Quarantine Database Controls for Sensitive Data Sharing
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Solution Overview
Problem
The sharing of data between parties raises concerns about privacy and security, particularly when sensitive information is involved, as existing systems lack effective mechanisms to restrict access and ensure proper handling of such data.
Innovation Solution
A computer-implemented method and system that involves storing data in a quarantine database where copying, moving, and sharing are restricted until authorized, parsing the data to identify sensitive portions, applying sensitivity markers, and granting access to authorized users based on access permissions and markers, while allowing interactive and dynamic user interfaces for efficient data presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is shared between parties, then data utility and collaboration are improved, but privacy and security risks increase
Solution Approach 1:
The patent segments data access control into multiple layers: sensitivity markers categorize data portions by sensitivity level, and role-based access control divides user permissions into distinct roles. This segmentation allows selective sharing of non-sensitive data while protecting sensitive portions, enabling collaboration without compromising security.
Solution Approach 2:
The system introduces an intermediary data governance layer that mediates between data sharing needs and security requirements. Sensitivity markers act as intermediaries to classify data, while the access control system serves as a mediator to enforce appropriate access restrictions based on user roles and data sensitivity, allowing safe data collaboration.
2Reliability
If access restrictions are imposed on data, then security is improved, but data accessibility and usability deteriorate
Solution Approach 1:
The access control system is dynamic rather than static. Access permissions are automatically determined by the system based on the user's role and the sensitivity markers of the data, rather than requiring manual configuration for each data-access pair. This dynamic approach maintains security while simplifying user interaction.
Solution Approach 2:
The system provides self-service data access where users can independently determine what data they can access based on their assigned roles and the sensitivity markers visible in the interface. The system automatically enforces access restrictions without requiring users to seek special permissions, making secure data access as easy as unrestricted access.
3Reliability
If sensitivity markers are applied to data portions, then data security control is improved, but system complexity increases
Solution Approach 1:
The system changes the parameter of data classification from complex policy-based rules to simple sensitivity marker tags. Each data portion is assigned a sensitivity marker (e.g., public, internal, confidential) that serves as a manageable parameter for access control, reducing system complexity while maintaining precise control.
4Reliability
If data is stored in quarantine database with restrictions, then security is improved, but data productivity and processing speed decrease
Solution Approach 1:
Sensitivity markers are applied to data portions during the data ingestion phase rather than during access or processing. This preliminary classification allows the data to be quickly accessed and processed later without real-time security checks, maintaining both security and productivity.
Data Source
AI summary
A computer system is configured to receiving a data set from a data provider and automatically save the data set in a quarantine database where copying, moving, and sharing of the data set are restricted until the data set is released by a data provider. The data set is parsed to find and mark portions with potentially sensitive information. At least those parts are reviewed by a data governor, who can confirm, add, edit, or remove markers. Those parts can be visually indicated to the data governor, along with a preview of, metadata about, and analysis of the data set. After reviewing at least the automatically marked portions, the data governor can release the data set to a non-quarantine database where another user can use the data set. The user is restricted from accessing the quarantine database.