Big Data Access Control via Query Modifiers and Chaining
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Solution Overview
Problem
Current technologies lack fine-grained access control and efficient data manipulation capabilities for big data sharing across multiple parties in a distribution chain, limiting the ability to segment and transform data as needed.
Innovation Solution
The system enables controlled data access and segmentation by allowing intermediary parties to modify database query jobs, implementing access control and data transformation through query modifiers, and facilitating a multi-participant process called 'chaining' that decouples data from its presentation, enabling seamless data-as-a-service (eDaaS) on the cloud without requiring data copies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is made widely accessible to maximize value derivation, then data exploration capability is improved, but fine-grained access control becomes difficult to implement
Solution Approach 1:
The patent segments data into fine-grained units (rows, columns, or cells) and applies access control at each segment level through XML tags in the data dictionary. This allows different portions of the same dataset to have different access permissions, enabling both broad accessibility and precise control simultaneously.
Solution Approach 2:
The patent introduces an intermediary layer (the data dictionary with XML-based access control tags) between the data storage and the data access mechanisms. This intermediary enables fine-grained control without complicating the underlying data structure or access protocols.
2Productivity
If data is copied and distributed to multiple parties, then data sharing efficiency is improved, but data storage requirements and management complexity increase
Solution Approach 1:
The patent creates virtual copies of data through XML-based data dictionaries that describe data structure, access control, and transformation rules. These dictionaries can be distributed to multiple parties without duplicating the actual data, enabling efficient sharing while minimizing storage requirements.
Solution Approach 2:
The patent adds a metadata dimension (XML data dictionary) that overlays the physical data structure. This allows data to be shared and accessed from multiple perspectives without creating physical copies, transforming the problem from spatial duplication to informational description.
3Adaptability or versatility
If data is transformed and segmented for different consumers, then data utility is improved, but processing complexity increases
Solution Approach 1:
The patent performs data transformation, segmentation, and access control rule application in advance during data ingestion and preparation phases. Query modifiers are pre-configured with transformation rules, so that when queries are executed, the complex processing has already been prepared, reducing real-time processing complexity.
Solution Approach 2:
The patent uses XML parameters in data dictionaries to define transformation rules, segmentation criteria, and access control policies. By parameterizing these transformations, the system can adapt to different data consumers without hardcoding complex processing logic, making the system more manageable.
4Adaptability or versatility
If intermediary parties are added to the distribution chain, then access control flexibility is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal XML-based data dictionary framework that serves multiple functions: data description, access control policy definition, transformation rule specification, and intermediary party authentication. This single framework handles all these requirements without requiring separate complex systems for each function.
Data Source
AI summary
An ecosystem that allows fine-grained multi-party control over access to information stored in one or more data sources of a data provider. A requesting party can submit a query job to the data provider. Resellers in the chain can introduce their own query modifiers to the query job, adding additional data access, data transformation and segmentation functions to the query job. The data provider can append its own query modifier to the query job and execute the query job with all of the query modifiers. Access control for each link in the chain is checked before the query modifier for the link is executed. After execution of all query modifiers and the query job, the results can be provided to the requesting party.