Blockchain Analytics Permissions for Cross-Party Privacy Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing blockchain systems lack efficient mechanisms for generating customizable analytics across multiple parties while maintaining privacy and security, as they are designed for centralized data and lack explicit permission control.
Innovation Solution
A blockchain network with a consortium model that provides built-in and custom analytics, using smart contracts to manage permissions and generate analytics based on user-defined requirements, ensuring privacy and security through indexed data and permissioned access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If blockchain systems use centralized data access with full permissions, then analytics can be calculated freely, but privacy and security control is lost
Solution Approach 1:
The patent segments data access permissions by creating different permission levels (read-only, read-write, admin) and assigning them to different user roles. This allows analytics to be calculated freely within each permission boundary while maintaining overall privacy and security control through the segmented permission structure.
Solution Approach 2:
The patent introduces smart contracts as intermediaries that mediate between data requests and blockchain data. These smart contracts enforce permission checks and privacy rules, enabling analytics calculation while maintaining security control through the intermediary layer.
2Reliability
If blockchain systems implement strict privacy and security control, then data protection is improved, but analytics generation across multiple parties becomes difficult
Solution Approach 1:
The patent creates a universal analytics platform that can generate multiple types of analytics (transaction volume, value, patterns, comparisons) across different parties while maintaining permission control. The system provides multi-functionality by supporting various analytics types and permission levels within a single framework.
Solution Approach 2:
The patent implements dynamic permission checking where access rights are determined at runtime based on the specific analytics request and user credentials. This dynamic approach allows the system to adaptively grant or deny access to different data sets, enabling versatile analytics generation while maintaining security.
3Productivity
If conventional centralized data systems are used, then analytics can be calculated without constraints, but permission control and security are insufficient
Solution Approach 1:
The patent performs preliminary permission verification through smart contracts before analytics calculation begins. User credentials and permission levels are checked in advance, and only authorized data access is permitted. This preliminary action ensures both efficient analytics calculation and reliable permission control.
Data Source
AI summary
A blockchain of transactions may be referenced for various purposes and may be later accessed by interested parties for ledger verification and information retrieval. One example method of operation may include identifying a number of data parameters to extract from a blockchain based on a request for analytic data, creating one or more queries based on the data parameters, executing the one or more queries and retrieving the data parameters from the blockchain, identifying one or more permissions of a user account associated with the request for analytic data, and populating an interface with analytic figures based on the data parameters retrieved from the blockchain.