Multi-tenant Data Cleanroom for Privacy-Preserving Aggregation
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Solution Overview
Problem
Managing data from multiple sources in electronic multi-tenant systems is challenging due to privacy and regulatory concerns, making it difficult for companies to share and analyze user data across platforms while maintaining user privacy and compliance with legal restrictions.
Innovation Solution
An electronic multi-tenant data management system that implements an attestation and approval process for securely aggregating and accessing data from multiple providers, using identity resolution and anonymization services to obscure personally identifiable information and transform data according to predefined rules, ensuring compliance with data management requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data from multiple providers is aggregated and shared across platforms, then a more comprehensive user data picture is achieved, but privacy and regulatory compliance risks increase
Solution Approach 1:
The patent introduces a cleanroom as an intermediary environment where data from multiple providers is aggregated and processed. The cleanroom acts as a mediator between data providers and data accessors, enabling comprehensive data analysis while maintaining privacy through controlled access and transformation of data within this isolated environment.
Solution Approach 2:
The system creates transformed copies of the original data through the cleanroom transformation process. Instead of sharing raw data directly, the system generates transformed versions that maintain analytical value while removing or obscuring personally identifiable information, thus reducing privacy risks while preserving data utility.
2Productivity
If data aggregation and access are enabled across multiple tenants, then data analysis capabilities improve, but system complexity and security management difficulty increase
Solution Approach 1:
The cleanroom is designed as a universal platform that can handle data from multiple providers and serve multiple accessors with different permission levels. The system provides multi-functional capabilities including data aggregation, transformation, access control, and compliance validation within a single unified environment, reducing overall system complexity despite the increased functionality.
Solution Approach 2:
The system implements feedback mechanisms through permission validation and compliance checking. Before data access is granted, the system validates permissions and transforms data according to predefined rules, providing feedback loops that ensure security and compliance are maintained automatically throughout the data processing workflow.
3Reliability
If permission validation and data transformation are performed for each search query, then data security and compliance are ensured, but processing time and operational complexity increase
Solution Approach 1:
The system performs permission validation and data transformation rules in advance, before actual data access occurs. By pre-establishing permission frameworks and transformation protocols within the cleanroom, the system reduces the time required for individual search queries while maintaining consistent security and compliance standards.
Data Source
AI summary
Disclosed are methods and systems for providing a plurality of data corpuses for anonymization and aggregation. A plurality of data providers validate rules for accessing data by data requesters prior to data availability.