data security systems are vulnerable to attacks and lack effective methods for securely storing and monetizing critical data, failing to maintain confidentiality and adapt to environmental conditions.
Innovation Solution
A multi-modal, modular data security and monetization system that utilizes distributed ledgers or blockchains with cellular immutability and connectivity, employing automatic information search operations to enhance data security and value, and dispersing data across secure storage facilities to protect and monetize critical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored in centralized secure locations, then data security is improved, but vulnerability to attacks and lack of adaptability worsen
Solution Approach 1:
The patent segments critical data into multiple fragments and distributes them across numerous decentralized storage locations (data lakes, data exchanges, cloud storage) rather than storing in a single centralized location. This segmentation approach maintains security while improving adaptability, as the system can respond to attacks by accessing alternative fragmented data sources.
Solution Approach 2:
The patent introduces a temporal dimension to data storage by implementing time-based access controls and data versioning. Data fragments are stored with timestamp metadata, allowing the system to retrieve historical versions of data or switch to alternative storage locations based on temporal conditions, thereby enhancing adaptability to security threats.
2Reliability
If data is encrypted and secured with predetermined clearance levels, then confidentiality is improved, but ability to monetize and distribute data worsens
Solution Approach 1:
The patent implements dynamic encryption key management where access keys and clearance levels can be modified in real-time based on user credentials, payment verification, and security conditions. This allows the system to maintain strong encryption for confidentiality while flexibly granting access to authorized users who meet security and payment requirements, enabling data monetization.
Solution Approach 2:
The patent changes the parameters of data access by implementing multi-factor authentication, dynamic clearance levels, and conditional access policies. These parameter changes allow the system to maintain high security thresholds while permitting authorized access for legitimate purposes including monetization transactions, thereby resolving the contradiction between confidentiality and distribution flexibility.
3Reliability
If data fragments are distributed across multiple locations, then security against attacks is improved, but data reconstruction complexity worsens
Solution Approach 1:
The patent implements feedback mechanisms through metadata catalogs and distributed indexing systems that track the location, status, and integrity of data fragments across multiple storage locations. This feedback system automatically guides the reconstruction process by identifying available fragments and their required assembly order, significantly reducing reconstruction complexity despite data distribution.
Solution Approach 2:
The patent enables self-service data reconstruction through automated algorithms that independently locate, retrieve, and assemble data fragments from distributed storage locations. The system uses embedded metadata and cryptographic proofs to automatically verify fragment authenticity and reconstruct original data without requiring complex manual coordination, thereby reducing reconstruction complexity.
4Loss of information
If automatic information search operations are implemented, then data value enhancement is improved, but system complexity and computational requirements worsen
Solution Approach 1:
The patent performs preliminary actions by pre-processing data during the fragmentation and storage phase, embedding metadata, keywords, and contextual information into each data fragment. This preliminary indexing and tagging enables subsequent automatic information search operations to efficiently enhance data value without requiring complex real-time processing, thereby reducing system complexity.
Data Source
AI summary
System and method secures critical data on distributed ledger (DL) or blockchain (Bchn) or linked memory cell (LCM) data construct. Each cell in DL/Bchn/LCM has cellular immutability and cellular connectivity characteristics. System randomly stores critical data in the DL/Bchn/LCM based with initial state function and stores nonsensical data in other cells based upon nonsensical initial state function which is inferior to the critical data function. The DL/Bchn/LCM has a stem, with stem cells, forking cells and branches with branch cells created by forking initial state function (sometimes triggered by cyber attacks, sometimes by new growth). Trees of DL/Bchn/LCM are formed as are forests of DL/Bchn/LCM trees. automatic information search operations (AISO) through data collections also grow stems and branches on the DL/Bchn/LCM trees. The AISO generates supplemental (Supple) data based on supple initial state function. Supple data is further dispersed and randomly stored in the DL/Bchn/LCM trees and/or forest.