Data Provenance Objects for Decentralized IP and Compliance Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing edge computing systems face challenges with resource constraints, power management, and security issues, particularly in multi-tenant environments, which affect latency and compliance with data privacy and security requirements.
Innovation Solution
Implementing decentralized data supply chain objects that enable data protection, enforce intellectual property rights, and facilitate compensation compliance in a distributed and decentralized ecosystem, without requiring centralized control, and utilizing edge computing to distribute resources closer to endpoints for improved latency and compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If decentralized data supply chain objects are implemented, then data protection and compliance management are improved, but device complexity increases
Solution Approach 1:
The system segments data supply chain management into discrete, standardized objects that can be independently created, tracked, and managed. Each data object contains specific metadata fields (creator, creation time, transformations, usage rights) that can be independently validated and enforced, breaking down the complex task of data provenance into manageable units.
Solution Approach 2:
The patent introduces an intermediary data supply chain object layer between raw data and end applications. This intermediary structure standardizes data representation and enforcement mechanisms, allowing complex compliance rules to be implemented through standardized object interfaces rather than custom solutions for each scenario.
2Speed
If edge computing is used to distribute resources closer to endpoints, then latency is reduced, but security issues in multi-tenant environments worsen
Solution Approach 1:
The system implements local quality control by enabling each edge device to independently validate data supply chain objects against compliance rules locally, without requiring centralized verification. This allows security enforcement to be distributed across multiple tenants while maintaining data privacy and reducing latency through local decision-making.
Solution Approach 2:
Data supply chain objects are pre-configured with compliance metadata (usage rights, transformations, restrictions) before data processing occurs. This preliminary structuring of compliance information allows edge devices to enforce security rules immediately upon receiving data objects, eliminating the need for complex runtime security negotiations in multi-tenant environments.
3Adaptability or versatility
If decentralized control is implemented without centralized authority, then adaptability is improved, but difficulty of detecting and measuring worsens
Solution Approach 1:
The system implements feedback mechanisms where data supply chain objects carry metadata that automatically updates and propagates through the decentralized network. Each transformation and usage of data generates feedback information (timestamps, creator identifiers, transformation details) that is embedded in the object itself, enabling automatic provenance tracking without centralized coordination.
Solution Approach 2:
The patent uses cryptographic copying mechanisms where data supply chain objects are replicated across the decentralized network with immutable metadata. Each copy contains verified provenance information that can be independently validated, allowing the system to maintain consistent provenance records across distributed nodes without requiring a central authority to coordinate updates.
Data Source
AI summary
Apparatus, systems, articles of manufacture, and methods are disclosed for generating a data supply chain object. An example non-transitory computer readable storage medium disclosed herein includes data which may be configured into executable instructions and, when configured and executed, cause one or more processors to at least: derive a provenance of a first data supply chain object; identify a first stakeholder from the provenance; determine if the first stakeholder is verified; utilize data associated with the data supply chain when the first stakeholder is verified; build a tag-value structure based on the utilization of the data; build a second data supply chain object based on the tag-value structure and an identity of a second stakeholder; and add the second data supply chain object to the data supply chain.