Tokenized Query Control for Secure Data Sharing
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Solution Overview
Problem
Existing data sharing environments face challenges in securely managing and limiting queries to prevent data misuse by malicious users, particularly when third-party cloud services are used, leading to potential data security breaches and increased processing costs due to data duplication and lack of owner control over data exposure.
Innovation Solution
Implementing a centralized data sharing model with a single data source that allows owners to control data exposure and access restrictions, using token-based authorization and monitoring to limit query execution time and frequency, ensuring secure and efficient data access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If third-party cloud services are used to store company data and enable restricted access for running queries, then data sharing capability is improved, but data security deteriorates due to potential abuse by malicious users running large numbers of queries
Solution Approach 1:
The patent introduces a query management system as an intermediary layer between the data sharing platform and users. This intermediary monitors, controls, and limits query execution, preventing malicious users from running excessive queries while still allowing legitimate data sharing operations to proceed normally
Solution Approach 2:
The system dynamically adjusts query parameters such as execution time limits, frequency restrictions, and resource allocation based on user behavior analysis. By changing these parameters in real-time, the system can respond to potential security threats while maintaining efficient data sharing for authorized users
2Adaptability or versatility
If data is shared across multiple business units using third-party cloud services, then data accessibility is improved, but processing costs increase due to data duplication
Solution Approach 1:
The patent implements a centralized data storage architecture where all business units access data from a single source through the query management system. This merging approach eliminates data duplication across multiple copies while maintaining accessibility for all authorized users, thereby reducing processing costs associated with storing and managing redundant data
3Productivity
If query execution is allowed without limitations, then data analysis efficiency is improved, but data security deteriorates due to potential stitching together of proprietary data sets
Solution Approach 1:
The query management system implements continuous monitoring and feedback mechanisms that track query patterns, execution frequencies, and results. This feedback is used to detect potential data stitching activities and adjust query limitations dynamically, maintaining data analysis efficiency for legitimate operations while preventing security breaches
4Reliability
If centralized data sharing model with single data source is implemented, then data control is improved, but system complexity increases
Solution Approach 1:
The query management system is designed as a universal platform that handles multiple functions including authentication, query execution, monitoring, limiting, and tracking within a single integrated architecture. This multi-functionality reduces the need for separate systems for each function, thereby managing complexity while maintaining strong centralized data control
Data Source
AI summary
The present disclosure relates generally to techniques for limiting and tracking queries in a data sharing environment such as a data cleanroom. A shared tokening may provide owner account control over sharing to client accounts within the data sharing environment.